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Characterization of genomic alterations in CIITA and their functional and clinical implications in malignant… Mottok, Anja 2017

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   CHARACTERIZATION OF GENOMIC ALTERATIONS IN CIITA AND THEIR FUNCTIONAL AND CLINICAL IMPLICATIONS IN MALIGNANT LYMPHOMAS by  Anja Mottok  MD, Johann Wolfgang Goethe-University Frankfurt am Main, 2005  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Pathology and Laboratory Medicine)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   June 2017  © Anja Mottok, 2017  ii Abstract Emerging evidence that the interplay between tumour cells and reactive immune cells has profound impact on tumour development, evolution and progression inspired the field of cancer research for the last decade. It has become apparent that the evolutionary pressure exerted by the immune system leads to the evolution of various mechanisms by which tumour cells escape immune surveillance. These often include somatically acquired genetic alterations, resulting in disturbed expression of surface molecules or an altered chemokine/cytokine milieu. B cells play an important role in the adaptive immune response and are potent antigen-presenting cells with high expression of major histocompatibility complexes (MHC) I and II. Multiple studies have reported on defective antigen presentation pathways in malignant lymphomas, however, many of the underlying genetic alterations are largely unexplored. Herein, we applied next generation sequencing techniques and fluorescence in situ hybridization to explore the landscape of genetic alterations in CIITA, the master transcriptional regulator of MHC class II, in various B cell lymphomas and to determine the spectrum of rearrangement partner genes. The functional impact of these mutations on MHC class II expression and the composition of the tumour microenvironment were subsequently evaluated in cell line model systems, and by immunohistochemistry performed on primary lymphoma specimens. Finally, we integrated our findings with patient outcomes to ascertain the clinical impact. We discovered that genomic rearrangements and coding sequence mutations in CIITA are frequent across B cell lymphoma subtypes and can result in diminished MHC class II expression, coinciding with a lower abundance of CD4- and CD8-positive T cells in the tumour microenvironment. We identified that at least some of the genetic alterations are likely a byproduct of AID-mediated somatic hypermutation, as evidenced by the co-occurrence of mutations in the non-coding region of CIITA intron 1. In addition, we described novel translocations involving a broad spectrum of rearrangement partner genes and intra-chromosomal structural variants. In summary, we established CIITA genetic alterations as a frequent immune escape strategy exploited by a variety of malignant B cell lymphomas. These mutations resulted in reduced MHC class II expression and altered microenvironment composition.  iii Lay Summary Malignant lymphomas are the fifth most frequent cancer in humans and arise from white blood cells. In certain subgroups of lymphoid cancers, the malignant cells are surrounded by immune cells, yet these cells are unable to muster an effective immune attack against the tumour. In this thesis, we focused on mechanisms how cancer cells escape the immune system by investigating a particular gene, CIITA. We found that this gene harbours multiple changes resulting in reduced levels of a molecule on the tumour cell surface, named MHC class II, which is essential for the recognition of cancer cells by the immune system. Loss of MHC class II was accompanied by reduction of immune cells, therefore enabling the tumour to escape the immune attack. Our studies provide information about the prognosis of lymphoma patients and will help develop new drugs leading to higher cure rates for patients suffering from lymphomas.  iv Preface The work presented in Chapters 2 and 3 was performed in the Department for Lymphoid Cancer Research at the British Columbia Cancer Agency’s Research Centre and were conducted under the auspices of Dr. Christian Steidl. Our work was generously funded by a Program Project Grant from the Terry Fox Research Institute (Grant No. 1023), the Canadian Cancer Society Research Institute, and the Michael Smith Foundation for Health Research. The research presented within this thesis is approved by the BC Cancer Agency – University of British Columbia Research Ethics Board (Certificate Numbers H05-60103, H13-01765, and H14-02304). This thesis includes published data as indicated in detail in the following paragraph; full references are provided at the end of this preface. The sequencing analysis of the PMBCL cohort and the in vitro functional experiments have been published in entirety. I was involved in designing the research, I analyzed and interpreted data, wrote the manuscript and performed the following experiments: PCR and Sanger sequencing, qRT-PCR, western blots, cloning and ectopic expression of wildtype and mutant CIITA, flow cytometry, as well as IHC. The contribution of all other authors is summarized herein: B.W.W. is a co-first author on this paper. He performed PCR, molecular cloning and analyzed sequencing data. F.C.C. and L.C. analyzed data and provided bioinformatics support, F.C.C. helped generating Figure 2.5 and L.C. generated Figure 3.4. E.C. performed library construction and sequencing, S.B.-N. performed FISH, and P.F. evaluated IHC. A.T. was involved in engineering the DEV cell line and performed DNA/RNA extractions, and M.B. helped with flow cytometry experiments and cell sorting. S.R., K.M.T., M.D., D.W.S., R.S. performed experiments. L.M.R. provided conceptual input and R.D.G. and C.S. designed the study and wrote the paper. The analysis of CIITA structural variants in three primary testicular lymphomas is part of a publication with David D. W. Twa, Fong Chun Chan, and me as co-first authors. Each of us contributed equally in designing and performing the research, interpreting the data and writing and editing the manuscript. S.B.-N., K.L.T. and myself performed and analyzed FISH data, while B.W.W. produced and analyzed sequencing data. A.J.M., H.D. and Y.Z. generated BAC capture and sequencing data, which was  v also analyzed by R.S.L.. B.H.N., myself and K.M. generated and analyzed IHC data. S.P.S., R.D.M., M.A.M. and D.W.S. provided experimental and editorial input. R.D.G. and C.S. designed the research, analyzed data, wrote the manuscript and C.S. also approved the paper. Part of the introduction is stemming from a review paper on the genetic basis of immune escape in malignant lymphomas, which was co-authored by me and C.S.. The work on the DLBCL cohort was initiated by Drs. Daisuke Ennishi, David W. Scott and Randy D. Gascoyne. They assembled the patient cohort and curated clinical data. D.E. designed and performed the sequencing experiments and Christoffer Hother performed mutation calling. I was responsible for reviewing cases and confirming pathological diagnoses as well as the assembly of the cases on a tissue microarray. I conducted all pathology-related aspects of this study, performed DNA/RNA extractions, analyzed CIITA mutational data and correlated this with IHC and patient outcomes. I generated all figures related to these experiments. The work on the FL cohort was spearheaded by Drs. Robert Kridel, Fong Chun Chan and Sohrab Shah. R.K. assembled the patient cohort and curated clinical data. R.K. and F.C.C. designed and performed the sequencing experiments and performed mutation calling. S.S. supervised the study. I was responsible for confirming pathological diagnoses and the assembly of the cases on a tissue microarray. I conducted all pathology-related aspects of this study, scored FISH assays, analyzed CIITA mutational data and correlated this with IHC and patient outcomes, and generated figures related to these experiments. Lauren Chong helped with the generation of Figures 2.13 and 2.15. The generation of rearrangement predictions and the graphical visualization (i.e. Figures 2.19 - 2.22) of the oligocapture results (Chapters 2.2.8.2 and 2.3.5) have been performed by Lauren Chong and are included in her master thesis. I contributed to the design of the project, assembled the patient cohort, performed DNA/RNA extractions, as well as validation experiments, and I interpreted the rearrangement predictions.     vi References:  Mottok A*, Woolcock B*, Chan FC, Tong KM, Chong L, Farinha P, Telenius A, Chavez E, Ramchandani S, Drake M, Boyle M, Ben-Neriah S, Scott DW, Rimsza LM, Siebert R, Gascoyne RD, Steidl C. Genomic Alterations in CIITA Are Frequent in Primary Mediastinal Large B Cell Lymphoma and Are Associated with Diminished MHC Class II Expression. Cell Rep. 2015 Nov 17;13(7):1418-31.  Mottok A, Steidl C. Genomic alterations underlying immune privilege in malignant lymphomas. Curr Opin Hematol. 2015 Jul;22(4):343-54.  Twa DD*, Mottok A*, Chan FC*, Ben-Neriah S, Woolcock BW, Tan KL, Mungall AJ, McDonald H, Zhao Y, Lim RS, Nelson BH, Milne K, Shah SP, Morin RD, Marra MA, Scott DW, Gascoyne RD, Steidl C. Recurrent genomic rearrangements in primary testicular lymphoma. J Pathol. 2015 Jun;236(2):136-41.  * denotes co-first authorship  vii Table of Contents  Abstract .......................................................................................................................... ii Lay Summary ................................................................................................................ iii Preface .......................................................................................................................... iv Table of Contents ........................................................................................................ vii List of Tables ................................................................................................................. x List of Figures .............................................................................................................. xi List of Abbreviations .................................................................................................. xiii Acknowledgements .................................................................................................... xvi Chapter 1: Introduction ................................................................................................. 1 1.1 B cell development and germinal centre reaction ............................................. 1 1.1.1 B cell development .................................................................................... 1 1.1.2 Germinal centre and germinal centre reaction ........................................... 3 1.2 B cell lymphomas .............................................................................................. 6 1.2.1 B cell lymphomagenesis ............................................................................ 7 1.2.2 Biological and clinical characteristics of major B cell lymphoma subtypes. 8 1.2.2.1 Diffuse large B cell lymphoma ............................................................ 8 1.2.2.2 Follicular lymphoma ............................................................................ 9 1.2.2.3 Primary mediastinal large B cell lymphoma ...................................... 11 1.2.3 Tumour-microenvironment interactions in malignant B cell lymphomas .. 12 1.3 Major histocompatibility complexes ................................................................. 14 1.3.1 Genomic alterations underlying MHC deficiency ..................................... 15 1.3.1.1 MHC class I deficiency ..................................................................... 15 1.3.1.2 MHC class II deficiency .................................................................... 16 1.3.2 Antigen presentation via MHC class II complexes ................................... 18 1.3.3 Transcriptional regulation of MHC class II ............................................... 20 1.4 Thesis theme and objectives........................................................................... 22 1.5 Hypothesis ...................................................................................................... 23 1.6 Research aims and thesis outline ................................................................... 23 Chapter 2: Genomic alterations of CIITA in malignant B cell lymphomas ............. 25 2.1 Introduction ..................................................................................................... 25 2.2 Materials and methods .................................................................................... 26 2.2.1 Cell lines and patient cohorts ................................................................... 26 2.2.1.1 Cell lines ........................................................................................... 26 2.2.1.2 Patient cohorts .................................................................................. 27 2.2.1.2.1 PMBCL cohort ............................................................................... 27 2.2.1.2.2 DLBCL cohort ................................................................................ 27 2.2.1.2.3 FL cohort ....................................................................................... 28 2.2.2 Cell sorting ............................................................................................... 28 2.2.3 Fluorescence in situ hybridization (FISH) ................................................ 28 2.2.4 Copy number analysis ............................................................................. 30 2.2.5 Sequencing of CIITA coding sequence and intron 1 ................................ 30 2.2.5.1 Sequencing of the PMBCL cohort..................................................... 30 2.2.5.2 Sequencing of the DLBCL cohort ..................................................... 31  viii 2.2.5.3 Sequencing of the FL cohort ............................................................. 32 2.2.6 Analysis of AID target motifs .................................................................... 33 2.2.7 Immunohistochemistry ............................................................................. 34 2.2.8 Characterization of chromosomal rearrangements .................................. 34 2.2.8.1 Bacterial artificial chromosome (BAC) capture ................................. 34 2.2.8.2 Capture sequencing .......................................................................... 35 2.2.9 Statistical analysis ................................................................................... 37 2.3 Results ............................................................................................................ 38 2.3.1 CIITA alterations in PMBCL ..................................................................... 38 2.3.1.1 Biallelic genomic alterations of CIITA in PMBCL- and NLPHL-derived cell lines .......................................................................................................... 38 2.3.1.2 CIITA coding sequence mutations and structural genomic alterations in primary PMBCL cases .................................................................................... 42 2.3.1.3 Intron 1 deletions and point mutations in primary PMBCL cases ...... 44 2.3.2 CIITA alterations in DLBCL ...................................................................... 48 2.3.3 CIITA alterations in FL ............................................................................. 50 2.3.3.1 CIITA coding sequence mutations and structural genomic alterations in primary FL cases ............................................................................................ 50 2.3.3.2 Intron 1 deletions and point mutations in primary FL cases .............. 53 2.3.4 BAC capture ............................................................................................ 57 2.3.5 Capture sequencing ................................................................................. 61 2.4 Discussion....................................................................................................... 71 Chapter 3: Functional and Clinical Relevance of CIITA Alterations ....................... 74 3.1 Introduction ..................................................................................................... 74 3.2 Materials and methods .................................................................................... 75 3.2.1 Flow cytometry ......................................................................................... 75 3.2.2 Quantitative reverse transcriptase (qRT)-PCR ........................................ 75 3.2.3 Western blotting ....................................................................................... 76 3.2.4 Retroviral transduction ............................................................................. 76 3.2.5 RNA-Seq .................................................................................................. 77 3.2.6 Immunohistochemistry ............................................................................. 78 3.2.7 Statistical and survival analysis ............................................................... 78 3.3 Results ............................................................................................................ 79 3.3.1 CIITA and HLA-DR expression in PMBCL- and NLPHL-derived cell lines ................................................................................................................. 79 3.3.2 Functional implications of CIITA mutants in in vitro cell line models ........ 81 3.3.3 RNA-Seq analysis .................................................................................... 84 3.3.4 Correlative studies in primary lymphoma cases ....................................... 86 3.3.4.1 PMBCL ............................................................................................. 86 3.3.4.2 DLBCL .............................................................................................. 90 3.3.4.3 FL ..................................................................................................... 94 3.3.4.3.1 tFL cohort ...................................................................................... 94 3.3.4.3.2 pFL/npFL cohort ............................................................................ 99 3.4 Discussion..................................................................................................... 101 Chapter 4: Conclusion .............................................................................................. 104 4.1 Summary of research findings ...................................................................... 104  ix 4.2 Limitations ..................................................................................................... 106 4.3 Potential applications .................................................................................... 108 4.4 Ongoing work ................................................................................................ 109 4.5 Open questions and future directions ........................................................... 110 4.5.1 Epigenetic control of MHC II expression ................................................ 110 4.5.2 Post-translational modification and degradation of CIITA and MHC class II ............................................................................................................... 111 4.5.3 Interplay between MHC and the PD-1/PDL axis .................................... 111 4.6 Final conclusion ............................................................................................ 112 Bibliography .............................................................................................................. 113 Appendices ................................................................................................................ 143 Appendix A - Supplementary methods .................................................................... 143 A.1 Assays and methodology applied to the PMBCL sequencing cohort ........ 143 A.2 TSCA oligos for the PMBCL cohort ........................................................... 145 A.3 Primer sets ................................................................................................ 148 A.4 TSCA design (CIITA) for the DLBCL cohort .............................................. 153 A.5 Cases selected for oligocapture sequencing ............................................. 155 Appendix B - Supplementary results ........................................................................ 158 B.1 CDS mutations and promoter III alterations in primary PMBCL specimens .................................................................................................................. 158 B.2 Intron 1 alterations in primary PMBCL cases ............................................ 158 B.3 Intron 1 alterations in tFL cases ................................................................ 167 B.4 Intron 1 alterations in pFL and npFL .......................................................... 181 B.5 High confidence predictions for the chromosome 16 capture space ......... 187 B.6 Putative fusion transcript A43031 .............................................................. 195 B.7 Putative fusion transcript A43036 .............................................................. 195 B.8 Putative fusion transcript A43051 .............................................................. 195 B.9 Putative fusion transcript A43076 .............................................................. 195   x List of Tables  Table 2.1: Specification of the BACs used for assessment of the CIITA locus by FISH 29 Table 2.2: Custom Agilent SureSelect design used for capture sequencing. ................ 36 Table 2.3: CDS mutations in DLBCL. ............................................................................ 49 Table 2.4: CDS mutations in FL .................................................................................... 51 Table 2.5: Structural genomic rearrangements in three PTL cases. ............................. 60 Table 2.6: SV predictions for CIITA obtained by oligocapture sequencing. ................... 63 Table 3.1: Differentially expressed genes. .................................................................... 85   xi List of Figures  Figure 1.1: Germinal centre reaction. .............................................................................. 5 Figure 1.2: Germinal centre-derived B cell malignancies. ............................................... 7 Figure 1.3: Genomic alterations of classical MHC II genes across cancer subtypes. ... 17 Figure 1.4: Frequency of CIITA genomic alterations across different cancer types. ..... 18 Figure 1.5: Antigen-presentation via the MHC class II complex. ................................... 20 Figure 2.1: Schematic of the CIITA FISH assay. ........................................................... 29 Figure 2.2: CIITA genetic alterations in the PMBCL-derived cell line MedB-1. .............. 38 Figure 2.3: CIITA genetic alterations in the PMBCL-derived cell line Karpas1106P. .... 39 Figure 2.4: CIITA genetic alterations in the PMBCL-associated cell line U2940. .......... 40 Figure 2.5: NUBP1-CIITA fusion observed in U2940 using RNA-Seq. .......................... 41 Figure 2.6: CIITA genetic alterations in the NLPHL-derived cell line DEV. .................... 42 Figure 2.7: Coding sequence mutations in primary PMBCL cases. .............................. 43 Figure 2.8: CIITA intron 1 alterations in primary PMBCL cases. ................................... 45 Figure 2.9: Subclonal evolution. .................................................................................... 46 Figure 2.10: AID hotspot targets are frequently mutated in PMBCL. ............................. 47 Figure 2.11: AID protein expression in PMBCL cases. .................................................. 47 Figure 2.12: Coding sequence mutations in primary DLBCL cases. ............................. 48 Figure 2.13: Coding sequence mutations in primary FL cases. ..................................... 50 Figure 2.14: CIITA intron 1 alterations in tFL cases. ..................................................... 54 Figure 2.15: AID hotspot targets are frequently mutated in tFL. .................................... 55 Figure 2.16: CIITA intron 1 alterations in early and late progressers. ........................... 56 Figure 2.17: AID hotspots targeted by mutations in pFL and npFL. .............................. 57 Figure 2.18: BAC capture results for three PTL cases. ................................................. 58 Figure 2.19: Oligocapture target region coverage depth. .............................................. 62 Figure 2.20: Circos plot depicting CIITA translocation events. ...................................... 69 Figure 2.21: Intrachromosomal rearrangements in the chromosome 16 capture space. ...................................................................................................................................... 70 Figure 2.22: Intrachromosomal rearrangements in CIITA intron 1. ............................... 71 Figure 3.1: CIITA mRNA expression in PMBCL- and NLPHL-derived cell lines. ........... 80 Figure 3.2: HLA-DR expression in PMBCL- and NLPHL-derived cell lines. .................. 81 Figure 3.3: Ectopic expression of CIITA wildtype and mutants in DEV. ........................ 84 Figure 3.4: Top differentially expressed genes in DEV cells expressing wt CIITA. ....... 84 Figure 3.5: MHC class II expression in primary PMBCL cases. .................................... 86 Figure 3.6: Abundance of T cell subsets in primary PMBCL cases. .............................. 88 Figure 3.7: Survival of PMBCL patients with CIITA wt or mutant tumours..................... 89 Figure 3.8: Survival of PMBCL patients according to MHC class II expression status. . 90 Figure 3.9: MHC class II expression and T cell abundance in primary DLBCL cases. .. 91 Figure 3.10: Abundance of T cell subsets in primary DLBCL cases. ............................. 92 Figure 3.11: Survival of DLBCL patients according to CIITA mutational status. ............ 93 Figure 3.12: Survival of DLBCL patients according to MHC class II surface expression. ...................................................................................................................................... 94 Figure 3.13: MHC class II expression and T cell abundance in tFL. ............................. 95 Figure 3.14: Abundance of T cell subsets in tFL according to CIITA mutation status. .. 96  xii Figure 3.15: Abundance of T cell subsets in tFL according to MHC II expression. ....... 97 Figure 3.16: TTT analysis in patients with tFL. .............................................................. 98 Figure 3.17: OS in patients with tFL. ............................................................................. 98 Figure 3.18: Abundance of T cell subsets in primary pFL/npFL cases. ....................... 100 Figure 3.19: Outcomes in patients with pFL and npFL. ............................................... 101 Figure 4.1: Functional impact of CIITA alterations in malignant lymphomas. .............. 106   xiii List of Abbreviations  AA   amino acid ABC   activated B cell-like  AID   activation-induced cytidine deaminase APC   antigen-presenting cell ba   break-apart B2M   ß2-microglobulin BAC   bacterial artificial chromosomes BCCA   British Columbia Cancer Agency BCR   B cell receptor BL   Burkitt lymphoma BLS   bare lymphocyte syndrome bp   base pair CDS   coding sequence CIITA   class II transactivator CLC   Centre for Lymphoid Cancer CN   copy number CNV   copy number variation COO   cell-of-origin CSR   class switch recombination CTL   cytotoxic T lymphocytes DLBCL  diffuse large B cell lymphoma DNA   deoxyribonucleic acid DSS   disease-specific survival EBV   Epstein-Barr virus ER   endoplasmic reticulum FBS   fetal bovine serum FC   fold change FDC   follicular dendritic cell FDR   false discovery rate  xiv FF   fresh-frozen FFPE   formalin-fixed, paraffin-embedded FISH   fluorescence in situ hybridization FL   follicular lymphoma GC   germinal centre GCB   germinal centre B cell-like GEP   gene expression profiling HL   Hodgkin lymphoma HLA   human leukocyte antigen IFN   interferon Ig   immunoglobulin IHC   immunohistochemistry IL   interleukin kb   kilobase LCL   lymphoblastoid cell line MALT   mucosa-associated lymphatic tissue Mb   megabase MCL   mantle cell lymphoma MHC   major histocompatibility complex mut   mutant MZL   marginal zone lymphoma NGS   next generation sequencing NK   natural killer NLPHL  Nodular lymphocyte-predominant Hodgkin lymphoma npFL   non-progressed follicular lymphoma OS   overall survival PCR   polymerase chain reaction PDL   programmed death ligand pFL   progressed follicular lymphoma PFS   progression-free survival PMBCL  primary mediastinal large B cell lymphoma  xv PTL   primary testicular lymphoma qRT   quantitative reverse transcriptase RNA   ribonucleic acid SHM   somatic hypermutation SNP   single nucleotide polymorphism SNV   single nucleotide variant SV   structural variant TCR   T cell receptor TMA   tissue microarray tFL   transformed follicular lymphoma TSS   transcriptional start site TTP   time to progression TTT   time to transformation UTR   untranslated region VAF   variant allelic frequency WGS   whole-genome sequencing WHO   World Health Organization wt   wildtype   xvi Acknowledgements  The work presented herein would not exist without the exceptional research environment that has been established within the Department of Lymphoid Cancer Research and the Centre for Lymphoid Cancer at the BC Cancer Agency Research Centre. I would like to convey my sincere gratitude to my supervisor Christian for his guidance, unconditional support and mentorship over the last 4 years. He has always encouraged me and helped me to grow as a scientist.  I am also grateful to the Chair and Members of my supervisory committee (Dr.’s David Huntsman, Pamela Hoodless, Andrew Weng, and Brad Nelson) for fruitful discussions, their advice and help to stay focused.  I am indebted to the Terry Fox Research Institute, the Canadian Cancer Society Research Institute and the Michael Smith Foundation for Health Research for funding the research presented herein.  I would like to thank my fellow lab members, in particular Bruce Woolcock, Adele Telenius, and Liz Chavez; your expertise and kindness made this work happen. I would like to thank Merrill Boyle, Dr. Barbara Meissner and Susana Ben-Neriah for their help and advice. Drs. Randy Gascoyne, David Scott, Robert Kridel, Pedro Farinha, and Daisuke Ennishi have been great colleagues and approachable mentors, and I am grateful for all the things I have learnt from you. Most of this work would not exist with the exceptional expertise of the bioinformatics team, led by Fong Chun Chan. Especially, I would like to thank Fong and Lauren Chong for their help.  Lastly, I would like to thank my family for their unconditional support and selflessness.   1 Chapter 1: Introduction The emergence of the adaptive immune system over 500 million years ago endowed mammals with a highly specific and sophisticated apparatus, not only to resist an immense number of pathogens, but also to develop immunological memory, thereby enabling rapid immune responses and providing the scientific rationale for vaccination [1]. The adaptive immune system relies on three major protein structures, the B cell receptor (BCR), the T cell receptor (TCR) and the major histocompatibility complexes (MHC). Lymphocytes play a crucial role in adaptive immunity, mainly due to their ability to present or recognize antigens and to produce high-affinity antibodies. Those diverse functions necessitate a considerable degree of morphological and functional plasticity, which have arisen over time. The delineation of lymphoid cells into B and T cell compartments, along with the identification of their primary reservoir, were first described about 50 years ago when experiments conducted in chickens revealed the importance of the thymus and the bursa fabricii (the functional, but not anatomical equivalent of the human bone marrow) for development and maturation of T and B lymphocytes, respectively [2,3]. The following paragraphs in this introduction provide an overview of normal B cell maturation, the germinal centre reaction and its importance for the development of B cell malignancies. Furthermore, I review clinical and biological characteristics of B cell lymphomas studied in this thesis and give a summary of current knowledge on MHC class II and its transcriptional activator CIITA.  1.1 B cell development and germinal centre reaction 1.1.1 B cell development Early B cell development from common lymphoid progenitors starts in the fetal liver, whereas later in life this process is mainly confined to the bone marrow. The first phase occurs in an antigen-independent manner, and involves the rearrangement of the immunoglobulin (Ig) loci, which is mediated by RAG1 and RAG2 recombinases [4,5]. This process is of fundamental importance for the generation of Ig diversity, a hallmark of (antibody-producing) B lymphocytes. The genomic region of the Ig loci is uniquely arranged in a way that multiple variable (V) gene segments are located upstream of  2 diversity (D) and joining (J) gene clusters, a structure termed translocon organization [1]. The variable regions, which eventually interact with antigens, are characterized by conserved segments, that build a framework interrupted by highly variable sequences, also known as “hypervariable” or complementarity-determining regions [6]. The formation of a rearranged Ig is a multi-step process, initiated at the pre-B cell stage, and starts with the rearrangement of the heavy chain locus (IGH) on chromosome 14. At first, a D segment is juxtaposed to a JH gene segment, followed by combination of a VH segment to DJH [6–9]. Subsequently, as a result of a functional rearrangement, a μ-protein is produced. This abandons any further rearrangement at the heavy chain locus and initiates a similar assembly process at the kappa (IGK) and lambda (IGL) light chain loci on chromosomes 2 and 22, respectively [6,10]. Under normal circumstances, the rearrangement of IGK antecedes any potential recombination of the lambda locus, and only if it would render a non-functional protein, IGL is rearranged [11]. The multiplicity of V, D and J segments alongside somatic variation, in addition to combinatorial and junctional diversification, creates a nearly indefinite number of possible Ig molecules, thereby overcoming the constraints of limited germline material [12]. It has been estimated, that the process of V(D)J recombination would enable the recognition of 5 x 1013 different molecules [13]. The process of Ig rearrangement needs to be tightly regulated and chronologically orchestrated to ensure that a particular B cell is limited to functional assembly and expression of a BCR with specificity for only one particular antigen, also known as allelic exclusion [9,14–17]. B cells with functional Ig rearrangements and surface expression of a pre-BCR exit the bone marrow as so-called naïve B cells, migrate into the periphery and populate secondary lymphoid organs, such as lymph nodes, spleen and mucosa-associated lymphatic tissues (MALT). Here the B cells normally encounter various antigens, the majority of them presented by T cells, they form primary follicles and eventually germinal centres (GC) to undergo further affinity maturation and functional selection [18,19].   3 1.1.2 Germinal centre and germinal centre reaction The germinal centre is an anatomical structure in lymphoid organs and was first described as such in 1884 by Walther Flemming, one of the pioneers in the field of cell biology and cytogenetics [20,21]. Intrigued by the observation of large lymphoid cells and the high frequency of mitotic figures, Flemming thought he had discovered the major source of lymphocytes in the body [22,23]. Although this was eventually disproven, Flemming’s initial observations ignited the research in this field, which has subsequently provided profound knowledge about GC physiology and underlying molecular principles. The GC can be further subdivided into a dark and a light zone based on the histological appearance and functional properties of the respective cells constituting these zones. Zonal separation becomes apparent on day seven after GC formation [24]. The dark zone develops proximal to the lymph node’s medullary zone, is comprised of large B cells, so-called centroblasts, which are highly proliferating and undergo genetic alterations, whereas the more peripherally located light zone is dominated by smaller appearing cells. Those cells are termed centrocytes and are intermingled with follicular dendritic cells (FDC) and various T cell subsets, predominantly CD4-positive follicular T helper cells [18,19]. The spatial positioning of the dark and light zones within the lymphoid organs is of immense importance since it strategically places the light zone compartment in close proximity to those anatomical structures, which normally function as access paths for foreign antigens (i.e. sinuses in lymph nodes and spleen or the mucosal surface in tonsils and intestine) [23]. The compartmentalization of the GC into dark and light zones is largely dependent on chemokine and chemokine receptor gradients. CXCR4, a chemokine receptor highly expressed on centroblasts, is thought to be critical for localization of these cells in the dark zone, a concept further substantiated by the higher abundance of the corresponding ligand SDF1 (CXCL12) [24,25]. Centrocytes on the other hand show higher expression of CXCR5 and migrate towards CXCL13. The CXCR5-CXCL13 axis is required for the correct positioning and polarization of the GC and the migration of B cells to the light zone, whereas the formation and segregation of dark and light zones is thought to occur independent of this receptor-ligand interaction [24,26]. Recent  4 technical advances, real-time imaging experiments and functional studies helped to shed light on the highly dynamic nature of the GC and the biological processes occurring within this anatomic structure (Figure 1.1) [26–29]. A complex network of transcriptional regulators, signaling molecules and cell-cell interactions, subsumed under the term germinal centre reaction, determines the fate of germinal centre B cells; they can undergo cyclic re-entry into the dark zone and experience multiple rounds of receptor editing to eventually pass the selection process in the light zone, which involves FDCs and follicular T helper cells. These positively selected B cells exit the GC as terminally differentiated plasma cells or memory B cells, whereas B cells with reduced affinity of their BCR to a given antigen are predisposed to undergo apoptosis [18,19,30–32]. The germinal centre reaction encompasses two main processes that are required for efficient affinity maturation: class switch recombination (CSR) and somatic hypermutation (SHM), both of which are essential for the maturation of B cells and adaptation to environmental antigens [18,19]. During the process of SHM, point mutations and small indels (insertions/deletions) are introduced into the Ig variable regions, which ultimately form the interface with the antigen and determine the specificity of the antibody. It was estimated that single nucleotide changes occur at a rate of one per 1000 bp per generation [33]. CSR on the other hand is essential for modulating the effector function of an antibody, conferred by the constant region of IGH, as well as for the generation of memory responses. The key enzyme to catalyze this “programmed” DNA damage is activation-induced cytidine deaminase (AID; encoded by AICDA), a nuclear-cytoplasmic shuttling enzyme which converts deoxycytidine into deoxyuridine [34–36]. AID recognizes and targets cytidine in a specific genomic context and although there have been some controversies about the exact nature of the motif, the majority of the literature acknowledges WRCY/RGWY (W=adenosine or thymidine; R= adenosine or guanosine; C= cytidine and Y= cytidine or thymidine) motifs as AID hotspots [13,37,38]. The process of DNA deamination entails the activation of mismatch repair and base excision repair mechanisms, which result in DNA double-strand breaks and thereby the initiation of CSR and SHM [13].  5  Figure 1.1: Germinal centre reaction. The GC is comprised of a dark zone and a light zone, surrounded by a mantle zone. (a) B cells compete for T cell help at the border of T and B zones and only cells with high affinity are entering the GC. (b) Proliferation and SHM occur primarily in the dark zone, whereas selection and CSR take place in the light zone compartment via interaction with FDCs and follicular T helper cells. (c) Migration of B cells between these two zones is mediated by differential expression of chemokine receptors and their respective ligands. (d) B cells can undergo multiple rounds of receptor editing and affinity selection and leave the GC as plasma cells or memory B cells. Abbreviations: AID, activation-induced cytidine deaminase; BCR, B cell receptor; FDC, follicular dendritic cell; GC, germinal centre; pMHC, peptide-MHC. This figure is reproduced from [19] with permission.  Although the germinal centre reaction is fundamental for the functionality of the adaptive immune response and immunological memory, it also comes with a substantial and potentially dangerous downside as it poses an inherent risk for malignant transformation of germinal centre B cells [18,39,40]. The development of high-throughput sequencing technologies was instrumental in investigating the landscape of  6 AID off-targets and it has soon been recognized that AID does not only target the Ig heavy and light chain loci, but also several other genes depending on their transcriptional activity and expression at various stages of germinal centre B cell maturation [41–45]. These collateral damage sites rely subsequently on an intact and sufficient DNA damage repair machinery [46], and failure of these mechanisms are believed to contribute to B cell lymphoma pathogenesis [13,18,40,47]. Recent studies have emphasized the importance of structural features, epigenetic accessibility, transcriptional regulation and the presence of super-enhancers for accurate prediction of AID off-targets in a specific cellular context [13].  1.2 B cell lymphomas The current and recently revised version of the WHO classification of tumours of haematopoietic and lymphoid tissues [48,49] recognizes more than 40 distinct lymphoma entities on the basis of morphology, phenotype, genetic aberrations and clinical features. About 10 % of lymphoma cases belong to the Hodgkin lymphoma (HL) group, whereas the vast majority can be classified as non-Hodgkin lymphomas (NHL). Among all newly diagnosed malignancies, NHL as a group represent the 5th most common cancer type in the U.S. with an incidence of 19.5 cases per 100,000 individuals/year according to the recent Surveillance, Epidemiology and End Results (SEER) report [50]. NHLs can be further subdivided according to their respective lineage in B or T cell lymphomas, with B-NHLs accounting for more than 90 %. Current pathogenic concepts highlight the acquisition of oncogenic mutations and other potentially transforming events in a definite cell-of-origin (COO) context to give rise to the various malignant phenotypes observed in B cell lymphomas [51,52]. For the majority of described genomic alterations, the germinal centre reaction constitutes the foundation for their occurrence and selection during the process of lymphomagenesis [18,19]. The recognition of distinct entities and molecular subtypes has significantly fostered our understanding of lymphoma biology and is indispensable for clinical decision-making and the development of targeted therapies [53].   7 1.2.1 B cell lymphomagenesis B cells at various stages of maturation are characterized by context-dependent gene expression profiles (GEP) and epigenetic programming. Accordingly, initiation and progression of lymphomas are closely related to the microenvironment in which they develop. In light of our knowledge about normal B cell development and the physiological genomic instability of B cells during the germinal centre reaction, it follows that B cell lymphomas can originate from normal counterparts at various developmental stages [51], with the majority stemming from germinal centre B cells (Figure 1.2). Recent gene expression profiling studies suggest that, with the exception of molecular Burkitt lymphomas (BL), most GC-related B cell malignancies originate from cells with a light zone phenotype [39].   Figure 1.2: Germinal centre-derived B cell malignancies. The biological processes of B cell development and antibody affinity maturation within the GC create an environment for the development of various B cell lymphomas, resembling different developmental stages. Based on GEP, Burkitt lymphoma is closely resembling dark zone B cells, whereas the other major B cell lymphoma subtypes are more related to light zone B cells. Abbreviations: GC, germinal centre; DLBCL, diffuse large B cell lymphoma. Reproduced from [47] with permission.  Similar to solid malignancies, B-NHLs can harbour numerous genetic alterations, such as copy number variations (CNV) or point mutations, which can confer gain- or  8 loss-of-function phenotypes. As mentioned in section 1.1.1, the processes of V(D)J recombination, SHM and CSR pose a significant risk for malignant transformation of B cells through acquisition of chromosomal translocations and deleterious or oncogenic mutations. Chromosomal rearrangements are disease-defining biological and diagnostic features in various B cell lymphoma subtypes, e.g. BCL2 translocations in follicular lymphoma (FL), CCND1 translocations in mantle cell lymphomas (MCL), MALT1 translocations in marginal zone lymphomas (MZL), or MYC rearrangements in BL [48]. In contrast to other haematological cancers, such as acute leukemias, chromosomal translocations in B-NHLs do not usually lead to the generation of gene fusions and chimeric proteins but rather to a ‘promoter swap’ [54]. In most cases, the result is the juxtaposition of an oncogene with the promoter or enhancer regions of the Ig loci, leading to dysregulated or exuberant expression of the oncogene. Translocations in B cells can theoretically occur at any time during development, but are more likely to arise as an inadvertent byproduct of the RAG-mediated recombination process (e.g. IGH-BCL2 translocation t(14;18) in FL) or the AID-dependent mechanisms of CSR and SHM (e.g. MYC translocations in BL) [47]. Despite the fact that chromosomal rearrangements in B-NHLs have long been recognized and utilized in diagnostic algorithms in clinical practice, little is known about the exact breakpoint anatomy, and a systematic survey of recurrent chromosomal rearrangements is lacking for the majority of lymphoma entities.  1.2.2 Biological and clinical characteristics of major B cell lymphoma subtypes 1.2.2.1 Diffuse large B cell lymphoma Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype worldwide and accounts for about 31 % of B-NHLs [55]. It can arise de novo or as the result of transformation from a low-grade lymphoma (e.g. chronic lymphocytic leukemia (CLL), MZL or FL). Patients diagnosed with this disease are usually between 60 and 70 years old, however, children and young adolescents can also be affected [55,56]. Histologically, DLBCL is characterized by a diffuse infiltration of lymph nodes or extranodal sites by predominantly large, highly proliferative neoplastic B cells  9 resembling centroblasts or immunoblasts [48]. Typical extranodal sites include the gastrointestinal tract, the central nervous system, testes, skin and bone [57]. A multitude of studies over the past two decades have demonstrated that the pathogenic mechanisms leading to the development of DLBCL are complex and heterogeneous. The implementation of genome-wide expression profiling and next generation sequencing (NGS) techniques led to: 1) the identification of two distinct molecular subtypes corresponding to different stages of B cell differentiation [58]; and 2) the delineation of the mutational landscape [59–61]. Based on differences in gene expression signatures, the germinal centre B cell-like type (GCB) and a subtype resembling activated B cells (ABC) can be distinguished. Those two subtypes not only differ in their GEP, but are also characterized by hallmark genetic lesions and a remarkably disparate clinical behaviour [62–65]. With the recent developments and emergence of new drugs targeting subtype-specific pathways and mutations [53], the distinction of GCB- and ABC-type DLBCL, commonly referred to as COO-assignment, has become a mandatory task for the diagnosing pathologist with the revision of the WHO classification [49]. The genes most frequently involved in chromosomal translocations in DLBCL are BCL6 (30 %), followed by BCL2 (20 %), MYC (10 %) and TBL1XR1/TP63 (5 %) [66–69]. In the past decade, a number of high-throughput sequencing studies have shed light on the molecular and genetic alterations contributing to DLBCL pathogenesis. The most commonly mutated genes are involved in epigenetic regulation and chromatin modification and include EZH2 [70], CREBBP, EP300 and KMT2D [59,61,71]. Of crucial importance for DLBCL pathogenesis is the dysregulation of BCL6, either directly through chromosomal translocation and somatic mutations or indirectly via alterations leading to changes in transcriptional activity, such as MEF2B mutations [66,72–74].  1.2.2.2 Follicular lymphoma Follicular lymphoma is the second most common lymphoma subtype, accounting for about 22 % of cases [55], with the highest incidence in North America and Western Europe [48]. FL is considered an indolent, yet mostly incurable cancer, characterized by a slowly progressing disease course in the majority of patients. Similar to DLBCL, FL is  10 seen mainly in older patients but can occur in children, although pediatric FL differs in terms of histological appearance, pathogenesis, mutational profiles and course of the disease [48,75,76]. As the name implies, FL is a tumour typically growing in follicular structures, which are to some extent reminiscent of normal GCs. The follicles in FL are usually densely-packed and therefore alter the normal lymph node architecture. Furthermore, a mantle zone is frequently absent and the zonal structure, with clearly visible dark and light zones, is disturbed. It has also been demonstrated, by using laser capture microdissection and single cell PCR, that lymphoma cells frequently migrate between neoplastic follicles [77], suggesting that these nodules are rather dynamic structures. The presence of non-neoplastic cells, such as follicular T helper cells, FDCs, macrophages and stromal cells, indicates the dependence of the malignant cell population on external stimuli and survival signals and has been shown to provide prognostic information [78,79]. Indeed, FL is the prototypic example of a cancer achieving ‘re-education’ of the surrounding immune cells to provide a pro-tumoural niche [80] and therefore enabling the lymphoma cells to thrive in this environment. The translocation t(14;18)(q32;q21), resulting in the juxtaposition of the BCL2 gene under the control of the IGH promoter, is the genetic hallmark of FL and is present in 75-90 % of cases, depending on the detection method employed [81]. Multiple studies have elucidated the mechanisms by which these chromosomal breaks occur and it is established that the BCL2 translocation in FL is the result of a concerted action involving RAG and AID during early B cell development in the bone marrow [82–84]. The t(14;18) itself is not sufficient for lymphomagenesis, as evidenced by the presence of t(14;18)-positive B cells in otherwise healthy individuals [85,86]. However, the t(14;18) translocation, leading to overexpression of the anti-apoptotic protein BCL2, is pivotal for disease progression and maintenance once an FL has arisen [87–89]. Because the onset of FL cannot be explained by the sole presence of the translocation t(14;18), additional genetic alterations need to occur to drive lymphoma development and progression. NGS techniques have revolutionized the field of cancer genomics and have enhanced our knowledge and understanding of disease biology. Numerous studies have revealed that histone modifiers are among the most frequently mutated genes in FL [59,90,91].  11 Patients diagnosed with FL are commonly risk-stratified based on clinical observations and measurable parameters, combined together in a prognostic tool called the FL International Prognostic Index (FLIPI) [92]. Recent efforts to refine risk stratification by incorporating mutational signatures of seven genes have led to the development of a new prognosticator, the m7-FLIPI [93]. As mentioned above, FL is an indolent, but incurable disease, meaning that patients affected by this disease will eventually experience relapse, progression or transformation into a high-grade lymphoma. Studies investigating the patterns of progression and transformation by applying conventional cytogenetics or (next-generation) sequencing approaches, often demonstrated divergent clonal evolution to be the most common mechanism [94–98].  1.2.2.3 Primary mediastinal large B cell lymphoma Primary mediastinal large B cell lymphoma (PMBCL) represents a relatively rare aggressive B cell neoplasm and accounts for only 2-4 % of B-NHLs. Young women in their third to fourth decade of life are frequently affected and, because those patients usually present with bulky tumour masses in the mediastinum, the putative cell of origin is thought to be a thymic medullary B cell [48]. The prototypic PMBCL presents histologically as a tumour of medium to large lymphoid blasts with abundant cytoplasm, some of which can resemble Hodgkin-like cells. Often, the tumour is compartmentalized by delicate collagenous fibrosis and can show extensive areas of necrosis [48]. Global GEP revealed a molecular signature that clearly distinguished PMBCL from other large B cell lymphomas, such as DLBCL, and established a linkage to the nodular sclerosis subtype of classical HL (cHL) [99,100]. Subsequent studies showed that these two entities not only show similarities on the transcriptomic level but also overlapping genomic alterations [101–104]. Moreover, PMBCL and cHL rely on constitutively active signaling pathways, such as the Janus kinase-signal transducer and activator of transcription (JAK-STAT) and nuclear factor-B (NF-B) pathway, for proliferation and survival [101,105]. The close relatedness is further substantiated by the introduction of a so-called grey zone category in the 2008 WHO classification to integrate cases which show intermediate features between cHL and PMBCL [48].  12 From a clinical point of view, patients with PMBCL tend to have better outcomes when treated with multiagent chemotherapy regimens compared to DLBCL [106,107]. More recent therapeutic approaches aim at eliminating the need for mediastinal radiation therapy, which comes with the risk of serious late site effects. A recently conducted phase 2 study using dose-adjusted etoposide, doxorubicin, cyclophosphamide, vincristine, prednisone, and rituximab (DA-EPOCH-R) has demonstrated promising results with event-free survival rates of 93 % [108].  1.2.3 Tumour-microenvironment interactions in malignant B cell lymphomas1 Over the past decade we have seen a major shift of focus in cancer research. Newly developed pathogenesis models have deviated from being solely centered on the description of accumulating genetic changes and pathway alterations in malignant cells [109] towards comprehensive consideration of the interactions between tumour cells and non-malignant cells in the tumour microenvironment. The notion of immune cells being significant contributors to cancerogenesis and the importance of cellular crosstalk with malignant cells have led to the recognition of these aspects of tumour biology as an emerging hallmark of cancer (“immune evasion”) and enabling characteristic (“tumour promoting inflammation”) [110]. Microenvironment-related biology in lymphoid cancers has been explored in a limited number of subtypes with variable contributions of reactive immune cells in the microenvironment. Amongst these, cHL represents the extreme example in a spectrum of diseases that feature a quantitatively dominant microenvironment composed of a variety of non-malignant cell types from both the innate and adaptive immune system. In cHL, these “bystander” cells are believed to be attracted by the Hodgkin- and Reed-Sternberg (HRS) cells as the master recruiters [80,111]. The composition of the tumour microenvironment, and in particular its spatial distribution, can be perceived as a complex interplay of: 1) genetic alterations within the malignant cell population; 2) the extent and dependence on the cellular and molecular crosstalk involving cyto- and chemokines as well as receptor-ligand interactions; and 3) host-specific factors (inflammatory response, systemic immune competence). This                                                  1 This paragraph has been modified from [111].  13 results in three highly characteristic blueprints for the microenvironment architecture of malignant lymphomas, termed “re-education”, “recruitment” and “effacement” [80]. FL is the prime example for the ‘re-education’ pattern since the tumour cells are at least to some extent dependent on their microenvironment for proliferation and survival. As described in section 1.2.2.2, the cellular composition of the neoplastic follicles closely resembles reactive GC, with high abundance of FDCs and follicular T helper cells. ‘Recruitment’ of various non-malignant immune cells is a hallmark of cHL. This results in a quantitative dominance of reactive cells over the tumour cells. The other end of the spectrum, ‘effacement’, is best represented by BL, a lymphoma with typically more than 90 % malignant cells. The microenvironment is sparse, in part caused by the ‘independence’ of the lymphoma cells on survival signals provided by the microenvironment [80]. The primary purpose of the immune system is to protect against infectious agents, but it also sufficiently recognizes and eliminates autologous cells displaying non-self antigens or so-called neo-antigens, which – in the case of malignant tumours - are often the result of cancer-specific genetic alterations [112–114]. T cell dependent immune responses involve complex interactions between antigen presenting cells (APCs) and T cells, which engage several stimulatory and inhibitory signaling molecules. In order to avoid non-directional and anomalous reactions that might lead to autoimmunity and excessive tissue damage, the entire process has to be strictly regulated. The sophisticated apparatus of the adaptive immune response has been exploited by cancer cells and there is ample evidence that interference with anti-tumour immunity is not a passively or randomly occurring process [115–117]. Malignant cells have developed strategies to escape from immune surveillance. These include mutations or deletions of genes involved in antigen presentation or, alternatively, structural rearrangements and copy number alterations (gain/amplification), resulting in overexpression of molecules involved in the induction of peripheral tolerance and T cell exhaustion (so-called immune checkpoint molecules). This ultimately leads to re-programmed and dysfunctional immune cells and, while some of these effects seem to be persistent, a proportion might be reversible and therapeutically targetable [118,119].  14 Importantly, effective reversal of this altered immune biology in the clinical setting will be accelerated by the identification of genomic and molecular alterations underlying immune privilege and the integration of these findings with clinical and morphological parameters to administer tailored therapy to lymphoma patients.  1.3 Major histocompatibility complexes The major histocompatibility complexes are glycoproteins on the cell surface and are integral to the normal function of the adaptive immune system. Furthermore, the biology of antigen presentation has major implications for pathologic processes, such as autoimmunity and transplant rejection, but also for tumour immunotherapy [120]. The MHC cluster encompasses a large genomic region harbouring over 100 genes close to 4 Mb in size [121] and can be subdivided into two major groups: MHC class I (with human leukocyte antigen (HLA)-A, -B and -C representing the classical MHC class I genes) and MHC class II (with HLA-DR, -DP, -DQ representing the classical MHC class II genes). They have in common the presentation of antigens to effector T cells, however there are also fundamental differences to be recognized. These include tissue-specific patterns of MHC expression, the nature and source of the peptide fragments presented, and the interacting T cell population. MHC class I molecules are expressed on all nucleated cells and present endogenous proteins to cytotoxic, CD8-positive T cells, therefore providing a blueprint of the intracellular proteome and playing an important role for the recognition of ‘self’ and ‘foreign’ [120]. MHC class II molecules are mainly restricted to APCs, they display predominantly exogenous antigens and are required for an immunological response executed by CD4+ T cells [122]. However, under certain circumstances cells deviate from that convention, a phenomenon known as cross-presentation [123]. This process has been described in APCs and leads to the presentation of extracellular antigens (from virus-infected cells or tumour cells) via MHC class I to naïve CD8+ T cells [120,124]. Autophagy, on the other hand, can result in the presentation of cytosolic/endogenous peptides via MHC class II [125–127].   15 1.3.1 Genomic alterations underlying MHC deficiency Immune evasion, metastasis and impaired patient outcomes have been, in part, attributed to downregulation of MHC class I and II in a variety of solid and hematological malignancies [128–134] and abnormalities of MHC class I expression represent one of the most frequent changes across different cancer types, allowing tumour cells to avoid destruction by cytotoxic CD8+ T lymphocytes (CTLs) [128,135].  1.3.1.1 MHC class I deficiency2 Several mechanisms have been described by which malignant B cells are able to downregulate MHC molecules. Homozygous and heterozygous deletions of the MHC locus on chromosome 6p occur frequently in DLBCL, with a predilection for those arising in ‘immune-privileged’ sites of the testes or brain [136–139]. Furthermore, the MHC locus is a very common susceptibility locus for the development of a variety of lymphomas, as identified by genome-wide association studies [140–143]. The MHC class I complex is composed of the heavy chain (a transmembrane glycopolypeptide) and the non-covalently bound ß2-microglobulin (B2M) light chain [144,145]. The association with B2M is important for the assembly and stabilization of the entire complex, as well as for maintaining a functionally active conformation in order to present peptides derived from intracellularly degraded proteins [146–148]. Alterations of the B2M gene have been described across a variety of solid tumours and malignant lymphomas [149–153]. The mutational pattern with frequent occurrence of loss of the start codon, truncating mutations, deletions and CNVs, as well as biallelic alterations established B2M as an important tumour suppressor gene in DLBCL [59,61,154] with a reported frequency of up to 29 %. In contrast, mutations in FL, BL, CLL, MCL and MZL were not or rarely detected [90,154,155]. Recent studies investigating the genetic mechanisms underlying transformation of FL have further demonstrated that B2M mutations are enriched in transformed lymphomas with mutation patterns similar to those observed in de novo DLBCL, providing evidence for the existence of immune selection pressure during evolution to a high-grade malignancy, and for a linkage between mutations and microenvironment composition [94,96].                                                  2 This paragraph has been modified from [111].  16 Interestingly, mutations of CD58, a member of the immunoglobulin superfamily and ligand for the CD2 receptor on natural killer (NK) cells [156,157], have been found to co-occur frequently with B2M aberrations in de novo DLBCL, as well as in transformed FL (tFL), suggesting that B2M and CD58 mutations represent complementary mechanisms to establish immune privilege [94,154]. Specifically, the co-occurrence was attributed to the potentially synergistic effects of reduced recognition by CTLs and inactivating NK cells, since it has been described in earlier studies that escape from CTLs triggers NK cell recognition as part of a compensation mechanism [154,158]. Similar alterations of B2M and CD58 have also been recently identified in HL-derived cell lines and HRS cells from primary tissue biopsies [159–162]. As B2M is indispensable for the assembly of the MHC class I complex, genomic alterations in B2M led to concomitant absence of surface HLA-A/B/C staining in mutated DLBCL and HL cases [154,159], a discovery that might also in part explain the reduction of MHC class I expression reported in earlier studies [163,164].  Recently, NLRC5 (CITA), a new member of the nucleotide-binding domain, leucine-rich repeat protein family, was identified to be involved in the transcriptional control of MHC class I [165,166] along with a potential role in regulating MHC class II transcription [167]. So far, NLRC5 alterations have been rarely described in malignant lymphomas [59,60,168,169], and functional studies are warranted to provide evidence for a potential link to immune escape in this specific context.  1.3.1.2 MHC class II deficiency Compared to MHC class I, there has not been nearly as much focus on MHC class II alterations in cancer, probably because of the rather restricted expression in APCs. When interrogating publically available sequencing data across different cancer types, alterations in the classical human MHC class II molecules, encoded by HLA-DR, HLA-DP and HLA-DQ, are frequently found in glioblastoma multiforme, followed by DLBCL (Figure 1.3).   17  Figure 1.3: Genomic alterations of classical MHC II genes across cancer subtypes. The results shown here are based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov and are visualized using the cBIOPortal for Cancer Genomics http://cbioportal.org/ [170,171].  In their capacity as potent antigen-presenters, B cells normally express MHC class II molecules on their surface to mediate interaction with CD4+ T helper cells. Our group has previously described recurrent structural genomic alterations (specifically, unbalanced chromosomal rearrangements) of CIITA, the master regulator of MHC class II transcription, in PMBCL and cHL [172]. These aberrations were proposed to be causative of MHC class II loss, however, a detailed analysis of MHC class II protein expression has not been performed. CIITA mutations have also been found in DLBCL [59,61,173] and, furthermore, it appears that concomitantly with B2M mutations, and therefore impairment of MHC class I, CIITA is frequently mutated in tFL [94]. In contrast, mutations in solid cancers are rarely found (Figure 1.4). Interestingly, the structural genomic aberrations appear to be a unique feature of PMBCL and cHL, since they were rarely observed in other lymphoma subtypes analyzed [172]. A comprehensive  18 assessment of CIITA mutations, as well as correlations with MHC class II expression and microenvironment composition are largely missing.   Figure 1.4: Frequency of CIITA genomic alterations across different cancer types. The results shown here are based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov and are visualized using the cBIOPortal for Cancer Genomics http://cbioportal.org/ [170,171].  1.3.2 Antigen presentation via MHC class II complexes Beside the importance of MHC class II-mediated antigen presentation for the protection against pathogens and tumours, it is also essential for selection processes during early T cell development in the thymus and maintenance of self-tolerance [174]. These important immunological functions necessitate tight regulation of MHC class II expression with regards to cell type specificity, activation and developmental stages, to assure an adequate response to pathogens while avoiding any reactivity against the host. MHC class II molecules are typically expressed by thymic epithelial cells and professional APCs, including not only dendritic cells and monocytes/macrophages, but also B cells [122,174,175]. Some studies have highlighted the dependence of MHC class II expression and the CD4+ T cell response on the APC, which is involved in the MHC class II-mediated antigen presentation. Macrophages for example are relying on  19 activating stimuli to induce MHC class II expression, whereas B cells are characterized by a rather constitutive expression, which can be enhanced by stimulatory signals, such as interleukin (IL) 4 [176,177]. However, the expression of MHC class II within the B cell lineage is strictly regulated. It is absent in early pro-B cells, increases in subsequent developmental stages to reach a maximum in GC B cells, and vanishes in plasma cells [178,179]. The classical human MHC class II molecules are encoded by three genes: HLA-DR, HLA-DP and HLA-DQ, located on the short arm of chromosome 6. These genes are highly polymorphic and differ in their capability to bind peptides [122]. The MHC class II complex formation starts with the assembly of a heterodimer, consisting of - and -chains, which subsequently liaises with the invariant chain (Ii; encoded by CD74) in the endoplasmic reticulum (ER). This step is important for stabilization of the entire complex, which gets then transported to the MHC class II compartment (MIIC) [180]. MIIC represents a late endosome and the cellular compartment where peptide loading of MHC class II is taking place. Proteolytic cleavage of the invariant chain results in a small residual peptide (CLIP, class II-associated Ii peptide), that occupies the peptide-binding groove of MHC class II until it is eventually exchanged for a peptide typically derived from the endosomal/endocytic pathway [181]. This step is dependent on the presence of HLA-DM, which functions as an MHC class II chaperone (Figure 1.5) [120,122].   20  Figure 1.5: Antigen-presentation via the MHC class II complex. (a) The - and -chains of the MHC class II complex are assembled in the endoplasmic reticulum (ER) and are transported to the endosome, where, following the removal of CLIP, peptide loading occurs (b). Transcriptional regulation of MHC II is mediated by a multi-protein complex, orchestrated by CIITA, the master transcriptional activator (c). Abbreviations: APC, antigen presenting cell; CLIP, class II-associated Ii peptide; CREB, cAMP-responsive-element-binding protein; CIITA, class II transactivator; ER, endoplasmic reticulum; ESCRT, endosomal sorting complex required for transport; MHC, major histocompatibility complex; MIIC, MHC class II compartment; NFY, nuclear transcription factor Y, RFX, regulatory factor X; TCR, T cell receptor. Adapted from [122] with permission.  1.3.3 Transcriptional regulation of MHC class II Our understanding of the detailed molecular mechanisms involved in antigen presentation via MHC class II and the transcriptional regulation of the complex itself have been strengthened by studies elucidating the genetic foundation of immunodeficiency [182,183]. The transcription of the MHC class II locus is tightly controlled by a multi-protein complex, involving regulatory factor X (RFX), cyclic AMP-responsive-element-binding protein (CREB), nuclear transcription factor Y (NF-Y) and CIITA, the latter considered to  21 be the master transcriptional regulator of MHC class II expression [184–186]. Of importance for controlling expression of MHC class II genes is a specific regulatory sequence, located approximately 150-300 bp upstream of the transcription start site (TSS), called SXY module [175,180,183]. This module encompasses four different boxes: W/S (essential for recruitment of CIITA to the promoter region) [187], as well as X1, X2 and Y, which are the binding sites for the heterotrimer RFX, CREB and NF-Y, respectively. Upon binding of these three proteins or protein complexes to the SXY module, the entire structure is termed MHC class II enhanceosome, to which CIITA is ultimately recruited [188]. Similar WXY motifs have been found in the promoter regions of the invariant chain (CD74) and MHC class I, suggesting an important role in regulating antigen presentation pathways. Since CIITA itself is not capable of DNA-binding, the interaction with the aforementioned proteins is indispensable. CIITA and its pathogenic relevance were first discovered and described in a rare but severe immune disorder, named hereditary, autosomal recessive MHC class II deficiency or type II bare lymphocyte syndrome (BLS) [183]. Subsequent studies have further delineated the underlying molecular defects in specific trans-acting factors, based on which patients with BLS can be subdivided in the following four complementation groups: BLS group A patients harbour loss of function mutations within CIITA [189], whereas patients in groups B, C and D are characterized by genetic defects of the genes defining the RFX complex, which consists of RFXANK, RFX5 and RFXAP [190–193]. Characteristic for the RFX-deficient BLS groups is that the promoters of MHC class II complex genes are unoccupied, highlighting the importance of RFX for the assembly of the MHC class II enhanceosome [180,194]. Mutations in the aforementioned genes often result in a lack of MHC class II protein, and because MHC class II expression is mainly restricted to APCs and is essential for the display of foreign antigens to CD4+ T cells, BLS patients often suffer from multiple infections as a result of an insufficient adaptive immune response. Cell-type specific expression of CIITA is ensured by usage of different promoter structures [175,180,195]. Four promoters have been described in the literature [196] and transcripts deriving from these promoters differ in their first exon. Promoter I (pI) is used by dendritic cells, promoter III (pIII) is restricted to B cells, whereas CIITA  22 expression from the promoter IV (pIV) can be induced upon interferon (IFN)  stimulation in a wide variety of different cell types without antigen presenting function, such as fibroblasts, endothelial cells and epithelium [197–200]. Significant amounts of promoter II (pII)-derived transcripts could not be detected in human tissues or cell lines, hence the biological relevance of this promoter is considered to be rather limited [196]. The CIITA protein consists of three important domains: an amino-terminal acidic domain, including a proline, serine, threonine (PST)-rich segment, a centrally located conserved NACHT-domain, also known as GTP-binding domain, and leucine-rich repeats (LRR) at the carboxyl-terminus [174,175,180]. The NACHT-domain is named after the genes in which it has been found: Naip, CIITA, HET-E, and TP-1 [201]. The N-terminal region is thought to mediate interactions of CIITA with effector proteins, such as transcription factors, chromatin remodeling factors and co-activators [202,203], whereas the GTP-binding domain is important for conformation of the CIITA protein, self-association and localization to the nucleus [204,205]. Similarly, disruption of the LRR region abrogates CIITA activity and results in cytoplasmic accumulation of the protein [206–209].  1.4 Thesis theme and objectives Malignant lymphomas account for approximately 5 % of all newly diagnosed cancer cases per year and affect patients of all ages [48]. Despite improvements in clinical management of lymphoma patients, a significant proportion still experience relapse or progression and eventually succumb to their disease. Over the past decade, numerous studies have carved out the importance of the microenvironment for cancer development as well as perpetuation [210,211]. Moreover, there is increasing evidence that tumour cells are orchestrating reactive cells in a targeted manner to escape immune surveillance [111,211]. Several mechanisms by which lymphoma cells can evade host immune response have been described. Expression of surface molecules on malignant cells including overexpression of Galectin-1 and ligands of programmed death receptor 1 (PDL) [212–214] are reported to establish peripheral tolerance in several lymphoma subtypes. Moreover, tumour cells in PMBCL and cHL sometimes lack MHC class II expression, a finding that has been  23 linked to reduced immunogenicity of tumour cells [133,134,215]. Based on these data, one can reasonably argue that immune escape represents an important pathogenic mechanism in lymphoid cancers. Importantly, although the phenotypic changes related to immune escape are increasingly recognized, most of the underlying genetic mechanisms still need to be uncovered. In view of our discovery of recurrent structural changes involving the CIITA gene locus in a large proportion of PMBCL and cHL cases [172], we hypothesize that genomic alterations of CIITA are prevalent in certain lymphoma subtypes and underlie an important mechanism of acquired immune privilege in a subgroup of lymphoid cancers. CIITA functions as the master transcriptional regulator of MHC class II molecules, which are commonly expressed on APCs and are crucial for the interaction with other cellular components of the immune system. In the setting of malignant lymphomas, somatic genetic alterations of CIITA could lead to a reduction of MHC class II expression, therefore creating an `immune privilege` phenotype in the malignant population and contributing to disease progression and impaired survival of lymphoma patients. The main objective of this research is to obtain a better understanding of the heterogeneity, molecular mechanisms, as well as the functional consequences, and ultimately the clinical implications, of CIITA gene alterations. These insights will be critical to the translation of our discoveries into clinically meaningful progress for affected patients and pave the way for targeted therapies.  1.5 Hypothesis Genetic alterations of CIITA are frequent across a spectrum of B cell lymphomas, result in reduction of MHC class II expression and altered microenvironment composition, thereby conferring an ‘immune privilege’ phenotype and contributing to disease progression and impaired survival of lymphoma patients.  1.6 Research aims and thesis outline I seek to comprehensively explore mutational patterns of CIITA in major B cell lymphoma subtypes (i.e. DLBCL, FL and PMBCL) and to uncover the repertoire of structural rearrangement partner genes. Secondly, I will correlate mutational findings  24 with pathologic and clinical characteristics and perform in vitro functional studies to elucidate consequences of genetic alterations in CIITA. The thesis consists of an introductory part, two chapters describing original research and a discussion with concluding remarks and an outline of ongoing and future research.  The structure of this thesis follows three specific aims:  Aim 1: To characterize genomic alterations in CIITA across major subtypes of B cell lymphomas.  Aim 2: To determine the spectrum of novel rearrangements and gene fusion partners of CIITA and describe breakpoint anatomy at base pair resolution.  Aim 3: To explore gene expression changes in monoculture and evaluate the functional and clinical impact of CIITA alterations in primary lymphoma cases.    25 Chapter 2: Genomic alterations of CIITA in malignant B cell lymphomas  2.1 Introduction Over the past decade, a lot of emphasis has been put on the refinement of cancer pathogenesis models to acknowledge the contribution of the immune system to disease development and progression. The revised version of the ‘hallmarks of cancer’ [109] prominently recognizes the importance of the cellular crosstalk of immune cells with the malignant cell population as a significant contributor to cancerogenesis (“tumour promoting inflammation”) but, at the same time, introduces the concept of “immune evasion” as one of the emerging hallmarks of cancer [110]. The evolution of NGS techniques had, and still continues to have, a profound impact on the field of cancer genomics, allowing for genome- and transcriptome-wide characterization of structural genomic alterations. By applying these novel techniques, we previously identified and described rearrangements involving CIITA, CD274 and PDCD1LG2 as common mutational events in certain lymphoma subtypes, namely PMBCL and cHL, as well as DLBCL cases arising in immune-privileged sites of the body [172,216,217]. Despite the fact that these lymphoma entities differ in their expression of certain B cell lineage markers and transcription factors, the expression of surface MHC class II molecules seems to be defective in a considerable fraction of cases (especially in PMBCL and cHL) - a finding that has been linked to reduced immunogenicity of tumour cells and was shown to correlate with inferior survival [133,134]. The recurrent structural genomic alterations (specifically, unbalanced chromosomal rearrangements) of CIITA, the master regulator of MHC class II transcription, were thought to be likely causative of MHC class II loss, however a detailed analysis of MHC class II protein expression and correlations with microenvironment composition and patient outcomes have not been performed. Although these chromosomal aberrations of CIITA seem to be critical pathogenic drivers, facilitating immune escape of the malignant B cell population, the full spectrum of genetic changes and related functional phenotypes in lymphomas still remain largely  26 unexplored. It follows, that the underlying causes of reduced MHC class II expression are only partially understood. CIITA and its pathogenic relevance were first described in a rare but severe immune disorder, namely hereditary MHC class II deficiency or type II BLS [189]. Patients affected by this heritable disease often harbor loss of function mutations within CIITA, resulting in a lack of MHC class II protein expression. Since this is indispensable for the display of foreign antigens to CD4+ T cells, BLS patients often suffer from multiple infections resulting from an insufficient adaptive immune response. CIITA expression is regulated by usage of different promoters in a cell type specific manner. Four promoters have been described in the literature [196] and transcripts deriving from these promoters differ in their first exon. Promoter III driven transcription of CIITA is the major source of CIITA expression in B cells, whereas expression from the interferon -inducible promoter IV only plays a minor role in this cellular context. Here, we aimed to describe the full spectrum of genomic alterations of CIITA in PMBCL, DLBCL and FL, including chromosomal rearrangements and coding sequence mutations. Furthermore, by applying targeted capture sequencing approaches we wanted to identify and characterize rearrangement partner genes as well as the biological implications of these structural genomic variants.  2.2 Materials and methods 2.2.1 Cell lines and patient cohorts 2.2.1.1 Cell lines The PMBCL-derived cell lines U2940, MedB-1 and Karpas1106P, as well as the nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL)-derived cell line DEV, were previously selected for and characterized by whole transcriptome paired-end sequencing (RNA-Seq) [104,216]. Karpas1106P was provided by Dr. M. Dyer (University of Leicester, UK) and grown in RPMI-1640 media (Life Technologies) with 20 % heat-inactivated fetal bovine serum (FBS, Life Technologies). The cell line U2940 was obtained from Dr. L. Staudt (National Institute of Health, Bethesda, MD) and propagated in RPMI with 10 % heat-inactivated FBS. MedB-1 was a kind gift from Drs. S. Brüderlein and P. Möller (Department of Pathology, University of Ulm, Germany) and  27 propagated as published [218]. The cell line DEV was generously provided by Dr. A. Diepstra (University Medical Center Groningen, The Netherlands) and grown in RPMI with 20 % heat-inactivated FBS. The lymphoblastoid cell line (LCL) was derived from Epstein-Barr virus (EBV)-transformed B cells of a healthy male donor and provided by Dr. U. Steidl (Albert Einstein College of Medicine, New York, NY). These cells were grown in RPMI supplemented with 20 % heat-inactivated FBS, 1 % penicillin/streptomycin, 1 % non-essential amino acids and 1 % sodium pyruvate (all Life Technologies).  2.2.1.2 Patient cohorts 2.2.1.2.1 PMBCL cohort We identified and selected diagnostic pre-treatment specimens from 45 PMBCL patients from our database based on the availability of fresh-frozen (FF) tissue biopsies or cell suspensions. Those were then retrieved from the tissue archives of the Centre for Lymphoid Cancer (CLC) at the British Columbia Cancer Agency (BCCA). Of these 45 cases, seven PMBCL specimens with available matched constitutional DNA were previously used for whole-genome sequencing (WGS) or RNA-Seq analyses [104]. Formalin-fixed, paraffin-embedded (FFPE) tissue specimens from 148 PMBCL cases were assembled on tissue microarrays (TMA), as described previously [104,172].  2.2.1.2.2 DLBCL cohort3 Next, we explored CIITA mutations in a cohort consisting of tissue biopsies stemming from 347 patients diagnosed with de novo DLBCL. All of these patients were uniformly treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and FF tissue or cell suspensions were available for targeted re-sequencing analyses of the protein coding region of 58 genes, known to be important for DLBCL pathogenesis. All tissue biopsies were reviewed by experienced haematopathologists at the BCCA and in addition, clinical parameter and outcome data, as well as COO, determined by the Lymph2Cx assay [65], were available.                                                  3 This cohort was primarily assembled by Drs. Daisuke Ennishi, David Scott and Randy Gascoyne as part of the TFRI program project grant, subproject 2.  28 2.2.1.2.3 FL cohort4 This cohort represents a spectrum of FL patients with different courses of their disease: 1) patients initially diagnosed with FL who subsequently experienced transformation (tFL) to a high-grade lymphoma (in most cases of the DLBCL subtype); 2) patients with progressive disease (pFL) within 2.5 years after treatment initiation, but without histological evidence of transformed FL; and 3) patients who had no clinical signs of progression (npFL) for at least 5 years. The final cohort used for capture sequencing (see section 2.2.5.3) consisted of 277 FL patients, of which 159 belonged to the transformed group (118 of those had biopsies available from timepoint T1 (per definition, the primary FL diagnosis) and T2 (timepoint of transformation, usually presenting as DLBCL), for 10 patients only the T1 biopsy was available, and 31 patients were represented solely by their T2 biopsy). Forty-one specimens from patients with pFL and 84 biopsies from patients with npFL completed the cohort. All biopsies were centrally reviewed by expert haematopathologists at the BCCA and Lymph2Cx assay scores were available for transformed lymphomas with classical DLBCL morphology [219].  2.2.2 Cell sorting Frozen vials of cells obtained from reactive tonsillar specimens were thawed and stained with purified mouse anti-human CD77 antibody (Clone 5B5, BD Pharmingen) for 30 minutes on ice. Cells were then incubated for 15 minutes at 4ºC with rat anti-mouse IgM MicroBeads (Miltenyi) and subsequently separated using the autoMACS Pro cell separator (Miltenyi) in order to enrich for germinal center B cells.  2.2.3 Fluorescence in situ hybridization (FISH) FISH break-apart (ba) assays were performed on TMAs, containing duplicate cores (0.6 or 1.0 mm in diameter) from each specimen. Briefly, TMA sections were stained with green and red labelled bacterial artificial chromosome (BAC) probes                                                  4 This cohort was primarily assembled by Drs. Robert Kridel and Randy Gascoyne as part of the TFRI program project grant, subproject 1.  29 flanking the genomic region containing the CIITA gene (Figure 2.1,Table 2.1.). DAPI (4,6-Diamidino-2-phenylindole) was used for counterstaining of the cell nuclei.    Figure 2.1: Schematic of the CIITA FISH assay. Shown at the bottom are the genomic coordinates of the hg19 chr16p13.13 locus, which contains the CIITA gene (other genes in this region are not depicted here for visualization purposes). The BACs flanking this region are labelled with either a green or a red fluorescent probe, corresponding to their respective boxes in this picture.  Table 2.1: Specification of the BACs used for assessment of the CIITA locus by FISH BAC/gene name Genomic coordinates start end CIITA 10,971,055 11,018,840 RP11-109M19 10,680,358 10,866,730 RP11-66H6 11,036,514 11,203,598 Genomic coordinates are given according to GRCh37/hg19. BAC: bacterial artificial chromosome.  After hybridization, slides were imaged using a Zeiss AXIO Imager.Z2 microscope, equipped with a Metafer imaging system (MetaSystems). One hundred interphase nuclei were assessed for each specimen and for all cores with examinable patterns, the rearrangement status was determined. Cases were classified as ba-positive if > 5 % of nuclei had split signals or signal patterns indicative of unbalanced rearrangements (e.g. loss of one signal). For CNV, the following cut-offs were applied: 1) loss: > 40 % of nuclei with one fusion signal; 2) gain: > 20 % nuclei with three or four fusion signals; and 3) amplification: > 20 % of nuclei with five or more fusion signals.  30  2.2.4 Copy number analysis Affymetrix Human SNP 6.0 microarrays were used to profile the genome-wide copy number (CN) status of the cell lines Karpas1106P, U2940, MedB-1 and DEV following standard protocols according to the manufacturer’s instructions. After quality control, SNP 6.0 microarrays were pre-processed using the PennCNV-Affy protocol [220]. OncoSNP (v1.3) was then used to simultaneously segment and predict CN [221]. The CN states of these segments were subsequently projected onto genes using Ensembl (version 72) as the scaffold.  2.2.5 Sequencing of CIITA coding sequence and intron 1 Sequencing for the three lymphoma cohorts described in section 2.2.1.2 was performed as part of different subprojects within the TFRI team grant at different timepoints, hence various sequencing methods were applied. Therefore, this section will be subdivided and details will be provided for the different approaches with respect to the corresponding cohort.  2.2.5.1 Sequencing of the PMBCL cohort Genomic DNA and RNA were extracted using the AllPrep DNA/RNA FFPE kit (Qiagen). CIITA coding sequence (CDS) mutations in primary PMBCL tumour specimens were detected by re-analysis of the previously generated WGS and/or RNA-Seq libraries (n = 7) [104]. In 18 cases, Sanger sequencing was performed for all coding exons and 30 cases were analyzed by deep amplicon sequencing (TruSeq Custom Amplicon assay (TSCA), Illumina). One case could not be completely characterized due to insufficient amounts of nucleic acids. For details, see A.1. TSCA was performed according to the manufacturer’s instructions. Briefly, 250 ng genomic DNA was amplified with oligonucleotides for the complete protein-coding sequence of CIITA and the alternative exon 1 that is driven by the pIV promoter (details of the oligonucleotide sequences can be found in A.2). Amplicon libraries were sequenced on an Illumina MiSeq instrument using the V2 300-cycles MiSeq reagent kit (Illumina), generating 150 bp paired-end reads. Sequencing reads were aligned to hg19  31 using Bowtie (v2.1) [222]. VarScan (v2.3.6) was then run using the tumour-normal comparison mode “somatic” for paired tumour-normal specimens. For single tumour samples, VarScan was run using mpileup2snp. Mutational data was then annotated using SnpEff (v3.2) with respect to the GRCh37.70 database. The following filters were applied for the paired tumour-normal sample data following VarScan: 1) filtering of SNPs (dbSNP137); 2) filter mutations with SnpEffs DOWNSTREAM, UPSTREAM, INTERGENIC, and INTRAGENIC; 3) somatic status (SS) == 2; 4) tumour variant read ratio > 0.1; 5) normal variant read ratio < 0.01; and 6) number of tumour reads > 10. The following filters were applied for the single tumour sample data following VarScan: 1) filtering of SNPs (dbSNP137); 2) filter mutations with SnpEffs DOWNSTREAM, UPSTREAM, INTERGENIC, and INTRAGENIC; 3) tumour variant read ratio > 0.05, and 4) number of tumour reads > 10. All mutation predictions resulting from WGS, RNA-Seq and deep amplicon sequencing were subjected to independent validation using Sanger Sequencing (3130 Genetic Analyzer, Applied Biosystems or outsourced to GENEWIZ Inc.). For the remaining specimens, which were not analyzed by NGS techniques, we amplified all CIITA coding exons by standard PCR prior to Sanger sequencing. Deletions in CIITA intron 1 were detected by amplification of a fragment covering the breakpoint cluster region [172] and aberrant length fragments (< 3 kb) were cloned into the pCR 2.1-TOPO vector (TOPO TA cloning kit, Invitrogen) and fully sequenced. Primer sets are listed in A.3. Sequence analysis and assembly were performed using Clone Manager software (Scientific & Educational Software). Genomic coordinates are given according to GRCh37/hg19.  2.2.5.2 Sequencing of the DLBCL cohort5 Deep amplicon sequencing of the DLBCL cohort was performed on the Illumina TSCA platform. The original panel consisted of 58 genes, which included recurrently mutated genes as described in previous studies [60,61,223], as well as genes of                                                  5 The study exploring the mutational landscape in DLBCL is spearheaded by Drs. Daisuke Ennishi and David W. Scott. Bioinformatics analyses were performed by Dr. Christoffer Hother, who, together with Dr. Ennishi, provided the initial draft for this methods section. In this thesis, only data on CIITA mutations were utilized for further exploration and analyses by myself.  32 biological interest. Oligo probes mapping to the target regions, which consisted of the entire protein-coding sequence of these genes, were designed using Illumina DesignStudio (Illumina); the coordinates for oligos capturing the CIITA gene locus are listed in A.4. Amplicon libraries were constructed according to the manufacturer’s protocol (Illumina) for end-repair, A-tailing and adaptor ligation, and 250 ng DNA from FF specimens served as input for the hybridization of the custom-designed oligo pool. Agencourt AMPure XP beads (Beckman Coulter) were used for PCR clean-up. Libraries were normalized according to the manufacturer’s instructions and were individually indexed using dual indexing before pooling. Purified pooled libraries were quantified on a real-time PCR instrument using the KAPA Illumina Library Quantification kit (KAPA Biosciences, KK4835) and quality control was performed with the Agilent Bioanalyzer (Agilent DNA 1000 Kit). Library pools were subsequently diluted into HT1 buffer prior to sequencing on the Illumina MiSeq instrument (Illumina), with MiSeq V2 cycle reagent kits and paired-end 2x150 bp reads. Sequencing data were converted and exported as FASTQ files using CASAVA (v1.8.2). Alignment was performed with bwa version 0.7.5a, and Mutascope (v1.02) was used to predict variants. Synonymous mutations and variants outside of the exonic space (e.g. intron, 5’ and 3’ untranslated region (UTR)) were excluded from further analysis. SNPs were filtered out if they appeared in the NCBI dbSNP137 or 1000 Genomes Project (v3) databases. Variants were not discarded, independent of their presence in other filters, if they were contained within the Catalogue of Somatic Mutations in Cancer (COSMIC) database (v62). Variant annotation and effect predictions were performed using SnpEff (v3.6).  2.2.5.3 Sequencing of the FL cohort6 Eighty-six genes were primarily selected for capture-based targeted sequencing of the FL cohort. Those genes were chosen based on three criteria: 1) recurrently mutated in FL with a frequency of > 5 % [90,93]; 2) recurrently mutated in DLBCL > 5 % (our own data) or 3) consistently mutated in BL [168,224,225]. Furthermore, 20 genes,                                                  6 The study exploring clonal evolution in FL is spearheaded by Drs. Robert Kridel and Fong Chun Chan and has been recently published [96]. Bioinformatics analyses were performed by Fong Chun Chan. For this thesis, only data on CIITA mutations obtained from capture-based targeted sequencing were utilized for further exploration and analyses by myself.  33 including CIITA, were selected to assess mutations in known targets of SHM. Libraries were constructed using either 500 ng of genomic DNA extracted from FF or 200 ng of FFPE tissue-derived genomic DNA as an input. Custom SureSelect XT2 baits (Agilent; total capture space 452,129 bp) were used for capturing. Libraries were subsequently pooled (maximum of 46 libraries per pool) and sequenced at Canada’s Michael Smith Genome Sciences Centre on one Illumina HiSeq lane per pool, generating 125 bp indexed reads (V4 chemistry). Alignment of sequencing reads to the GRCh37 genome was performed with bwa version 0.7.5a and cases with low mean target coverage (i.e. < 50x) were excluded from subsequent analyses. For single nucleotide variant (SNV) calling, MutationSeq (v4.3.8) [226] was used and the following criteria were applied: mutation probability > 0.8 and coverage > 100 or mutation probability > 0.9 and coverage < 100 for FF specimens; for FFPE specimens the requirements were relaxed to meet either a mutation probability > 0.7 and coverage > 50 or mutation probability > 0.9 and coverage < 50. For cases with available germline DNA (n = 80), SNVs were filtered out if they were present in the germline specimen. For all other cases, putative SNPs were identified and filtered out if they were present in at least two unrelated germline specimens from the 80 cases mentioned above or in dbSNP version 137. SNVs were annotated with SnpEff. For cases with matching germline specimens, indels were called using Strelka (v1.0.13) and for those without matching germline, indels were called using VarScan and putative germline variants were filtered out using dbSNP (v137) and the 1000 Genomes Project (v3) database.  2.2.6 Analysis of AID target motifs Potential AID target motifs (WRCY/RGYW) within the first 2 kb downstream of the TSS were identified using the Possum tool (http://zlab.bu.edu/~mfrith/possum/). Cytosine residues within (third position of the 4-base motif) and outside (including cytosine at position 4) of potential AID target motifs were then enumerated with the ratio (within vs outside) of these numbers representing the expected frequency of a cytosine within the motif being affected by mutation. Next, we determined how many of the observed mutations at cytosine residues occurred in WRCY/RGYW motifs and compared this to the number of affected cytosines outside these hotspots.  34 2.2.7 Immunohistochemistry  Immunohistochemistry (IHC) was performed on 4 m sections from FFPE tissue specimens arranged on previously constructed TMAs [104,172] or on whole tissue sections in the case where a particular sample was not evaluable or represented on the TMA. Following antigen retrieval, sections were stained with a primary antibody recognizing AID (dilution 1:75, clone 1A9-1, Cell Signaling, #4959) followed by routine protocols for automated IHC on the Ventana Benchmark XT (Ventana Medical Systems). The percentages of positive tumour cells were recorded in 10 % increments.  2.2.8 Characterization of chromosomal rearrangements Targeted sequencing approaches are ideally suited for research questions focusing on a circumscribed genomic region. Therefore, this technology has become increasingly popular in cancer research since many malignancies are characterized by recurrent mutations and rearrangements in a relatively small number of genomic loci. For our comprehensive assessment of structural variants (SV), we explored two different approaches which are further explained in the sections below.  2.2.8.1 Bacterial artificial chromosome (BAC) capture7 To explore novel structural genomic rearrangement partners and breakpoints in primary testicular lymphoma (PTL), a DLBCL arising primarily in the testis, three pre-treatment biopsies, one of which was previously shown to be 9p24.1 rearranged by FISH, were selected for targeted BAC capture high-throughput sequencing [216]. One extranodal DLBCL, known to harbour a TBL1XR1-TP63 inversion and a BCL2 rearrangement, was sequenced as a positive control [69]. DNA was extracted from these archival FFPE biopsies using the Qiagen DNA/RNA FFPE Kit as per the manufacturer’s protocol and 2 μg were used for library construction. To identify gene fusions and structural genomic alterations, we re-sequenced 7.45 Mb of the human genome with a focus on 12 loci known to be recurrently affected by rearrangements in B-cell lymphomas [59,69,172,216]: CIITA, CD274 (PDL1), PDCD1LG2 (PDL2), TP63, TBL1XR1, BCL2, BCL6, IGH, IGL, IGK, MYC and JAK2. Custom capture was                                                  7 A version of this paragraph is included in [217] and is used with permission.  35 performed in four FFPE specimens using biotinylated RNA capture probes derived from BAC clones. Briefly, 72 BAC clones from the RPCI-11 library were identified as spanning the 12 gene loci from the reference human genome assembly (GRCh37/hg19) displayed in the UCSC Genome Browser. BAC clone DNA was extracted and the identities confirmed by BAC-end Sanger sequencing using T7 and SP6 primers and DNA fingerprinting. Validated clone DNAs were pooled, sonicated, and products in the 75-200 bp range were excised from an 8 % PAGE gel and quantified. Two hundred ng of the size-selected pooled DNA was end-repaired and phosphorylated for A-tailing and adapter ligation. Adapter-ligated products were enriched using eight cycles of PCR. Gel-purified DNA was in vitro transcribed using T7 RNA Polymerase. Libraries were captured using a 400:1 ratio of BAC-derived probes to library DNA. Products subsequently underwent 17 cycles of PCR prior to sequencing which was performed on an Illumina HiSeq2000 generating 75 bp paired-end reads. Sequencing data was analysed using the nFuse and deStruct algorithms to generate and cross-corroborate rearrangement predictions, as has been previously published [216,227]. These predictions were subsequently filtered on the basis of the validation probability metric (> 0.75); a score of uniqueness among libraries, quality and number of spanning and split read support, and alignment relative to the capture space. Subsequently, these events were BLAT-assessed and a select number were validated by Sanger sequencing.  2.2.8.2 Capture sequencing8 As an alternative to BAC capture sequencing, we used a custom Agilent SureSelect design to enrich for specific genomic regions. Genomic coordinates were chosen based on our genes of interest and all previously described rearrangement breakpoints were taken into consideration. Two regions were located on chromosome 16: one spanning the CIITA gene and the other located downstream, spanning the SOCS1 gene. SOCS1 is a known tumour suppressor in cHL and PMBCL, which regulates JAK/STAT signaling and is frequently mutated in those lymphoma entities [228]. The third region spanned the adjacent CD274 and PDCD1LG2 genes on chromosome 9 and was designed to include all previously described PDL translocation                                                  8 This section is in part published in [214] and is used with permission.  36 breakpoints. Table 2.2 displays the exact target coordinates used in the capture design, spanning approximately 0.5 Mb of genomic space in total.  Table 2.2: Custom Agilent SureSelect design used for capture sequencing. Gene  Chromosome Captured region Capture space (bp) start end CD274 and PDCD1LG2 9 5,449,434 5,573,579 124,146 CIITA 16 10,959,585 11,277,301 317,717 SOCS1 16 11,332,082 11,350,098 18,017 Genomic coordinates are given according to GRCh37/hg19.  The Agilent SureSelect custom kit consisted of labeled RNA probes complementary to the target space (Table 2.2). Probes were designed using 5x tiling and standard boosting. Repetitive regions were not masked to increase the likelihood to identify breakpoints located in repetitive regions, even though this also increased the off-target capture rate. Cases were selected based on results from previous screening studies using FISH to interrogate the CIITA, TBL1XR1 and PDL loci. FISH assays were performed as described in section 2.2.3. Specimens were selected if they had a ba-positive status at any of these loci. In addition, five samples were included because they showed over-expression of one or both PDLs by qRT-PCR, but were negative for structural rearrangements or CNV by FISH. Genomic DNA and RNA were extracted from FFPE tissue scrolls using the Qiagen AllPrep DNA/RNA FFPE kit according to the manufacturer’s instructions. Library construction was performed at Canada’s Michael Smith Genome Sciences Centre using a 96-well plate protocol suitable for FFPE. All DNA samples were normalized to contain 100 ng in a total volume of 62 l elution buffer (Qiagen). DNA was subsequently transferred into a microTUBE plate for shearing using an LE220 acoustic sonicator (Covaris) and the following conditions: duty factor = 20 %, peak incident power = 450 W, cycle per burst = 200, duration = 2x 60 seconds with an intervening spin. The expected fragment size for this protocol is 300-400 bp. In order to further improve the quality of the library, a solid phase reversible immobilization (SPRI)  37 bead-based size selection was performed to remove smaller DNA fragments which may have resulted from fragmentation processes occurring during formalin fixation. DNA damage and end-repair, as well as phosphorylation were performed in a single reaction using an enzyme premix (NEB). Repaired DNA fragments were A-tailed for ligation to paired-end, partial Illumina sequencing adapters and then purified twice with SPRI beads. Eight cycles of PCR were performed to introduce fault-tolerant hexamer “barcodes” to allow multiplexing of the libraries for sequencing. Final library concentration was measured using a high sensitivity Caliper LabChip GX in conjunction with Quant-iT (Invitrogen). Libraries were pooled prior to capture. Sequencing was performed in two batches, the first batch consisted of 16 libraries and was sequenced in a single lane on an Illumina HiSeq 2500 using version 3 chemistry, producing paired-end 100 bp reads. The second batch of the remaining 52 libraries was pooled into two groups of 17 and one group of 18. Sequencing was performed using version 4 chemistry, resulting in paired-end 125 bp reads. Following quality control measures, including filtering and removal of duplicate reads, FASTQ files were aligned to the GRCh37 genome. Quality control and bioinformatics analysis including SV detection were performed by Lauren C. Chong and are described in detail in her Master’s thesis (https://dx.doi.org/10.14288/1.0229569). To validate predicted structural rearrangement events, custom primer sets were designed for a targeted PCR amplification of the respective genomic region (A.3). Primer design was performed using the Primer3 software (version 0.4.0; http://bioinfo.ut.ee/primer3-0.4.0/primer3/). Successfully amplified PCR products were subsequently Sanger sequenced.  2.2.9 Statistical analysis The Fisher’s exact test and 2 test were used to compare categorical variables. McNemar’s test was used when comparing categorical variables between paired specimens. P-values < .05 were considered being significant.   38 2.3 Results 2.3.1 CIITA alterations in PMBCL 2.3.1.1 Biallelic genomic alterations of CIITA in PMBCL- and NLPHL-derived cell lines We have previously demonstrated that genomic rearrangements of CIITA occur in various lymphoid malignancies and are highly recurrent in cHL and PMBCL [172]. In order to inform on the prevalence and different types of genomic aberrations affecting CIITA in PMBCL, we first re-analyzed previously published whole transcriptome sequencing (RNA-Seq) data of three PMBCL-derived cell lines: Karpas1106P, MedB-1 and U2940 [104]. Since we have reported on a CIITA-PDCD1LG2 fusion in DEV, an NLPHL-derived cell line [216], this was also included in the analysis. In addition, we performed high-resolution CN analysis (Affymetrix SNP 6.0 arrays), and validated identified SNVs and rearrangements by Sanger sequencing. No CIITA copy number or structural alterations were found in MedB-1, but we identified two SNVs, one (hg19 chr16: g.10989537G>A) resulting in an amino acid exchange (p.71Asp>Asn) in the acidic domain and the other (hg19 chr16: g.35202C>T) altering the amino acid sequence (p.636Thr>Met) in the conserved NACHT-domain of the CIITA protein. Analysis of individual cDNA clones showed that these point mutations occur in trans configuration (Figure 2.2).   Figure 2.2: CIITA genetic alterations in the PMBCL-derived cell line MedB-1. MedB-1 is characterized by two missense mutations occurring in trans and leading to amino acid exchanges in functionally relevant protein domains (green: acidic domain; blue: NACHT domain; red: leucine rich repeat (LRR) domain). All genomic coordinates are given according to the hg19 reference genome.     39 It has been previously described that the tumour suppressor SOCS1 is inactivated in the Karpas1106P cell line due to a biallelic deletion in this chromosomal region [228,229]. Interestingly, CIITA is located just 0.5 Mb telomeric of SOCS1. Analysis of our RNA-Seq data revealed a lack of CIITA mRNA expression in this cell line but detected a TXNDC11-EMP2 fusion transcript (exon 3 of TXNDC11 spliced in frame to exon 2 of EMP2; Figure 2.3), which is the result of a genomic deletion encompassing 11 genes including CIITA, SOCS1 and CLEC16A, the latter recently shown to be involved in normal B cell development [230]. The precise coordinates of the deletion were determined as hg19 chr16: g.10641751_11825721del. The SNP array data identified a region in which to perform a “PCR walk” to inform on the breakpoints of the deletion encompassing the 5’ region of the other CIITA allele, which were in intron 1 of TVP23A and intron 1 of CIITA (hg19 chr16: g.10899052_10985179del), resulting in the loss of pIII and the associated exon 1 (Figure 2.3). As would be expected, because TVP23A and CIITA appear in opposite orientations on the chromosome, and the promoter for TVP23A is also deleted, no transcript from this fusion was detected in the RNA-Seq data.   Figure 2.3: CIITA genetic alterations in the PMBCL-derived cell line Karpas1106P. Karpas1106P harbours a large deletion encompassing CIITA and SOCS1, leading to a novel gene fusion between EMP2 and TXNDC11. The other allele is affected by a genomic deletion, resulting in the structural disruption of CIITA. All genomic coordinates are given according to the hg19 reference genome.  A similar analysis of U2940 led to the discovery of an in-frame NUBP1-CIITA fusion transcript with the amino terminus of the predicted chimeric protein encoded by the first nine exons of NUBP1 and the carboxyl terminus encoded by all but the first exon of CIITA. The genomic deletion was determined to be hg19 chr16:  40 g.10858971_10974177del (Figure 2.4). Detailed information on the breakpoint sequence and effect at the transcript level are highlighted in Figure 2.5. Since transcription of the NUBP1-CIITA fusion would be driven by the NUBP1 promoter, instead of the strong B-cell CIITA promoter pIII, expression of CIITA from this allele would be expected to be reduced. Indeed, the majority of transcripts (97 %) detected by RNA-Seq were derived from the second allele, which in this cell line, harbours an SNV (hg19 chr16: g.11017158C>T) that results in the loss of the original stop codon (p.1131STOP>R*35; Figure 2.4).   Figure 2.4: CIITA genetic alterations in the PMBCL-associated cell line U2940. In U2940, a large deletion results in a NUBP1-CIITA fusion transcript (for details see Figure 2.5). The second allele has acquired a base substitution mutation resulting in the loss of the stop codon. All genomic coordinates are given according to the hg19 reference genome.    41  Figure 2.5: NUBP1-CIITA fusion observed in U2940 using RNA-Seq. The upper panel shows the genomic structure with paired read sequences aligning on either side of the breakpoint (orange and blue lines). Split reads spanning the breakpoint are highlighted in green with the histogram on the right showing the absolute frequency for each of these reads. The lower panel provides the reading frame at the breakpoint junction and the putative translation. All genomic coordinates are given according to the hg19 reference genome. By integrating high-resolution CN analysis, FISH mapping and a stepwise PCR approach, we were able to decipher the genomic structure of the CIITA rearrangements in the cell line DEV (Figure 2.6). One allele is disrupted by a reciprocal translocation and deletion. The CIITA-PDCD1LG2 fusion has been previously described [216] and similar fusions have been observed in two primary PMBCL cases [172]. The PDCD1LG2-CIITA fusion (t(9;16)(p24.1;p13.13)(chr9:g.5511575::chr16:g.10971955) is linked to a large deletion between CIITA intron 1 and CLEC16A that includes most of the coding sequence of CIITA (hg19 chr16: g.10973066_11275555del). This reciprocal translocation results in PDCD1LG2 expression driven by the CIITA promoter and a complex PDCD1LG2-CIITA-CLEC16A rearrangement failing to encode a functional CIITA protein. Additionally, we identified an inversion involving the second CIITA allele  42 and SOCS1 (hg19 chr16: g.10972393_11348602inv), that would lead to the functional abrogation of CIITA.   Figure 2.6: CIITA genetic alterations in the NLPHL-derived cell line DEV. CIITA rearrangements in DEV are complex, involving the PD-1 ligand PDCD1LG2 and SOCS1, respectively. See main text for detailed description. All genomic coordinates are given according to the hg19 reference genome.  2.3.1.2 CIITA coding sequence mutations and structural genomic alterations in primary PMBCL cases Prompted by the observed CIITA aberrations in cell lines, we next investigated to what extent such genetic alterations could be detected in primary PMBCL tumours. First, we focused on recently published WGS and RNA-Seq data of seven cases [104]. We identified one case (#19) harbouring a somatic CDS mutation (hg19 chr16: g.11001430T>C, p.694Leu>Ser), which has been validated by deep amplicon sequencing. A second case (#20) revealed a nonsense mutation (hg19 chr16: g.10992550C>T) resulting in the acquisition of a premature stop codon (p.107Glu>Stop). Both mutations were independently validated using Sanger sequencing. Based on these observations, we next screened for mutations within the 19 coding exons of CIITA and alterations in the pIII region in a larger cohort of PMBCL  43 biopsies. In total, we selected 45 cases (“sequencing cohort”) from the CLC database at the BCCA based on availability of FF material obtained prior to treatment (A.1). After exclusion of known SNPs and synonymous mutations, we found 16 SNVs within the CDS of 13 clinical specimens, consisting of seven nonsense/frameshift mutations, one SNV resulting in loss of the start codon, four missense mutations and four splice site alterations affecting the exon 1 splice donor site. One of these cases (#16) also harboured a small deletion of 8 bp in the 5’ UTR and a partial deletion of exon 1 that extends into the first intron. In addition, we observed another case (#2) with four alterations in the pIII region and a 232 bp deletion that encompasses the entirety of exon 1 from 14 bp upstream of the TSS extending into intron 1. One sample (#4) displayed a single bp substitution in pIII. Overall, alterations affecting the pIII region seem to be rare (five mutations in only two cases), whereas almost half of the CDS mutations (43.8 %) occur in the first exon. The distribution and types of mutations for each exon are shown in Figure 2.7, and a detailed assembly of genomic coordinates and the putative translational impact is given in B.1. For three PMBCL cases we confirmed the identified mutations as being of somatic origin by sequencing constitutional DNA extracted from peripheral blood (for details see B.1).   Figure 2.7: Coding sequence mutations in primary PMBCL cases. The distribution of CIITA coding sequence mutations in 44 analyzed primary PMBCL specimens identified by WGS, RNA-Seq, TruSeq custom amplicon sequencing and Sanger sequencing. Variations in non-coding regions, silent mutations, larger deletions and known SNPs are not shown. Abbreviations: TSS, translational start site; LRR, leucine-rich repeats.   44  In order to inform on structural chromosomal alterations in our sequencing cohort, we performed FISH on two TMAs, encompassing 148 PMBCL cases in total, including 41 of the cases in our sequencing cohort. We also performed FISH on whole tissue sections from FFPE tissue biopsies either not represented or initially not evaluable on the TMAs. In total, specimens from 150 individual patients were analyzed and FISH was evaluable in 116 cases (77 %), of which 77 were previously reported [172]. Thirty-nine cases (33.6 %) were scored as CIITA ba-positive in the entire cohort (n = 116), including 15 of 41 evaluable samples (36.6 %) in the sequencing cohort. A FISH signal constellation indicative of unbalanced rearrangements and/or deletion of genomic sequence next to the CIITA breakpoint was found in 44 % of ba-positive cases.  2.3.1.3 Intron 1 deletions and point mutations in primary PMBCL cases We have previously shown that the majority of CIITA translocation breakpoints in PMBCL cluster within a distinct, 1.6 kb spanning region near the 5’ end of intron 1 [172]. Of note, the breakpoints observed in DEV fall in the exact same region, prompting us to examine in detail the genomic sequence of this region in our sequencing cohort. Genomic DNA extending 3 kb from the end of exon 1 into intron 1 was PCR-amplified and visualized after agarose gel electrophoresis. Deletions were clearly evident in 13 of the 45 primary PMBCL samples but were not observed in 20 DLBCL cases, five reactive lymph nodes and three samples of purified tonsillar germinal centre B cells that were analyzed for comparison, suggesting that these deletions might be a specific event in PMBCL pathogenesis. Cloning and sequencing of the aberrant length fragments revealed frequent microdeletions, multiple base substitutions and (more rarely) small insertions, duplications and inversions. As many as 51 alterations were seen per clone and multiple SNVs were detected in some of the alleles lacking visible deletions. In total, 21 cases from the sequencing cohort were found to have sequence alterations within the first 3 kb of intron 1. The allelic origin of a cloned sequence can be inferred from the sequence at heterozygous SNP positions and showed that, at least in some cases, biallelic sequence variants have been acquired. Emphasizing the genomic instability of this region in PMBCL, analysis of 15 PCR clones amplified from purified tonsillar germinal centre B cells of three donors (five clones per donor) revealed only a  45 total of nine base substitutions among seven clones. A detailed description of the genomic aberrations is given in Figure 2.8 and B.2.    Figure 2.8: CIITA intron 1 alterations in primary PMBCL cases. Depicted is the CIITA genomic locus with the pIII region and the first 3 kb of intron 1. a) Sequencing analyses revealed multiple genomic aberrations. Point mutations and deletions detected in individual cases are shown. In contrast, sequence alterations were rare in reactive germinal centre B cells (GCB). b) For visualization purposes, only mutations affecting transcription factor binding sites and responsive elements in the pIV region or the alternative exon 1 are shown. Red triangles indicate deletions, green dots SNVs.  46 Interestingly, deletions and SNVs seemed to be enriched in a region encoding the alternative exon 1 of the CIITA transcript that is driven by the pIV promoter and is inducible in many different cell types upon IFN  stimulation (Figure 2.8). In some primary tumours, we found clear evidence that a stepwise accumulation of genetic alterations occurred, indicating genomic instability and clonal evolution (Figure 2.9).   Figure 2.9: Subclonal evolution. Three primary PMBCL cases showed clear evidence for subclonal evolution, likely as the result of ongoing somatic hypermutation at the CIITA gene locus. Genetic aberrations which were acquired in individual subclones are shown in boxes adjacent to a particular cloned sequence.  Furthermore, the high prevalence of CDS mutations in exon 1 and alterations within the first 3 kb of intron 1 led us to speculate that these alterations are the result of AID-mediated aberrant SHM. We, therefore, analyzed all SNVs observed within 2 kb from the TSS to determine whether they represent transitions or transversions. In total, 233 transitions and 146 transversions occurred (ratio 1.6:1), which is considerably skewed compared to the theoretically expected transition/transversion ratio (1:2). Furthermore, we found a significant enrichment in mutated cytosine residues within AID target motifs than one would expect by chance (χ2 test P < .001). Specifically, cytosine residues within AGC sequence motifs were most commonly affected (Figure 2.10).   47  Figure 2.10: AID hotspot targets are frequently mutated in PMBCL. Absolute frequency of mutated cytosine residues within the genomic context of two basepairs upstream. Red bars indicate AID hot spot targets based on RGYW/WRCY motifs.  We then asked the question if AID protein expression is detectable in diagnostic biopsy material of PMBCL cases. Immunohistochemistry was evaluable in 114 cases. 48.2 % (55/114) were considered positive with variable percentages of tumour cells stained. Two representative cases are depicted in Figure 2.11.   Figure 2.11: AID protein expression in PMBCL cases. The large neoplastic cells in a) show moderate to strong cytoplasmic positivity, whereas the tumour cells in b) are negative. Original magnification: x400.  48 2.3.2 CIITA alterations in DLBCL In the cohort of 347 de novo DLBCL cases, we found 36 mutations in 31 individual specimens, resulting in a mutation frequency of 8.9 % for the CIITA gene in this lymphoma entity. The majority consisted of missense mutations (29/36; 80.5 %), followed by splice site alterations (4/36; 11.1 %) and frameshift mutations (3/36; 8.3 %). The distribution and types of mutations for each exon are shown in Figure 2.12 and a detailed assembly of genomic coordinates and the putative translational impact is given in Table 2.3. Notably, when integrating data obtained from the molecular subtyping of these cases using the Lymph2Cx NanoString assay [65,231], no significant association with the GCB- or ABC-DLBCL subtype could be observed (Fisher’s exact test: P = .38). Compared to the distribution of CDS mutations in PMBCL (see Figure 2.7 in section 2.3.1.2), no obvious enrichment within the first exon of CIITA could be observed in DLBCL cases. Instead, most of the mutations seemed to cluster in the gene region encoding for the conserved NACHT-domain (GTP-binding domain) and the LRR-domain at the carboxyl-terminus.   Figure 2.12: Coding sequence mutations in primary DLBCL cases. The distribution of CIITA coding sequence mutations in 347 analyzed primary DLBCL specimens identified by TruSeq custom amplicon sequencing. Variations in non-coding regions, silent mutations and known SNPs are not shown. Abbreviations: TSS, translational start site; LRR, leucine-rich repeats.   49 Table 2.3: CDS mutations in DLBCL. Case Gene Chromosome Position Ref Alt VAF Mutation type cDNA AA change DLC006 CIITA chr16 11001778 T A 26.03 MISSENSE 2429T>A Leu810Gln DLC007 CIITA chr16 10997738 G C 50.63 MISSENSE 923G>C Arg308Pro DLC018 CIITA chr16 11001940 G C 71.35 MISSENSE 2591G>C Arg864Pro DLC041 CIITA chr16 11009508 G T 40.89 SPLICE_SITE   DLC041 CIITA chr16 11016055 G A 28.84 MISSENSE 3181G>A Ala1061Thr DLC041 CIITA chr16 11009492 C T 40.89 MISSENSE 2954C>T Ser985Phe DLC041 CIITA chr16 11009491 T A 40.89 MISSENSE 2953T>A Ser985Thr DLC048 CIITA chr16 11000793 G A 46.91 MISSENSE 1444G>A Glu482Lys DLC073 CIITA chr16 10971233 C CCCCA 6.07 FRAME_SHIFT 47_48insCCCA Gln17Hisfs*22 DLC080 CIITA chr16 11016023 G A 5.65 SPLICE_SITE   DLC092 CIITA chr16 11000940 G A 47.08 MISSENSE 1591G>A Gly531Ser DLC103 CIITA chr16 11016097 C T 43.02 MISSENSE 3223C>T Arg1075Trp DLC142 CIITA chr16 10989151 G T 62.46 MISSENSE 65G>T Cys22Phe DLC142 CIITA chr16 11009462 A G 25.24 MISSENSE 2924A>G Lys975Arg DLC149 CIITA chr16 11001295 C G 45.75 MISSENSE 1946C>G Ala649Gly DLC151 CIITA chr16 10997686 G A 8.67 MISSENSE 871G>A Ala291Thr DLC167 CIITA chr16 11016287 C G 11.95 MISSENSE 3257C>G Ala1086Gly DLC169 CIITA chr16 10971240 G A 49.17 SPLICE_SITE   DLC173 CIITA chr16 11000940 G A 50.91 MISSENSE 1591G>A Gly531Ser DLC178 CIITA chr16 10989612 G A 61.93 MISSENSE 286G>A Ala96Thr DLC183 CIITA chr16 10971233 C A 22.51 MISSENSE 46C>A Pro16Thr DLC222 CIITA chr16 11009462 A G 49.15 MISSENSE 2924A>G Lys975Arg DLC251 CIITA chr16 10997588 G A 65.76 MISSENSE 773G>A Gly258Asp DLC283 CIITA chr16 11001388 TC T 28.42 FRAME_SHIFT 2040_2041delC Pro680Hisfs*3 DLC286 CIITA chr16 11001304 G GC 42.15 FRAME_SHIFT 1956_1957insC Gly655Argfs*92 DLC291 CIITA chr16 11001843 C T 49.64 MISSENSE 2494C>T Arg832Cys DLC293 CIITA chr16 11009462 A G 37.08 MISSENSE 2924A>G Lys975Arg DLC305 CIITA chr16 11000815 A G 53.12 MISSENSE 1466A>G Lys489Arg DLC319 CIITA chr16 11004092 G A 46.10 MISSENSE 2864G>A Arg955Gln DLC330 CIITA chr16 11010253 G T 11.59 MISSENSE 2999G>T Gly1000Val DLC353 CIITA chr16 11001939 C T 51.11 MISSENSE 2590C>T Arg864Cys DLC360 CIITA chr16 11002983 C T 26.09 MISSENSE 2755C>T Pro919Ser DLC360 CIITA chr16 11000658 T A 24.25 MISSENSE 1309T>A Trp437Arg DLC366 CIITA chr16 10989143 C G 13.03 MISSENSE 57C>G Ser19Arg DLC376 CIITA chr16 10971240 G A 40.82 SPLICE_SITE   DLC379 CIITA chr16 11000992 G A 51.29 MISSENSE 1643G>A Arg548Gln  50 2.3.3 CIITA alterations in FL 2.3.3.1 CIITA coding sequence mutations and structural genomic alterations in primary FL cases In the entire FL cohort, consisting of transformed and progressed/non-progressed cases, we detected 28 mutations affecting the CDS of CIITA. Similar to the DLBCL cohort, the majority represented missense mutations (19/28; 67.9 %). Furthermore, we found five nonsense/frameshift mutations (5/28; 17.9 %), one case with a small deletion of 3 bp leading to the loss of a codon and three alterations (3/28; 10.7 %) affecting splice sites. The distribution and respective types of mutations for each exon are shown in Figure 2.13 and a detailed assembly of genomic coordinates and the putative translational impact is given in Table 2.4.   Figure 2.13: Coding sequence mutations in primary FL cases. The distribution of CIITA coding sequence mutations in 397 analyzed primary FL specimens identified by targeted capture sequencing. Framed symbols indicate that this alteration was detected in both, the T1 and T2 timepoint of an individual case. Variations in non-coding regions, silent mutations and known SNPs are not shown. Abbreviations: TSS, translational start site; LRR, leucine-rich repeats.   51 Table 2.4: CDS mutations in FL Case Gene Chromosome Position Ref Alt VAF Mutation type cDNA AA change FL1002T1 CIITA chr16 11000647 T G 0.13 MISSENSE 1298T>G Val433Gly FL1002T2 CIITA chr16 11000647 T G 0.37 MISSENSE 1298T>G Val433Gly FL1013T1 CIITA chr16 10996526 AGTTCCTC A 0.22 FRAME_SHIFT 641_642delGTTCCTC Ser214* FL1013T2 CIITA chr16 10996526 AGTTCCTC A 0.26 FRAME_SHIFT 641_642delGTTCCTC Ser214* FL1014T2 CIITA chr16 11009456 T TCC 0.85 FRAME_SHIFT 2919_2920insCC Phe973Phe fs*20 FL1019T2 CIITA chr16 11001373 T G 0.29 MISSENSE 2024T>G Leu675Arg FL1116T2 CIITA chr16 11000362 T C 0.13 MISSENSE 1013T>C Val338Ala FL1122T1 CIITA chr16 11000686 A T 0.27 MISSENSE 1337A>T Asp446Val FL1145T1 CIITA chr16 11002013 T G 0.09 SPLICE_SITE_ REGION   FL1178T1 CIITA chr16 11001155 ACTT A 0.15 CODON_ DELETION 1807_1808delCTT Leu603X FL1190T2 CIITA chr16 10992591 T G 0.34 SPLICE_SITE_ DONOR   FL1192T2 CIITA chr16 11001783 T G 0.34 MISSENSE 2434T>G Cys812Gly FL1192T2 CIITA chr16 11010255 G T 0.39 MISSENSE 3001G>T Asp1001Tyr FL1198T1 CIITA chr16 11000865 G A 0.12 MISSENSE 1516G>A Ala506Thr FL1204T2 CIITA chr16 11000848 G C 0.48 MISSENSE 1499G>C Gly500Ala FL1221T2 CIITA chr16 10995370 G T 0.14 SPLICE_SITE_ ACCEPTOR   FL1221T2 CIITA chr16 11000589 C T 0.09 NONSENSE 1240C>T Arg414* FL1221T2 CIITA chr16 11016104 T C 0.07 MISSENSE 3230T>C Met1077Thr FL1229T2 CIITA chr16 11001122 A C 0.10 MISSENSE 1773A>C Gln591His FL1252T2 CIITA chr16 11017098 A G 0.43 MISSENSE 3331A>G Thr1111Ala FL2005T1 CIITA chr16 11016071 G A 0.97 MISSENSE 3197G>A Arg1066His FL2005T2 CIITA chr16 11016071 G A 1.00 MISSENSE 3197G>A Arg1066His FL2111T1 CIITA chr16 11000388 G A 0.42 MISSENSE 1039G>A Asp347Asn FL2111T1 CIITA chr16 11000895 G A 0.50 MISSENSE 1546G>A Gly516Arg FL2115T1 CIITA chr16 11000532 G T 0.44 NONSENSE 1183G>T Gly395* FL3013T1 CIITA chr16 10989621 G A 0.53 MISSENSE 295G>A Ala99Thr FL3140T1 CIITA chr16 10971192 G A 0.22 MISSENSE 5G>A Arg2His FL3144T1 CIITA chr16 10997689 C T 0.25 MISSENSE 874C>T Pro292Ser  52 Out of 277 successfully sequenced specimens in the tFL subset of the cohort, six samples which were obtained at the time of the initial FL diagnosis (T1 timepoint; 4.7 %) and 11 samples which were collected at the time of transformation (T2 timepoint; 7.4 %) carried mutations, with only two cases (out of 15) sharing the mutation between T1 and T2. There was no enrichment for CIITA mutations in the T2 specimens since four cases had a mutation present at T1 that was not detected at T2, whereas six cases showed mutations at the timepoint of transformation which could not be seen in the respective T1 specimen (McNemar’s test: P = .752). In addition, three cases with T2 mutations did not have sequencing data from their respective primary diagnostic specimen (T1) available. Among the early progressers (pFL), 8.1 % showed CDS mutations (3/37), whereas 3.6 % (3/83) in the late/no progressive group (npFL) were found to be mutated. Hence, there was no significant difference between pFL and npFL with regards to the prevalence of CIITA CDS mutations (Fisher’s exact test: P = .37). Likewise, CIITA mutations were not more frequently observed in cases, which eventually transformed compared to those which progressed (Fisher’s exact test: P = 1). We also performed FISH on all cases that were arranged on TMAs to interrogate the rearrangement status of CIITA. Out of 273 tissue specimens in the tFL subset of the cohort, 250 were evaluable (91.6 %). Thirty-five samples which were obtained at the time of the initial FL diagnosis (T1 timepoint; 29.9 %) and 49 samples which were collected at the time of transformation (T2 timepoint; 36.8 %) showed a signal constellation indicative of a CIITA ba-status. For 100 cases, information on CIITA ba-status was available for both timepoints, with 26 cases sharing the chromosomal rearrangement between T1 and T2. When restricting the analysis to those paired specimens, there was a significant enrichment for CIITA alterations in the T2 specimens, since, in addition to the 26 cases with concordant FISH results, five cases were ba-positive at T1 but not at T2, whereas 17 cases showed ba signals at the timepoint of transformation which could not be seen in the respective T1 specimen (McNemar’s test: P = .019). Among the early progressers 15.2 % showed CIITA ba-positivity (5/33 cases), whereas in the npFL group four out of 74 cases (5.4 %) were translocated. Hence, there  53 was no significant difference between pFL and npFL with regard to the prevalence of CIITA structural chromosomal aberrations (Fisher’s exact test: P = .13). However, CIITA ba-positive cases were significantly enriched in the cohort of FL specimens, which eventually transformed to a high-grade lymphoma compared to those which progressed (Fisher’s exact test: P < .0001).  2.3.3.2 Intron 1 deletions and point mutations in primary FL cases The CIITA gene was also assessed as a SHM target in the FL capture sequencing panel and, therefore, mutation calls for intron 1 were available and analyzed similar to the PMBCL cohort (see 2.3.1.3). For the tFL cohort, we focused on the paired specimens, for which we had sequencing data from both timepoints available (n = 118). In 80 cases (67.8 %) intron 1 mutations were detected and, in the vast majority, were seen in the specimens from both timepoints (93.75 %). As many as 46 alterations were seen, most of them confined to the region within 2 kb of the TSS, known to be a hotspot for AID-mediated SHM (Figure 2.14, B.3). We, therefore, analyzed all SNVs observed within 2 kb from the TSS to determine whether they represent transitions or transversions. In total, 384 transitions and 168 transversions occurred (ratio 2.3:1), which is, similar to PMBCL, considerably skewed compared to the theoretically expected ratio (1:2). Again, we found a significant enrichment in mutated cytosine residues within AID target motifs than one would expect by chance (χ2 test: P < .001). Specifically, cytosine residues within AGC sequence motifs were most commonly affected (Figure 2.15).  54  Figure 2.14: CIITA intron 1 alterations in tFL cases. Depicted is the genomic locus of CIITA encompassing the pIII region and the first 3 kb of intron 1. For visualization purposes, only paired tFL cases and those which harbour at least two alterations are shown. Sequencing analyses revealed multiple genomic aberrations, including point mutations, deletions and insertions within the first 3 kb of intron 1.   55  Figure 2.15: AID hotspot targets are frequently mutated in tFL. Absolute frequency of mutated cytosine residues within the genomic context of two basepairs upstream in a) the T1 specimens, and b) the T2 specimens. Red bars indicate AID hot spot targets based on RGYW/WRCY motifs.    A similar analysis was then performed for the pFL and npFL cases (Figure 2.16). As many as 35 individual mutations were seen per case (B.4). In pFL, 56 transitions and 15 transversions occurred (ratio 3.7:1), whereas in npFL, 108 transitions and 55 transversions were observed (ratio 2:1). Again, similar to the distributions in tFL and PMBCL, these ratios are considerably skewed compared to the theoretically expected transition/transversion ratio (1:2). Furthermore, we found a significant enrichment in mutated cytosine residues within AID target motifs than one would expect by chance (χ2 test P < .001) and cytosine residues within AGC sequence motifs were commonly affected (Figure 2.17).   56  Figure 2.16: CIITA intron 1 alterations in early and late progressers. Depicted is the genomic locus of CIITA encompassing the pIII region and the first 3 kb of intron 1. Sequencing analyses revealed multiple genomic aberrations, including point mutations and deletions within the first 3 kb of intron 1.  57  Figure 2.17: AID hotspots targeted by mutations in pFL and npFL. Absolute frequency of mutated cytosine residues within the genomic context of two basepairs upstream in a) early progressers and b) late/no progressers. Red bars indicate AID hot spot targets based on the RGYW/WRCY motifs.  2.3.4 BAC capture Having CIITA firmly established as a recurrent translocation and gene fusion partner in lymphoid malignancies [172] accentuated the need for a comprehensive and detailed description of breakpoint anatomy, as well as the identity of the rearrangement partner genes. First, we explored the utility of BAC capture sequencing in a small pilot project, consisting of four cases with known FISH results for CIITA, PD-1 ligands (CD274 and PDCD1LG2) and TBL1XR1. BAC capture sequencing of FFPE tissue yielded a mean coverage depth of 82x across the capture space in the four enriched libraries; 16.7 % of reads were non-PCR duplicates that aligned to hg19/GRCh37. Following stringent filtering, a list of 16 genomic rearrangements in the four libraries was generated. In the extranodal DLBCL positive control, we observed a TBL1XR1-TP63 inversion and a BCL2-IGHV3-9 translocation, validating previously published FISH data [69]. A complete list with rearrangement partners, genomic breakpoints and putative translation of the other 14 rearrangement events are presented in Table 2.5 and are visualized in the circos plot (Figure 2.18).  .  58  Figure 2.18: BAC capture results for three PTL cases. Circos plot depicting the 20 regions of the BAC capture space spanning 7.45 Mb and the 11 structural genomic events observed in three libraries obtained from PTL archival FFPE tissue. The outer-most concentric track represents the chromosomes, the middle track denotes the capture space, and the inner-most track shows deletion events. The adjoining lines depict rearrangement partners. Events are colour-coded to reflect those which overlap between cases. Only chromosomes relevant to the capture space have been included and chromosomes 3, 9 and 16 have been magnified to improve resolution. The regions of the chromosomes that are highlighted in red are the centromeres. Reproduced with permission from [217].  In the context of this thesis, only alterations involving CIITA are discussed. The interested reader is referred to Twa et al. for more details [217]. In case B, we observed an interstitial deletion juxtaposing intron 15 of CIITA with intron 14 of SNX29 (16p13.13). This deletion results in a partial transcriptional loss of the C-terminal LRR domain and putatively produces an out-of-frame fusion leading to a premature stop. It is therefore expected that this may result in a dominant-negative CIITA protein [172]. In  59 case C, we observed biallelic deletions of CIITA, which likely cripple normal function of the protein. The 30 kb deletion on one allele includes both promoter regions (pIII and pIV), crucial for transcription in a B-cell context, while the deletion on the other allele likely results in an in-frame splice variant of exon 1 to exon 10 that lacks the functionally relevant acidic domain. Inexplicably, these events were not sizeable enough to explain the unbalanced signal pattern observed using FISH, suggesting a more complex rearrangement may be present. Extending our study of CIITA rearrangements in PTL, we performed FISH on a TMA including additional 85 specimens using the CIITA break-apart assay. In total, we observed a ba signal pattern in 8/82 (10 %) evaluable cases, suggesting that CIITA rearrangements are recurrent and may be responsible for reduced levels of MHC class II expression in a subset of PTLs [164]  60 Table 2.5: Structural genomic rearrangements in three PTL cases. Library Involved Genes Structural Rearrangement Type Genomic Location Exact Genomic Breakpoints Putative Translational Significance Sanger Sequencing Validated A CD274 Interstitial deletion Exon 7-3’intergenic chr9:5468110-chr9:5489373 IE; transcript stability Y PDCD1LG2 Interstitial deletion Intron 4-Exon 7 chr9:5554986-chr9:5570162 IE; protein solubility Y IGHG4-PDCD1LG2 Translocation 5’intergenic-3’intergenic chr14:106094861-chr9:5572111 IE Y* B CIITA-SNX29 Interstitial deletion Intron 15-Intron 14 chr16:11011017-chr16:12330239 DN; reduced MHCII Y* SMARCA2- CD274 Inversion 5’intergenic-Exon 7 chr9:1948958- chr9:5468076 IE; transcript stability N RFX3-CD274 Interstitial deletion Exon 16-Exon 7 chr9:3220442-chr9:5468461 IE of PDCD1LG2 Y C CIITA Interstitial deletion 5’intergenic-Intron 3 chr16:10960096-chr16:10990709 DE; reduced MHCII Y CIITA Interstitial deletion Intron 1-Intron 9 chr16:10988710-chr16:10997807 DN; reduced MHCII Y FOXP1-FLJ45248 Translocation Intron 11-3’intergenic chr3:71074272-chr8:103828413 IE; pro-apoptotic repression N* BCL6 Interstitial deletion 5’intergenic-Intron 1 chr3:187461229- chr3:187463676 IE; cell cycle progression N RMI2 Interstitial deletion Intron 1-Intron 2 chr16:11389010- chr16:11389154 DE; genomic instability N DE, decreased expression; DN, dominant-negative phenotype; IE, increased expression; Y, validated; N, not validated, due to exhaustion of genomic material; *, also observed by FISH. Reproduced from [217] with permission.  61 2.3.5 Capture sequencing The high technical demands of the BAC capture technique, as well as the enormous expenditure of time, forced us to explore alternative approaches for the decoding of translocation breakpoint anatomy. Another prerequisite that needed to be fulfilled was the suitability for using FFPE tissue. Targeted capture sequencing is ideally suited for interrogation of a circumscribed genomic region and is applicable to archival tissue specimens. Based on previous FISH results, in total 92 specimens were selected for capture sequencing. Those included 91 clinical cases (41 PMBCLs, 39 DLBCLs and 11 FLs) and a cHL-derived cell line (L1236). Eighty-five of the clinical specimens were FFPE tissues and six were FF cell suspensions. A.5 provides an overview of the specimens with their respective FISH pattern for the loci included in the capture space. Twenty-four specimens failed library construction, either due to insufficient DNA amounts (20 cases) or due to heavily fragmented DNA (four cases). The 68 successful libraries were from 35 PMBCLs, 31 DLBCLs, one FL and the cHL-derived cell line L1236. The results for the PDL loci CD274 and PDCD1LG2 have been previously published [214] and are not discussed herein. At first, quality assessment was performed to inform on the suitability of the sequencing data for further analysis.9 The mean coverage of each region captured represents the average sequencing depth (at a per-base basis) across all bases in the respective region. PCR duplicates were removed prior to the analysis. The mean coverage was uniform between the targeted regions and exceeded 600x for the CIITA and SOCS1 locus, respectively. However, a per-case analysis revealed a moderate degree of variability between individual specimens (Figure 2.19).                                                   9 Bioinformatic analyses were performed by Lauren Chong.  62  Figure 2.19: Oligocapture target region coverage depth. a) Mean coverage for the two target regions located on the short arm of chromosome 16, CIITA and SOCS1. b) Mean coverage for CIITA (upper panel) and SOCS1 (lower panel) on a per library basis, each column on the x-axis represents a successfully constructed library. Abbreviations: FFPE; formalin-fixed, paraffin-embedded; FF, fresh-frozen.  Structural variant detection was performed by integrating results from various prediction tools and different trimmed read lengths as described [214].10 Ultimately, the DELLY and deStruct tools were used because of their high concordance, comprehensive output format and high sensitivity. For the genomic region on chromosome 16, that was included in our capture design, the two SV detection tools resulted in a list of 145 predictions. To further narrow down the list to only include high-confidence SVs, we applied the following filter criteria: 1) read support; a cut-off of > 10 reads was applied; and 2) redundancy; predictions had to be obtained in at least two data sets. This reduced the list to 75 unique events, which are listed in detail in B.5. When we restricted our analysis to those predictions with effects on the CIITA gene locus, 53 events were identified. Table 2.6 provides a comprehensive overview on exact chromosomal breakpoint locations, SV type and functional impact for all CIITA-affecting predictions (including reciprocal events).                                                   10 These analyses were performed by Lauren Chong and are in detail explained in her MSc thesis. The methodology is described in sufficient detail in the supplement of [214].  63 Table 2.6: SV predictions for CIITA obtained by oligocapture sequencing. Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43030 DEL 16 10947070 CIITA 16 11116222 CLEC16A 38 4 169 kb deletion, breakpoints upstream of CIITA and in intron 11 of CLEC16A, complete loss of this CIITA allele Y A43031 INV 16 11013706 CIITA 16 11033187 DEXI 149 8 19 kb inversion, breakpoints in intron 16 of CIITA and intron 1 of DEXI, fuses CIITA exon 1-16 to DEXI exon 2, the latter is non-coding but a putative fusion protein can be derived (B.6) Y INV 16 11013709 CIITA 16 11033083 DEXI 110 7 reciprocal event, stop codon in exon 1 of DEXI, creates no fusion with CIITA exon 17-19  A43036 INV 16 10972119 CIITA 16 11349103 SOCS1 144 6 377 kb inversion, breakpoints in intron 1 of CIITA and exon 2 of SOCS1, likely disruptive for both genes Y INV 16 10972127 CIITA 16 11349114 SOCS1 65 4 reciprocal event  TRA 16 10972522 CIITA X 41548791 GPR34 68 6 t(X;16), breakpoints in CIITA intron 1 and GPR34 intron 1, putative fusion of CIITA exon 1 to GPR34 exon 2, 51 aa protein predicted (B.7), likely non-functional Y TRA 16 10972530 CIITA X 41548793 GPR34 70 2 reciprocal event, t(X;16), small ORFs, non-functional  DEL 16 10972770 CIITA 16 10973118 CIITA 112 4 347 bp deletion CIITA intron 1 N  64 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43037 DEL 16 10973706 CIITA 16 10972948 CIITA 252 6 757 bp deletion intron 1 CIITA Y A43043 DEL 16 10972316 CIITA 16 10972128 CIITA 94 4 187 bp deletion CIITA intron 1 Y A43049 INV 16 3056935 CLDN6 16 10966595 CIITA 21 8 8 Mb inversion, breakpoints upstream of CLDN6 and upstream of CIITA, results in dislocation of the green BAC probe but no structural damage to CIITA Y* A43050 DEL 16 10972395 CIITA 16 10973044 CIITA 108 6 648 bp deletion CIITA intron 1, FISH not explained but apparently small clone (5 %)  A43051 DEL 16 7638085 RBFOX1 16 10972040 CIITA 19 5 3.3 Mb deletion, breakpoints in intron 4 of RBFOX1 and intron 1 of CIITA, leads to fusion of RFBOX1 exon 4 to exon 2 of CIITA (B.8), resulting in a truncated protein  A43052 TRA 2 61108467 REL 16 10974031 CIITA 21 8 t(2;16), breakpoints in CIITA intron 1 and upstream of REL, fusion transcript possible (CIITA exon 1 to REL exon 2) Y TRA 2 61108477 REL 16 10974001 CIITA 13 7 reciprocal event  TRA 2 89159665 IGK 16 10972714 CIITA 15 6 t(2;16), breakpoints in CIITA intron 1 and centromeric on chromosome 2, close to IGK gene region Y DEL 16 10973286 CIITA 16 10972769 CIITA 13 2 516 bp deletion CIITA intron 1 N*  65 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43067 INV 16 10973601 CIITA 16 27326617 IL4R 39 6 16 Mb inversion, breakpoints in CIITA intron 1 and IL4R intron 1, same strand direction, therefore no fusion transcript upon inversion, likely disruptive N* INV 16 10973610 CIITA 16 27326640 IL4R 16 6 reciprocal event  A43068 DEL 16 10962704 CIITA 16 11310352 CLEC16A 54 8 348 kb deletion, deletes CIITA, DEXI and CLEC16A entirely N* A43069 TRA 16 10973113 CIITA 22 39854860 MGAT3 55 6 t(16;22), breakpoints in intron 1 of CIITA and intron 1 of MGAT3, different chromosome arms, same strand direction, therefore no fusion, likely disruptive Y TRA 16 10973113 CIITA 22 39854856 MGAT3 40 6 reciprocal event  A43070 DEL 16 10983031 CIITA 16 11812699 TXNDC11 41 8 830 kb deletion, breakpoints in CIITA intron 1 and TXNDC11 intron 5, different strand directions, therefore no fusion transcript Y TRA 1 2985148 PRDM16 16 10972750 CIITA 102 5 t(1:16), breakpoints in CIITA exon 1 and upstream of PRDM16, results in fusion of CIITA exon 1 to PRDM16 exon 2 Y TRA 1 2984655 PRDM16 16 10972919 CIITA 56 8 reciprocal event translocation CIITA intron 1 and upstream of PRDM16, no promoter swap, disruption of CIITA allele  A43071 DEL 16 10756488 TEKT5 16 11339356 SOCS1 21 7 417 kb deletion, deletes CIITA allele   66 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43072 DEL 16 10861924 NUBP1 16 10996431 CIITA 73 8 134 kb deletion, breakpoints in NUBP1 intron 9 and CIITA intron 1, creates in-frame fusion transcript NUBP1 exon 9 - CIITA exon 8 Y A43075 TRA 16 8762984 AICDA 12 10973366 CIITA 48 6 t(12;16), breakpoints in CIITA intron1 and AICDA intron 1, same chromosome arms, different strand direction, therefore no fusion transcript Y TRA 12 8764607 AICDA 16 10973178 CIITA 133 5 reciprocal event  A43076 DEL 16 10982313 CIITA 16 12374408 SNX29 20 6 1.4 Mb deletion, breakpoints in CIITA intron 1 and SNX29 intron 15, putative 29 aa fusion transcript (B.9) Y DUP 16 10972350 CIITA 16 10972662 CIITA 45 4 300 bp duplication intron 1 CIITA  A43077 DEL 16 10972806 CIITA 16 12062507 TNFRSF17 81 6 1 Mb deletion, breakpoints in CIITA intron 1 and downstream of TNFRSF17 Y A43078 TRA 8 128808741 PVT1 16 10972594 CIITA 90 4 t(8;16), breakpoints in CIITA intron 1 and PVT1 intron 1, different chromosome arms, same strand direction, therefore no fusion transcript Y TRA 8 128808716 PVT1 16 10972569 CIITA 39 3 reciprocal event  DEL 16 10972600 CIITA 16 10972919 CIITA 55 2 318 bp deletion CIITA intron 1 Y  67 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43079 TRA 10 46794179 CTSL1P5 16 10972823 CIITA 18 2 t(10;16)  N* TRA 10 48989246 GLUD1P7 16 10972800 CIITA 146 7 t(10;16)   DEL 16 10973892 CIITA 16 10973408 CIITA 189 6 483 bp deletion intron 1 CIITA N A43080 DEL 16 11348838 SOCS1 16 10973122 CIITA 195 8 375 kb deletion, breakpoints in intron 1 CIITA and SOCS1 exon 2 Y DEL 16 10972446 CIITA 16 10971699 CIITA 106 8 752 bp deletion intron 1 CIITA Y A43081 DEL 16 10973504 CIITA 16 10971906 CIITA 21 5 401 bp deletion intron 1 CIITA  DEL 16 10972143 CIITA 16 10971940 CIITA 12 4 202 bp deletion intron 1 CIITA  INV 16 10972733 CIITA 16 10973111 CIITA 17 3 367 bp inversion CIITA intron 1  INV 16 10973005 CIITA 16 10972714 CIITA 18 3 reciprocal event   A43082 DEL 16 10972338 CIITA 16 10972492 CIITA 28 2 153 bp deletion intron 1 CIITA  DEL 16 10972737 CIITA 16 10972561 CIITA 29 2 175 bp deletion intron 1 CIITA  DEL 16 10972598 CIITA 16 10972316 CIITA 20 2 281 bp deletion intron 1 CIITA  A43084 DEL 16 10972598 CIITA 16 10972316 CIITA 97 2 281 bp deletion intron 1 CIITA  A43093 DEL 16 10975142 CIITA 16 10973558 CIITA 80 8 1.5 kb deletion CIITA intron 1  INV 16 10971536 CIITA 16 10972727 CIITA 90 6 1.2 kb inversion CIITA intron 1  INV 16 10971870 CIITA 16 10972644 CIITA 83 3 773 bp inversion CIITA intron 1  DUP 16 10972945 CIITA 16 10973145 CIITA 35 2 199 bp duplication CIITA intron 1   68 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of CIITA oligocapture results Val A43095 DEL 16 10974070 CIITA 16 10972127 CIITA 20 6 2 kb deletion CIITA intron 1 N* DEL 16 10972312 CIITA 16 10972015 CIITA 76 5 296 bp deletion CIITA intron 1  INV 16 10973186 CIITA 16 10973372 CIITA 66 3 185 bp inversion CIITA intron 1 Y INV 16 10973169 CIITA 16 10973376 CIITA 37 3 reciprocal event  DEL 16 10974698 CIITA 16 10974425 CIITA 83 2 262 bp deletion CIITA intron 1  A43097 DEL 16 10971998 CIITA 16 10971586 CIITA 138 5 411 bp deletion CIITA intron 1 Y A43101 INV 16 10971827 CIITA 16 10973681 CIITA 52 6 1.8 kb inversion CIITA intron 1  INV 16 10971821 CIITA 16 10973687 CIITA 36 5 reciprocal event  A43110 DEL 16 11143548 CLEC16A 16 10810673 NUBP1 63 7 333 kb deletion of NUBP1, CIITA, DEXI and parts of CLEC16A Y A43115 DEL 16 10973158 CIITA 16 10972963 CIITA 141 5 194 bp deletion intron 1 CIITA Y INV 16 10971282 CIITA 16 10971688 CIITA 251 3 405 bp inversion in CIITA intron 1 N INV 16 10971301 CIITA 16 10971709 CIITA 236 3 reciprocal event  TRA 7 128309229 FAM71F2 16 10980174 CIITA 15 2 t(7:16) breakpoints in CIITA intron 1 and upstream of FAM71F2, different chromosome arms, same reading direction, no fusion N* A43117 DEL 16 10973536 CIITA 16 10972620 CIITA 349 6 915 bp deletion CIITA intron 1 Y Abbreviations: aa, amino acid; BAC, bacterial artificial chromosome; chr, chromosome; N, not validated; N*, not validated because of limited material or PCR failure; num, number; ORF, open reading frame; SV, structural variant; Val, validation; Y, validated; Y*, validated, but different mapping   69 Ten translocation events (in eight specimens) were identified, in nine of these, the breakpoint in CIITA mapped to the 1.5 kb hotspot region within intron 1, where previously identified breakpoints are located [172,232]. In concordance with our previous observations of a high frequency of large scale and small deletions in that region we found 31 such events in our oligocapture cohort. In addition, 10 inversions and two duplications were detected. A detailed analysis of the translocation events revealed that CIITA rearrangements involve multiple different partner genes. Most of these translocations do not result in the generation of fusion transcripts because of strand orientation and/or intergenic location of the second breakpoint. However, since most of the breakpoints in CIITA are located within the first 3 kb of CIITA intron 1, the majority result in functional abrogation of this gene. An overview of the translocation events and the putative partner genes is provided in the circos plot in Figure 2.20.  Figure 2.20: Circos plot depicting CIITA translocation events.For visualization purposes, only chromosomal regions involved in the predicted translocations are shown and the CIITA region is enlarged.  70 Beside the frequently occurring small deletions in CIITA intron 1 we also discovered eight large scale deletions. Of those, four resulted in the deletion of the entire CIITA gene locus whereas the remainder led to only a partial deletion. However, since the partial deletions involved either exon 1 or a large proportion of the gene, most of these events would lead to functional abrogation of CIITA. A schematic overview of these events is provided in Figure 2.21.   Figure 2.21: Intrachromosomal rearrangements in the chromosome 16 capture space. Only intrachromosomal events involving CIITA are depicted. The upper track shows the genomic coordinates according to hg19, as well as the location of the translocation breakpoints and the rearrangement partner genes. The panel underneath provides a schematic of the exon/intron structure of the three main genes included in the chromosome 16 capture space.  Of importance, the vast majority of intrachromosal structural variants involved the cluster breakpoint region in CIITA intron 1, which is confined to the first 3 kb of intron 1 and contains the inducible promoter IV with its alternative exon 1 (Figure 2.22).  71  Figure 2.22: Intrachromosomal rearrangements in CIITA intron 1. The upper track shows the genomic coordinates according to hg19, as well as the location of the translocation breakpoints and the rearrangement partner genes. The boundaries of CIITA intron 1 are indicated with vertical dashed lines.  2.4 Discussion Here, we performed a comprehensive analysis of genomic alterations in CIITA using NGS approaches and FISH across a spectrum of different B cell lymphoma subtypes. We established PMBCL as the entity with the highest frequency of CIITA alterations, including novel somatic CDS mutations, as well as deletions and rearrangements and, thereby, we substantially expanded on our previous findings of recurrent CIITA rearrangements in this disease [172]. Overall, CDS mutations together with structural alterations of the CIITA locus, encompassing deletions and rearrangements, were found in 71 % of PMBCL cases, thus establishing CIITA as one of the most frequently altered genes in this lymphoma entity [101]. The pattern of CIITA CDS aberrations, predominantly consisting of nonsense and frameshift mutations, as well as small deletions and chromosomal breakpoints, within a hot spot region in the first exon and intron, is indicative of loss of function. Moreover, our findings in PMBCL- 72 derived cell lines and in a proportion of primary clinical cases establish the pattern of CIITA biallelic hits. The pathogenic contribution of the clustered intron 1 deletions and point mutations still needs to be determined. The majority might be co-selected passenger mutations or more likely the result of AID-mediated aberrant SHM. However, as many of these alterations occur within the pIV region and frequently target transcription factor binding motifs and responsive elements [196] or even entirely delete this promoter and/or its associated alternative first exon, they might be of pathogenic relevance. It has been recently shown in splenic dendritic cells that distal regulatory elements - regions involved in the regulation of CIITA transcription - are able to switch to and interact with other downstream promoters if the pI promoter (from where CIITA is expressed in dendritic cells) is not accessible [233]. This promoter flexibility could be a potential “rescue mechanism” for B cells to maintain high expression levels of CIITA mRNA despite mutation-associated loss of pIII-driven transcripts. Thus, additional functional abrogation of pIV could be a selective advantage for malignant B cells. CIITA CDS mutations were less frequently observed in our cohort of de novo DLBCL (8.9 %) compared to PMBCL, but the frequency matches the range observed in previous studies [60,61,223,234]. Interestingly, we did not observe an association with a particular COO-subtype. Unfortunately, the design of the sequencing panel and the platform used did not allow the analysis of alterations in the non-coding space, in particular intron 1, in this cohort. However, similar to the rare observation of chromosomal rearrangements in DLBCL (with the exception of PTL), large scale deletions within the first 3 kb of intron 1 could not be detected in a small set of DLBCL cases analyzed by conventional PCR [172,217]. In our highly selected FL cohort, which was enriched for cases with subsequent transformation and progression, we discovered a high frequency of abnormal signal patterns in the FISH study with as much as 36.8 % abnormal cases among the transformed FL specimens (T2 specimens, mostly DLBCL morphology), followed by the respective T1 samples (29.9 %). Specimens within the pFL and npFL cohorts showed structural chromosomal alterations to a much lesser extent with 15.2 % and 5.4 %, respectively, indicating that these alterations might be a surrogate for an imminent  73 transformation event, when detectable at initial diagnosis. Of note, CDS mutations were not enriched among the FLs which eventually transformed. The analysis of intron 1 mutations in FL showed frequent SNVs and rarely small deletions or insertions. The clustering of SNVs, deletions and chromosomal breakpoints in the first exon and intron, as well as a significant association with AID target motifs, raises the likelihood that CIITA is aberrantly targeted by the AID-mediated SHM process. As it has been shown in previous studies for a variety of genes characteristically expressed in germinal center B cells (e.g. BCL6, MYC, PAX5, PIM1, RHOH, CD95 and SOCS1), mutations in these loci can occur as a side-product of the B cell maturation and antibody diversification process and might play a crucial role in the development of malignant lymphomas of (post)germinal-center B cell origin [41–43,235–237]. Following these studies, genome-wide screens and targeted sequencing approaches in mice and humans have identified a large number of other genes affected by aberrant SHM in both non-malignant and malignant contexts [46,95,98,234,238]. As a result, CIITA is considered to be a target of aberrant SHM in DLBCL and FL. We show in our study that AID protein expression is detectable in a substantial fraction of PMBCL tumors. This is in line with previous reports in the literature where the authors observed AID mRNA and protein expression but were limited by analyzing only a small number of tissue samples [239,240]. By using BAC capture and oligocapture sequencing approaches, we were able to provide a comprehensive characterization of breakpoint anatomy and rearrangement partner genes. We further substantiated our notion of a cluster breakpoint region in intron 1 of CIITA, identified novel translocations and revealed that CIITA rearrangements involve multiple different partner genes. In addition, we identified frequent intrachromosomal SV, most of them resulting in functional abrogation of CIITA.  74 Chapter 3: Functional and Clinical Relevance of CIITA Alterations  3.1 Introduction Over 20 years ago, CIITA was identified as the master transcriptional regulator of MHC class II expression based on studies conducted in patients with a severe immunodeficiency syndrome, namely type II bare lymphocyte syndrome (BLS) [189]. Individuals affected by this disease harbour somatic mutations which ultimately result in the loss of MHC class II expression and as an ultimate consequence patients suffer from multiple infections due to an inadequate adaptive immune response. Further studies uncovered the complex regulation of MHC class II expression, involving several co-factors assembled in a multi-protein complex known as the MHC enhanceosome [188,241]. Expression of CIITA is driven by different promoters which regulate transcription in a cell-type and context-specific manner. Four promoters have been described in the literature and the respective CIITA transcripts are characterized by a different first exon [196]. Of importance for the regulation of CIITA transcription in humans are: 1) pI, the promoter used by dendritic cells; 2) pIII, the dominant driver of CIITA-expression in B cells; and 3) pIV, the INF- inducible promoter. Significant amounts of pII-derived transcripts could not be detected in human tissues or cell lines, hence the biological relevance of this promoter seems to be rather limited [196]. MHC are glycoproteins on the cell surface and are integral and indispensable for the normal function of the adaptive immune system. MHC class II is predominantly involved in the display of exogenous antigens to CD4+ T cells and expression is mainly restricted to APCs [122]. B cells are potent antigen presenters and are, therefore, characterized by a rather constitutive expression of MHC class II, which can be enhanced by stimulatory signals, such as IL-4 [176,177]. However, the expression of MHC class II within the B cell lineage is restricted and strictly regulated. It is absent in early pro-B cells and then increases in subsequent developmental stages. The expression maximum is reached in germinal centre B cells, whereas terminally differentiated plasma cells are largely negative [178,179]. The loss of surface expression of MHC class II molecules has been described across different lymphoma entities and has been linked to reduced immunogenicity of  75 tumour cells. While some studies clearly established an association of MHC class II loss with inferior survival in cHL, PMBCL and DLBCL [133,134,215,242,243], others could not demonstrate an impact of MHC class II deficiency on patient outcomes [64,244]. Here we thought to assess the impact of somatic CIITA alterations, as identified in Chapter 2, on MHC class II expression in in vitro cell line models as well as primary tissue specimens. Furthermore, we aimed at linking CIITA mutations and MHC class II loss of expression with the abundance of T cell subsets in the tumour microenvironment and patient outcomes.  3.2 Materials and methods 3.2.1 Flow cytometry Flow cytometry was used to quantify HLA-DR surface expression in cell lines. Briefly, 0.5 x 106 cells were washed once in cold PBS containing 1 % FBS and then incubated for 30 minutes on ice with PerCP/Cy5.5 anti-human HLA-DR (BioLegend, 0.25 µg/test). PerCP/Cy5.5 Mouse IgG2a  was used as an isotype control. After washing and resuspension, samples were acquired on a FACSCalibur (BD Biosciences). All analyses were done using FlowJo software (version 10.0.7r2, FlowJo, LLC).  3.2.2 Quantitative reverse transcriptase (qRT)-PCR  All qRT-PCR assays were performed on a CFX384 real-time PCR system (Bio-Rad). The efficiencies of target and reference amplifications were verified to be equal, therefore expression levels were quantified using the ∆∆CT method. A TaqMan RNA-to-CTTM 1-Step Kit and TaqMan® gene expression assays were used to detect mRNA expression levels of CIITA (Hs00932860_m1) and HLA-DR (Hs00734212_m1). GAPDH expression (GAPDH (DQ) Oligo Mix, Cat. # 4332649, Life Technologies) served as an internal control. Each specimen was assayed in triplicate using 1 ng of total RNA per 10 l reaction and results are shown relative to the expression in either germinal centre B cells or cells transduced with the empty vector control. CIITA pIII and pIV specific mRNA transcripts were assayed by a two-step SYBR Green assay (Power SYBR Green PCR Master Mix, Life Technologies). cDNA was  76 synthesized from 1 g total RNA using random hexamers and SuperScript III Reverse Transcriptase (Life Technologies). cDNA equivalent to 5 ng RNA was used for each 10 l reaction and expression levels were normalized to GAPDH.  3.2.3 Western blotting  Total cell lysates were prepared using RIPA lysis and extraction buffer (Thermo Scientific). Cultured cell lines were washed once with PBS and then incubated for 15 minutes on ice in RIPA buffer supplemented with a protease inhibitor cocktail (Sigma-Aldrich). Twenty-five g of protein lysate was resolved on a 4-12 % NuPAGE Novex Bis-Tris gradient gel (Invitrogen) and transferred to a nitrocellulose membrane by wet transfer. Blots were probed with an anti-CIITA antibody (clone 7-1H, Abcam, ab49989) at a 1:1000 dilution. β-actin (A5441; Sigma-Aldrich) served as an internal loading control (dilution 1:10000). Horseradish peroxidase (HRP) conjugated anti-mouse IgG (W402B, Promega) was used to visualize bands using the enhanced chemiluminescence (ECL) system (Amersham) on a Chemidoc digital imager (Bio-Rad).  3.2.4 Retroviral transduction Retroviral transductions were performed as previously described [245]. Briefly, the NLPHL-derived cell line DEV was at first transduced with a feline endogenous virus expressing the ecotropic retroviral receptor (mCAT, obtained as supernatant from the stable producer line FLYRD18/mCAT-IRES-Bleo; gift from Dr. Louis Staudt, NIH, Bethesda, MD). Secondly, following a 14-day selection period with Zeocin, cells were infected with an ecotropic retrovirus, expressing the bacterial tetracycline repressor (TetR). Cells expressing TetR were positively selected with Blasticidin over two weeks. Wildtype (wt) or mutant CIITA cDNAs were amplified using Phusion DNA polymerase (NEB) and subsequently cloned into the doxycycline-inducible pRetroCMV/TO/GFP vector. The mutant alleles discovered in clinical cases were generated from the vector containing the wt allele by using the QuikChange II XL site-directed mutagenesis kit (Agilent) according to the manufacturer’s instructions. The NUBP1-CIITA fusion was cloned using the Gibson Assembly Master Mix (NEB). Inserts were verified using Sanger sequencing.  77 A mixture of CIITA-containing plasmid DNA, the mutant ecotropic envelope-expressing plasmid pHIT/EA6x3 and gag-pol expressing plasmid pHIT60 were co-transfected in HEK293T cells using the Lipofectamine 2000 Reagent (Invitrogen). Two days after transfection, retroviral supernatants were collected to infect the engineered target cells in the presence of 8 g/ml polybrene (Sigma) in a single spin infection (90 minutes at 2500 rpm and 25ºC) and two days after transduction puromycin was added to select for stable integration over 4-6 days. Gene expression was induced by adding 20 ng/ml doxycycline (Sigma) to the media for 48 hours.  3.2.5 RNA-Seq11 RNA-Seq was performed as previously described [59] using RNA extracted from DEV cells expressing either the empty pRETRO vector, wt CIITA or the p.1131STOP>R*35 mutant. In brief, approximately two million cells were harvested after 48h treatment with 20 ng/ml doxycyclin and RNA was extracted using the RNeasy Mini Kit (Qiagen). RNA was then submitted to the Genome Sciences Centre for further processing, library construction and sequencing. Polyadenylated (polyA+) messenger RNA (mRNA) was purified, ethanol–precipitated, and used to synthesize cDNA using the Maxima H Minus First Strand cDNA Synthesis kit (Thermo-Fisher) and random hexamer primers. The second strand cDNA was synthesized following the Superscript cDNA synthesis protocol by replacing the dTTP with dUTP in the dNTP mix, allowing the second strand to be digested using UNG (Uracil-N-Glycosylase, Life Technologies) and thus achieving strand specificity. cDNA was fragmented by sonication using a Covaris LE220 (Covaris). Libraries with a desired size range were purified and diluted to 8 nM, and then pooled at five per lane and sequenced on the HiSeq 2500 platform, generating 75 bp paired-end reads. Sequencing files were aligned using the STAR aligner (version 2.5.2a) and differentially expressed genes were reported using DESeq2 (version 1.12.2) based on the following criteria: 1) genes with an absolute log2 fold change (FC) of ≥ 1.0 were considered as being differentially expressed; and 2) false discovery rate (FDR)-adjusted P-value (q-value) < .05 was considered significant (Benjamini-Hochberg method).                                                  11 This section is modified from a method draft provided by Dr. Andrew Mungall.  78 3.2.6 Immunohistochemistry  IHC was performed on 4 m sections from FFPE tissue samples arranged on previously constructed TMAs [65,104,172,219] or on whole tissue sections in the case where a particular sample was not evaluable or represented on the TMA. Following antigen retrieval, sections were stained with primary antibodies recognizing HLA-DR/DP/DQ (dilution 1:1000, clone CR3/43, Dako, M0775), CD4 (neat, clone SP35, Ventana 790-4423) and CD8 (dilution 1:50, clone C8/144B, Dako, M710301) followed by routine protocols for automated IHC on the Ventana Benchmark XT (Ventana Medical Systems). MHC class II protein expression was assessed semi-quantitatively as follows: 0 = negative, 1 = membranous staining, 2 = cytoplasmic staining, and the predominant pattern based on evaluation of duplicate TMA cores was assigned to a case. Representative images were taken using a Nikon Eclipse 80i microscope equipped with a Nikon DS-Ri1 camera and NIS Elements imaging software (Version D3.10). Immunohistochemically stained slides for the T cell markers CD4 and CD8 were scanned with an Aperio ScanScope XT at 20x magnification and analyzed utilizing the Aperio ImageScope viewer (Version 12.1.0; Aperio Technologies). Only cores and areas containing tumour were scored using the Positive Pixel Count algorithm with optimized color saturation thresholds. Any staining was considered positive and the number of positive pixels was divided by the total pixel count. Whenever applicable, scores from both cores were averaged and multiplied by 100 to obtain the percentage of positive pixels.  3.2.7 Statistical and survival analysis Fisher’s exact test and 2 test were used to compare categorical variables. McNemar’s test was used when comparing categorical variables between paired specimens. The Mann-Whitney U test was applied to compare two groups. Spearman correlation was used to test the association between two continuous variables. Survival analysis were performed using the Kaplan-Meier method and differences between groups were assessed by applying the log-rank test. Overall survival (OS) was defined as time from diagnosis to death from any cause; disease- 79 specific survival (DSS) as time from diagnosis to death from lymphoma or acute treatment-related toxicity; progression-free survival (PFS) as time from diagnosis to disease progression/relapse or death from any cause and time to progression (TTP) as time from diagnosis to disease progression/relapse or death from lymphoma or acute treatment-related toxicity. Time to transformation (TTT) was calculated as the time between diagnosis of FL and histological confirmation of large cell transformation. Patients, who did not experience an event, were censored at the time of last follow-up. P-values < .05 were considered being significant.  3.3 Results 3.3.1 CIITA and HLA-DR expression in PMBCL- and NLPHL-derived cell lines Based on our observations of frequent biallelic genomic alterations of CIITA in PMBCL-derived cell lines and in DEV and given the functional importance of CIITA in the transcriptional regulation of MHC class II genes, we analyzed the expression of CIITA and HLA-DR by qRT-PCR and flow cytometry and compared it to sorted germinal centre B cells and an EBV-transformed lymphoblastoid B cell line (LCL), respectively. In Karpas1106P and in DEV, CIITA mRNA expression was not detectable by qRT-PCR, as a consequence of biallelic rearrangements in these cell lines (see section 2.3.1.1 for details). CIITA expression levels were higher in U2940 compared to germinal centre B cells but markedly reduced in MedB-1 (Figure 3.1).     80  Figure 3.1: CIITA mRNA expression in PMBCL- and NLPHL-derived cell lines.  Shown is the relative expression of CIITA mRNA in four lymphoma cell lines compared to germinal centre B cells (GCB).  We subsequently analyzed HLA-DR protein expression by flow cytometry (Figure 3.2). Karpas1106P and DEV had no detectable surface HLA-DR expression, whereas U2940 showed an intermediate expression level compared to the LCL cell line used as a control. Interestingly, the third PMBCL cell line MedB-1 showed reduced, but remarkably heterogeneous HLA-DR expression. To explore to which extend CIITA expression can be induced upon IFN  stimulation in PMBCL cell lines we performed a transcript specific qRT-PCR. As expected, Karpas1106P showed no expression because of the biallelic deletion (see Figure 2.3). The stimulation with IFN  resulted in a slight increase of the pIII transcript (1.4-fold for MedB-1 and 1.3-fold for U2940). Expression of the pIV transcript increased by 2.3-fold for MedB-1 and 5-fold for U2940. These data are in agreement with the published literature confirming a preferential effect of IFN  on pIV in B cells [179]. However, no changes in HLA-DR expression were observed, which is expected, given the CIITA alterations in these cell lines.   81  Figure 3.2: HLA-DR expression in PMBCL- and NLPHL-derived cell lines. HLA-DR expression in PMBCL- and NLPHL-derived cell lines was assessed by flow cytometry. Expression levels are compared to LCL, an EBV-transformed lymphoblastoid cell line, which is depicted by the dashed grey line.   3.3.2 Functional implications of CIITA mutants in in vitro cell line models To study the functional consequences of CIITA mutations, we generated stably transduced cell lines expressing either wt or mutant CIITA. The NLPHL-derived cell line DEV was selected for retroviral transduction experiments because it completely lacks surface HLA-DR expression due to biallelic inactivation of CIITA (Figure 2.6) and proved to be transducable with the retroviral vector system as described in section 3.2.4. The ectopic reintroduction of the CIITA wt allele into DEV was able to restore CIITA mRNA and protein expression, measured by qRT-PCR and Western blot, and resulted in HLA-DR surface expression by flow cytometry (Figure 3.3 a-g) comparable to levels observed in LCL (see Figure 3.2 for comparison). Next, we evaluated the  82 effects of several CIITA mutants, including the NUBP1-CIITA fusion, which we described in the PMBCL-derived cell lines U2940 and MedB-1 (Figure 2.2 and Figure 2.4), as well as two missense mutations observed in primary patient-derived cases. The hg19 chr16: g.11017158C>T mutation, resulting in a loss of the original stop codon p.1131STOP>R*35, showed CIITA mRNA expression comparable to the wt (Figure 3.3 a), but was not capable of re-establishing HLA-DR expression (Figure 3.3 d, e and g). The NUBP1-CIITA fusion only partially restored HLA-DR levels and therefore explains the intermediate expression levels seen in U2940 (Figure 3.2). Interestingly, the two different mutant alleles which occur in trans-configuration in MedB-1 showed approximately equal amounts of CIITA mRNA and protein (Figure 3.3 a and b), but revealed different effects on HLA-DR expression when independently transduced. Specifically, the p.71Asp>Asn mutation restored HLA-DR surface protein levels, whereas the p.636Thr>Met allele resulted in a broad range of expression similar to the parental cell line (Figure 3.3 d, e and Figure 3.2). The p.715Cys>Tyr mutant could only marginally restore HLA-DR expression, however, with the p.11Ser>Pro allele high levels of HLA-DR expression were observed (Figure 3.3 a-g). We noted that, despite similar mRNA expression levels for CIITA, protein expression was lower in cells transduced with wt CIITA or the p.1131STOP>R*35 mutant compared to others. We speculate that this may originate from differences in protein stability.  83   84 Figure 3.3: Ectopic expression of CIITA wildtype and mutants in DEV. a) No significant differences in CIITA mRNA expression were observed upon retroviral transduction of wt and mutant CIITA (number of independent experiments, n = 3). b) CIITA protein expression is restored upon transduction with wt and mutant CIITA. As expected, the p.STOP1131R*35 mutant and the NUBP1-CIITA fusion protein have a slightly higher molecular weight compared to the wt protein. c, d) Wt CIITA restores HLA-DR mRNA (c; number of independent experiments, n = 3) and surface protein expression (d; representative data from 3 experiments) whereas the p.STOP1131R*35 mutant does not. The missense variants discovered in MedB-1 and two clinical samples have different impact on HLA-DR expression. e) Density plots for GFP and HLA-DR expression in transduced DEV cells. f, g) Geometric mean of the fluorescence intensity (FI) for HLA-DR (f; n = 3) and GFP (g; n = 3). Mean + SD are shown for all bar graphs. Abbreviations: wt, wildtype.  3.3.3 RNA-Seq analysis To further evaluate the functional impact of CIITA deficiency on a more global level, we performed RNA-Seq experiments to determine genome-wide changes in transcriptional activity. We compared DEV cells transduced with the empty retroviral vector backbone to cells transduced with the vector containing wt CIITA. Surprisingly, we found only 26 significant differentially expressed genes (Figure 3.4), of which 12 genes met our criteria (absolute log2 FC of ≥ 1.0, adjusted P-value < .05, Table 3.1).  Figure 3.4: Top differentially expressed genes in DEV cells expressing wt CIITA. The waterfall plot shows all significant differentially expressed genes (FDR < .05). The dashed line indicates the threshold of an absolute log2 FC of ≥ 1.0.  85 Table 3.1: Differentially expressed genes. gene_name baseMean log2FoldChange pvalue padj gene annotation HLA-DPB1 760.9832721 5.928838653 1.29E-207 1.93E-203 MHC class II HLA-DRA 5930.725532 4.866696771 4.95E-138 3.72E-134 MHC class II HLA-DOA 126.9200534 3.496263144 1.57E-72 7.84E-69 MHC class II HLA-DMA 683.2489663 2.481786444 4.57E-58 1.72E-54 MHC class II CD74 76631.21505 2.099627182 3.26E-56 9.80E-53 MHC class II (invariant chain) HLA-DMB 201.4500995 2.064319728 1.36E-37 3.40E-34 MHC class II CIITA 7354.75111 2.309386328 1.72E-35 3.69E-32  CADM3 17.69970813 1.76395559 1.00E-27 1.88E-24 cell adhesion molecule 3, member of the nectin family, cytoplasmic region interacts with EPB41L1, DLG3, MPP6 and CASK  PARVG 29.91164828 1.754111704 4.11E-23 6.86E-20 parvin gamma, focal adhesion molecule, plays a role in the regulation of cell adhesion and cytoskeleton organization SESN3 117.1944716 1.375663471 1.33E-12 2.00E-09 Sestrin 3, member of the sestrin family of stress-induced proteins, reduces levels of intracellular ROS. The protein is required for normal regulation of blood glucose and plays a role in lipid storage. BTN2A2 824.6334586 1.331249587 2.81E-12 3.84E-09 encodes a type I receptor glycoprotein involved in lipid, fatty-acid and sterol metabolism HLA-DOB 39.35284458 1.204205428 2.67E-10 3.34E-07 MHC class II  86  Beside CIITA itself, there were seven more MHC class II complex genes, among those the classical MHC class II complex members, HLA-DRA and HLA-DPB1, as well as the invariant chain CD74, and the chaperones HLA-DM and HLA-DO. Similar results were obtained when comparing DEV CIITA wt versus DEV cells transduced with the vector containing the STOP-lost mutant as discovered in U2940 (see section 2.3.1.1 and Figure 2.4), underscoring that this mutation indeed abrogates CIITA function.  3.3.4 Correlative studies in primary lymphoma cases 3.3.4.1 PMBCL In order to inform on the functional implications of CIITA genomic alterations, we performed and evaluated MHC class II (HLA-DR/DP/DQ) protein expression by IHC on the aforementioned TMAs (2.2.1.2.1). Only cases with complete information on CIITA FISH ba-status and MHC class II protein expression (n = 103) were analyzed further, and mutational data (although only available for 44 cases from the sequencing cohort) were also included. Cases which were scored as ba-positive by FISH and/or harboured CIITA CDS mutations were significantly more often negative for MHC class II compared to wt cases (2-test: P = .02). Figure 3.5 shows two representative cases from the sequencing cohort.  Figure 3.5: MHC class II expression in primary PMBCL cases. Shown are two representative PMBCL cases; a) case #7 and b) case #33 from the sequencing cohort. Case #7 shows strong membranous MHC class II expression in the tumour cell population, whereas in case #33 the neoplastic cells are negative. Small, reactive B cells and macrophages are stained as an internal control. Original magnification: x400.  87 To explore the potential impact of CIITA genetic aberrations or absent MHC class II surface expression on the microenvironment composition and in particular T cell subsets we compared the abundance of CD4- and CD8-positive T cells between the CIITA wt and mutated group, as well as between MHC class II positive and negative cases (Figure 3.6). No significant differences in CD4+ and CD8+ T cells were observed when comparing CIITA wt versus mutant/ba-positive cases (Mann-Whitney test: P = .58 and P = .63, respectively). When the same type of comparisons was performed with regard to MHC class II surface expression on the malignant cell population, a significantly higher amount of CD4-expressing T cells was present in MHC class II positive cases (Mann-Whitney test: P = .008). A trend was also seen in the CD8-positive subset, although this did not quite reach statistical significance (Mann-Whitney test: P = .06). For this cohort of cases the expression of MHC class II had been previously recorded as percentage of positive tumour cells in 10% increments and a histological score was generated, which also considered the staining intensity [232]. Based on these data we were able to perform a Spearman correlation and observed a weak to moderate correlation of MHC class II protein expression and the abundance of CD4- and CD8-positive T cells, respectively (Spearman r = .224, P = .027 for CD4; r = .246, P = .015 for CD8).  88  Figure 3.6: Abundance of T cell subsets in primary PMBCL cases. Scatter plots for the percentage of CD4- and CD8-positive pixels, respectively. Coloured horizontal lines show the median and the error bars represent the 95 % confidence interval. Abbreviations: ba, break-apart; mut, mutant; neg, negative; ns, not significant; pos, positive; wt, wildtype. P-values: * < .05; ** < .01; *** < .005.  Since it was previously reported, that CIITA genomic rearrangements were associated with impaired DSS in PMBCL [172], we next thought to perform outcome analyses in this slightly larger cohort and with the additional information obtained from the sequencing studies. No significant differences in survival (OS, DSS, PFS and TTP) were observed between CIITA wt and mutant cases (Figure 3.7). Furthermore, although the outcomes for patients with MHC class II negative tumours were less favourable compared to those with MHC class II positive lymphoma cells, significant differences  89 could not be observed (Figure 3.8). Similar results were seen when restricting the analyses to only include patients treated with rituximab-containing regimens.  Figure 3.7: Survival of PMBCL patients with CIITA wt or mutant tumours. Shown are KM-plots for a) OS, b) PFS, c) DSS, and d) TTP.  90  Figure 3.8: Survival of PMBCL patients according to MHC class II expression status. Shown are KM-plots for a) OS, b) PFS, c) DSS, and d) TTP.  3.3.4.2 DLBCL Of 347 cases, 316 were evaluable for both CIITA mutational status and MHC class II expression. Cases harbouring CIITA CDS mutations were significantly more often negative for MHC class II compared to wt cases (2-test: P = .002). Next, we compared the abundance of CD4- and CD8-positive T cells between the CIITA wt and mutated group, as well as between MHC class II positive and negative cases (Figure 3.9). No significant differences in the abundance of CD4+ and CD8+ T cells, as inferred from the positive pixel count data, were observed when comparing CIITA wt versus mutant cases (Mann-Whitney test: P = .18 and P = .66, respectively; Figure 3.10). When allocating cases to groups based on MHC class II surface expression in the malignant cell population, a significantly higher amount of CD4-expressing T cells was present in MHC class II positive cases (Mann-Whitney test: P =  91 .03). However, the abundance of CD8-positive T lymphocytes was not significantly different between MHC class II positive and negative cases (Mann-Whitney test: P = .45; Figure 3.10).  Figure 3.9: MHC class II expression and T cell abundance in primary DLBCL cases. Panels a-c show a CIITA wt case with strong membranous MHC class II expression (a) and moderate numbers of tumour infiltrating CD4- (b) and CD8-positive (c) T cells. The case depicted in panels d-f harbours a CIITA CDS mutation with subsequent loss of MHC class II expression (d) and, in comparison to the wt case, fewer CD4+ (e) and CD8+ T cells (f). Measurement bars equal 25 m; original magnification: x400.  92  Figure 3.10: Abundance of T cell subsets in primary DLBCL cases. Scatter plots for the percentage of CD4- and CD8-positive pixels, respectively. Coloured horizontal lines show the median and the error bars represent the 95 % confidence interval. Abbreviations: mut, mutant; neg, negative; ns, not significant; pos, positive; wt, wildtype. P-values: * < .05; ** < .01; *** < .005  We then performed outcome analyses in this large, uniformly treated DLBCL cohort. No significant differences in OS, DSS, and TTP were observed between CIITA wt and mutant cases, but PFS was significantly impaired in patients with CIITA mutated DLBCL (Figure 3.11). No differences in survival were seen between MHC class II positive and negative cases (Figure 3.12).   93  Figure 3.11: Survival of DLBCL patients according to CIITA mutational status. Shown are KM-plots for a) OS, b) PFS, c) DSS, and d) TTP.   94  Figure 3.12: Survival of DLBCL patients according to MHC class II surface expression. Shown are KM-plots for a) OS, b) PFS, c) DSS, and d) TTP.  3.3.4.3 FL 3.3.4.3.1 tFL cohort One hundred and four T1 biopsies were evaluable for both CIITA mutational/ba status and MHC class II expression. The Fisher’s exact test revealed no significant difference in terms of MHC class II expression between CIITA altered and wt cases (P = .49). Similar results were obtained for the T2 specimens (130 evaluable cases; Fisher’s exact test: P = .84). Since we have observed an enrichment of CIITA genetic alterations, specifically structural chromosomal aberrations, in the T2 biopsies compared to their respective T1 specimen (2.3.3.1), we wanted to assess if the T2 specimens were more frequently negative for MHC class II (surface) expression. For 113 tFL pairs we had MHC class II protein expression data available, 85 were MHC class II positive at both timepoints,  95 seven pairs were concordantly negative, and in three cases tumour cells expressed MHC class II only in the T2 biopsy. In contrast, 18 cases became MHC class II negative at the T2 timepoint (McNemar test, P = .002; Figure 3.13). Similar results were obtained when considering surface MHC class II expression (McNemar test, P = .001).  Figure 3.13: MHC class II expression and T cell abundance in tFL. Shown are histological images of two lymphoma biopsies from a patient, who experienced transformation of an FL (panels a-c) into a DLBCL (panels d-f). The initial FL shows tumour cells which are positive for MHC class II (a), whereas the transformed lymphoma specimen is negative (d). In addition, the abundance of CD4+ (b, e) and CD8+ T cells (c, f) is higher in the indolent lymphoma compared to the high-grade lesion. Measurement bars equal 50 m; original magnification: x200.  96 Similar to the studies performed in the PMBCL (3.3.4.1) and DLBCL cohort (3.3.4.2), we compared the abundance of CD4- and CD8-positive T cells between the CIITA wt and mutated group, as well as between MHC class II positive and negative cases. No significant differences in CD4- and CD8-expressing T cells were observed when comparing CIITA wt versus mutant/ba-positive T1 cases (Mann-Whitney test: P = .2 and P = .99, respectively; Figure 3.14), as well as when comparing T2 biopsies with and without genomic CIITA alterations (Mann-Whitney test: P = .51 and P = .76, respectively; Figure 3.14).  Figure 3.14: Abundance of T cell subsets in tFL according to CIITA mutation status. Scatter plots for the percentage of CD4- and CD8-positive pixels. Panel a) and b) show the percentages of CD4- and CD8-positive pixel counts for the T1 specimens, whereas the T2 specimens are shown in panel c) and d).Coloured horizontal lines show the median and the error bars represent the 95 % confidence interval. Abbreviations: ba, break-apart; mut, mutant; neg, negative; ns, not significant; pos, positive; wt, wildtype. P-values: * < .05; ** < .01; *** < .005.   97 When the same type of comparison was performed with regards to MHC class II surface expression on the malignant cell population (Figure 3.15), a significantly higher amount of CD4-expressing T cells was present in MHC class II positive T1 cases (Mann-Whitney test: P = .0003) but not in the T2 specimens (Mann-Whitney test: P = .35). However, the abundance of CD8-positive T lymphocytes was not significantly different between MHC class II positive and negative T1 cases (Mann-Whitney test: P = .07), but was significant in the T2 biopsies (Mann-Whitney test: P = .04).   Figure 3.15: Abundance of T cell subsets in tFL according to MHC II expression. Scatter plots for the percentage of CD4- and CD8-positive pixels. Panel a) and b) show the percentages of CD4- and CD8-positive pixel counts for the T1 specimens, whereas the T2 specimens are shown in panel c) and d).Coloured horizontal lines show the median and the error bars represent the 95 % confidence interval. Abbreviations: ba, break-apart; mut, mutant; neg, negative; ns, not significant; pos, positive; wt, wildtype. P-values: * < .05; ** < .01; *** < .005.   98 We also performed outcome analyses in this cohort and were primarily interested in the impact of CIITA alterations and MHC class II expression on TTT. No significant differences in TTT were observed between CIITA wt and mutant cases, but surprisingly, patients, whose tumours were positive for surface MHC class II, transformed significantly earlier compared to the ones with MHC class II negative tumours (Mann-Whitney test: P = .02; Figure 3.16).   Figure 3.16: TTT analysis in patients with tFL. TTT in patients with tFL comparing CIITA wt and mutant cases (a) and MHC class II positive and negative cases (b). P-values: * < .05; ** < .01; *** < .005.  No significant differences in OS were seen between CIITA wt and mutant cases or MHC class II positive and negative cases (Figure 3.17).    Figure 3.17: OS in patients with tFL. OS in patients with tFL comparing CIITA wt and mutant cases (a) and MHC class II positive and negative cases (b).    99  3.3.4.3.2 pFL/npFL cohort One hundred five biopsies were evaluable for both, CIITA mutational/ba status and MHC class II expression. As in the tFL cohort, there was no significant difference in terms of MHC class II expression status between CIITA altered and wt cases (Fisher’s exact test, P = .68). The association of CIITA mutation status with the abundance of CD4- and CD8-positive T cells (Figure 3.18) revealed no significant differences in CD4 and CD8 T cells between CIITA wt and mutant cases (Mann-Whitney test: P = .61 and P = .55, respectively). When the same type of comparison was performed with regard to MHC class II surface expression (Figure 3.18), again no significant differences were observed (Mann-Whitney test: P = .08 and P = .59, respectively).  100  Figure 3.18: Abundance of T cell subsets in primary pFL/npFL cases. Scatter plots for the percentage of CD4- and CD8-positive pixels, respectively. Coloured horizontal lines show the median and the error bars represent the 95 % confidence interval. Abbreviations: ba, break-apart; mut, mutant; neg, negative; ns, not significant; pos, positive; wt, wildtype. P-values: * < .05; ** < .01; *** < .005.  Although there seems to be a clear trend towards impaired OS and PFS in patients with CIITA mutated tumours (Figure 3.19 panel a and b), similar to what was observed in DLBCL (see section 3.3.4.2), the relatively low numbers preclude us from drawing meaningful conclusions, and further analysis in larger cohorts would be needed to address this question. Differences in survival between MHC class II positive and negative cases were not seen (Figure 3.19 panel c and d).  101  Figure 3.19: Outcomes in patients with pFL and npFL. OS and PFS in patients with pFL/npFL comparing CIITA wt and mutant cases (a, b) and MHC class II positive and negative cases (c, d).  3.4 Discussion In Chapter 2 we have described CIITA CDS mutations and structural variants as frequent genetic alterations in PMBCL, DLBCL and FL. Since CIITA is known as the master transcriptional regulator of MHC class II, the impaired function would be expected to lead to a decrease in MHC class II expression, which has been linked to reduced tumour cell immunogenicity [215,246]. By performing functional rescue experiments in a cell line model, we were able to demonstrate that at least some of the CIITA missense mutants resulted in a functionally deficient protein incapable of inducing HLA-DR surface expression in vitro. On the other hand, some altered alleles obviously retain their capability to activate MHC class II transcription. However, some mutations, like the p.636Thr>Met discovered in MedB-1, might lead to a dominant-negative  102 phenotype, a phenomenon previously seen by others in functional selection studies [206,247] and demonstrated by us for the CIITA-FLJ27352 gene fusion [172]. In primary PMBCL and DLBCL cases, CIITA genomic alterations were significantly associated with loss of MHC class II protein expression, underscoring the role of CIITA as the master transcriptional regulator of MHC class II. Interestingly, no such correlation was seen in the FL cohort. In fact, a considerable proportion of cases was characterized by a remarkably heterogeneous MHC class II expression pattern, in the sense that often completely negative areas were admixed with positive follicles or tumour cells with a predominant Golgi-pattern. Future studies would need to explore the underlying genetic/epigenetic mechanisms. Our correlative studies, however, showed that at least in some instances lower numbers of CD4+ and/or CD8+ T cells (as inferred by the percentage of positive pixels, quantified by semi-automated image analysis) were present in the microenvironment of tumour biopsies with low MHC class II expression, whereas no such association was seen with respect to CIITA mutation status. This can be explained by our observations in the in vitro model, where we were able to demonstrate that some missense mutations do not impair the functional properties of the CIITA protein. Future studies would need to explore changes in T cell proliferation and consequences for their functionality. Given the semi-quantitative nature of IHC and its low dynamic range, it is difficult to elucidate what the exact consequences of a quantitative reduction might be with respect to tumour-microenvironment interaction. However, our data, together with HLA-DR reduction in CIITA-mutated PMBCL cell lines, suggest that CIITA mutations may contribute to the immune escape phenomena in these lymphoma subtypes. Since CIITA requires co-factors to induce MHC class II transcription, it is conceivable that mutations of such co-factors may contribute to immune escape. For instance, in a recently published study, Green et al. [90] have shown that CREBBP mutant FL samples exhibit lower MHC class II transcript and protein levels. Further studies would be needed to explore how CREBBP mutations might be linked to genomic alterations occurring in CIITA. Whereas our data demonstrated the functional relevance and clonal selection of CIITA rearrangements and CDS mutations, the pathogenic contribution of the clustered  103 intron 1 deletions and point mutations still needs to be determined. Of note, intron 1 variants were not correlated with either CIITA or MHC class II expression in our PMBCL sequencing cohort, suggesting that the majority might be co-selected passenger mutations, or more likely the result of AID-mediated aberrant SHM. In summary, CIITA and the subsequent MHC class II abrogation describes an ancillary mechanism that is critically involved in the establishment of an immune privilege phenotype. The identification of acquired immune-privilege properties harbours the potential to develop and pursue targeted treatment approaches, such as PD1- and PDL blockade [248] or cell based vaccination [249], in these molecularly characterized subgroups of B cell lymphoma.   104 Chapter 4: Conclusion 4.1 Summary of research findings The main objective of the research presented in this thesis was to obtain a better understanding of the heterogeneity, molecular mechanisms and functional consequences of CIITA gene alterations in B cell malignancies. Furthermore, we aimed to inform on the implications for tumour microenvironment composition and patient outcomes in various types of B cell lymphomas. The premise that genetic alterations are frequent across a spectrum of B cell lymphomas constitutes the cornerstone of our hypothesis. To address this, in Chapter 2, we performed targeted sequencing of the CIITA locus in large cohorts of PMBCL, DLBCL and (transformed/progressed) FL. FISH was performed on TMAs to broaden our knowledge about the prevalence of CIITA structural variants in various B-NHL subtypes [172]. In PMBCL, we discovered that over 70 % of cases harbour at least one genetic hit, establishing CIITA as one of the most frequently altered genes in this particular entity. The pattern of CIITA aberrations in PMBCL, predominantly consisting of nonsense and frameshift CDS mutations, as well as small deletions and chromosomal breakpoints within a hot spot region confined to the first exon and intron, is indicative of loss of function. Moreover, the pattern of CIITA bi-allelic hits in PMBCL-derived cell lines and in a proportion of primary clinical cases, emphasizes a potential tumour suppressor role for CIITA in this context. CIITA CDS mutations were less frequently observed in our cohort of de novo DLBCL (8.9 %) compared to PMBCL, but the frequency matches the range observed in previous studies [60,61,223,234]. We did not observe an association with a particular COO-subtype, as determined by gene expression profiling [65]. Interestingly, most of the mutations were missense mutations and clustered in regions encoding functionally important protein domains, such as the conserved NACHT-domain (the GTP-binding domain of CIITA) and the LRR repeats, important for dimerization and nuclear import of the protein. In our FL cohort, which was enriched for cases with subsequent transformation and progression, we discovered a high frequency of abnormal signal patterns in our FISH study with as much as 36.8 % abnormal cases among the transformed FL  105 specimens (T2 timepoint), followed by the respective preceding FL samples (T1 timepoint, 29.9 %). Specimens within the pFL and npFL cohorts showed structural chromosomal alterations to a much lesser extent with 15.2 % and 5.4 %, respectively, indicating that these alterations might be a surrogate for an imminent transformation event, when detectable at initial diagnosis. Of note, CDS alterations were not enriched among the FLs which eventually transformed and, similar to the DLBCL cohort, largely consisted of missense mutations affecting crucial protein domains. The analysis of intron 1 mutations in FL showed frequent SNVs, similar to PMBCL, but rarely small deletions or insertions. To inform comprehensively on novel CIITA rearrangements, partner genes and breakpoint anatomy, we applied targeted capture sequencing on 92 lymphoma specimens with known FISH ba-status. We further substantiated our previous finding of a well-defined cluster breakpoint region in intron 1 of CIITA and identified 10 novel CIITA translocations involving multiple different partner genes, as well as intra-chromosomal structural alterations. Furthermore, we provided evidence that oligocapture sequencing can be successfully performed using FFPE-derived DNA and complements FISH in detecting structural variants [214]. We further hypothesized that the genetic alterations in CIITA provide the foundation for the development of an ‘immune privilege’ phenotype as a consequence of loss of MHC class II expression and altered tumour microenvironment composition. By using immunohistochemistry for the exploration of MHC class II expression patterns and automated imaging analysis for the enumeration of T cell subsets, we were able to demonstrate that CIITA mutations and structural alterations were associated with a reduction of MHC class II expression in PMBCL and DLBCL, but not in FL. Furthermore, although in most instances the numbers of CD4- and CD8-positive T cells were reduced in CIITA-mutated cases compared to wt cases, statistically significant results were only seen when comparisons were centred on surface MHC class II expression. Lastly, our hypothesis, that CIITA alterations and MHC class II expression loss impair patient outcomes was largely disproved. Although the outcomes in CIITA-mutated cases were often inferior, a statistically significant result could only be obtained for PFS in the DLBCL cohort.  106 In conclusion, our findings can be summarized in the following model. Structural genomic alterations, i.e. rearrangements, not only result in the functional abrogation of CIITA but also in some cases in overexpression of the respective partner genes such as PD-1 ligands. Therefore, these alterations might present as “double-hits” leading to reduced immunogenicity and the enforcement of an exhausted T cell phenotype. Coding sequence mutations and intron 1 alterations may cause functional impairment of CIITA, resulting in reduced levels of MHC class II expression.  Figure 4.1: Functional impact of CIITA alterations in malignant lymphomas.   4.2 Limitations In the correlative studies performed in this thesis, we largely ignore the fact that - in most instances - tumours represent an aggregation of diverse cell populations with differences in their genetic make-up. This intratumoural heterogeneity is reflected in the existence of subclones, which are exposed to evolutionary pressures, exerted by the tumour niche, the host immune system and therapy [250,251]. In fact, this becomes  107 clearly evident in our FL cohort, where the allelic frequencies of CIITA mutations or the percentage of cells with abnormal FISH-signal patterns were often lower in the initial FL biopsy compared to their respective transformed lymphoma. This likely explains the overt phenotypic heterogeneity with regards to MHC class II protein expression in these specimens. In addition, malignant tumours represent complex ecosystems and phenotypic traits are often the result of an interaction between multiple genetic alterations, epigenetic regulation and various activated or perturbed signaling pathways [109,110]. Since CIITA requires co-factors to induce MHC class II transcription, it is conceivable that mutations of such co-factors may contribute to immune escape. For instance, in a recently published study, Green et al. [90] have shown that CREBBP mutant FL samples exhibit lower MHC class II transcript and protein levels. CREBBP is one of the most frequently mutated genes in FL and DLBCL [59,252] and further studies would need to explore how CREBBP mutations might be linked to genomic alterations occurring in CIITA and how this interplay would determine MHC class II expression. In addition, FOXP1 has recently been proposed to alter MHC class II expression in the ABC-like subtype of DLBCL [253]. Deregulation of pathways such as NFB and JAK-STAT can result in disturbed expression and abundance of chemokines and cytokines, which in turn might influence expression of CIITA and MHC class II. NFB and JAK-STAT pathways are constitutively active in DLBCL, PMBCL and, to a lesser extent in FL and likely result in a deregulated micromilieu. The impact on MHC class II expression remains largely unknown. Although in a different cellular context (microglia), it has been demonstrated that IFN, IL-3, IL-4 and TNF can induce CIITA, whereas TGF, IL-10 and IL-1b are believed to cause downregulation of CIITA and MHC class II [254,255]. We observed a correlation of MHC class II expression with increased abundance of CD4+ T cells (and in rare instances also with CD8-positive T cells), however, the exact nature and functional phenotype of this population (i.e. Th1, Th2, Th17, regulatory T cells, follicular T helper cells) is unknown. This question would be best addressed using novel technology platforms such as CyTOF, which enables unprecedented simultaneous interrogation of over 40 markers on a single cell level in one experiment. This could be combined with single cell RNA-Seq technologies to further increase the  108 granularity of information. In addition, functional studies in vitro, using co-culture experiments with (HLA-matched) T cells, could provide information on changes in T cell activation status and proliferation.  4.3 Potential applications A variety of acquired genomic alterations and perturbed signaling pathways can contribute to an immune escape phenotype in malignant lymphoma cells by effectively subverting the ability of the host immune system to target and eliminate tumour cells [111]. Novel therapeutic approaches aiming at a rectification of the deranged anti-tumour immune response have been developed over the past decades to capitalize on the increasing knowledge about immune evasion strategies and mechanisms employed by cancer cells. The compelling success of novel cellular-based therapies, such as CAR-T cells, or immune checkpoint blockade implies a profound knowledge of immune escape mechanisms and synergistic relationships among different pathways to enable the development of predictive biomarkers that can precisely inform on a patient’s response to treatment. The potential of determining the genetic basis for clinical response to immune checkpoint inhibitors has been recently demonstrated in patients with malignant melanoma [256]. Preliminary results from phase 1 and 2 clinical trials in lymphoma patients provide evidence for efficacy and safety [248,257,258], but more data are imperatively needed in order to develop reliable prognostic and predictive biomarkers, applicable in routine clinical practice, and to select patients upfront who will benefit from these new therapeutic approaches. The assessment of MHC deficiency (and underlying genetic mechanisms) will potentially become of greater importance as the field of cancer treatment moves increasingly towards broad implementation of immunotherapeutic strategies for the treatment of cancer patients. A recent study conducted by Johnson et al. [259] has demonstrated the importance of MHC class II expression in patients with malignant melanomas for the response to immune checkpoint blockade with the anti-PD-1 antibodies Nivolumab and Pembrolizumab or anti-PDL1 antibodies. Tumour cells positive for MHC class II (cut-off > 5 %) were more likely to respond to PD-1-blockade, likely due to the contribution of a higher immune cell infiltrate, and had an increased  109 survival probability. Interestingly, expression of PDL1 itself was relatively rare in those tumours and did not correlate with response to the PD-1/PDL1-targeting approach. The assessment and characterization of defects in antigen presentation can, in theory, help to identify patients which may or may not respond to these immunotherapies. Moreover, with methods available to correct such deficiencies, the response rates could potentially be improved. An alternative idea is to enhance MHC class II expression for therapeutic purposes in treatment of cancer patients. This approach is largely based on “vaccination” approaches and previous studies have shown that transfection of tumour cells with MHC class II can result in sufficient presentation of cytosolic, tumour-derived endogenous antigens (“neo-antigenes”) to CD4+ T cells [260,261]. Therefore, enforced expression of MHC class II in tumour cells poses an opportunity to enhance anti-tumour immune response and tumour rejection [262].  4.4 Ongoing work We have demonstrated that CIITA structural variants occur frequently in tFL and that these genomic alterations might be an indicator of an impending high-grade transformation when detected at initial diagnosis. We also showed that targeted capture sequencing and FISH are complementary techniques to fully capture these alterations, as well as to provide base pair resolution and information on rearrangement partner genes. We will, therefore, apply this technology to our FL cohort, to inform on the exact nature of structural aberrations and to generate hypotheses on functional implications. Based on prior work of our group in collaboration with Dr. Oliver Weigert and his team (LMU Munich, Germany) on the m7-FLIPI [93], we noticed that the transcription factor FOXP1 is transcriptionally down-regulated in EZH2 and MEF2B mutated FL cases. By using FOXP1 IHC on TMAs from a retrospective series of 107 patients treated with R-CVP at the BCCA, we could demonstrate that FOXP1 protein expression correlated with adverse outcome. We are currently validating the prognostic value of FOXP1 in several TMAs comprised of tissue biopsies from patients enrolled in clinical trials of the German Low Grade Study Group (GLSG). In addition, we will explore this potential biomarker in both, the transformed and progressed FL cohorts. This is not only  110 of interest in terms of outcome prediction, but also because of the potential link between FOXP1 and MHC class II expression, as recently demonstrated in DLBCL [253]. In this study, Brown et al. showed that expression of FOXP1 was inversely correlated with mRNA expression levels of several MHC class II genes. Moreover, knock-down of FOXP1 resulted in upregulation of HLA-DRA and CD74. We therefore aim to evaluate if FOXP1 is directly or indirectly involved in regulating expression of CIITA and thereby MHC class II.  4.5 Open questions and future directions 4.5.1 Epigenetic control of MHC II expression  It is well known, that CIITA is involved in the recruitment of chromatin-/histone-modifiers and therefore in the epigenetic control and modulation of MHC class II expression. Of importance for maximal expression of MHC class II is the interaction of the N-terminus of CIITA with CREBBP-p300 [263,264]. As a result, CIITA can be perceived as a bridging molecule, facilitating the interaction of DNA-bound transcription factors, histone acetyltransferases (leading to the acetylation of histones H3 and H4) and the transcription machinery. It is suggested, that the assembly of the DNA-binding proteins RFX, CREB and NF-Y leads to a basal level of H3 and H4 acetylation, and therefore may result in MHC class II expression, even without the presence of CIITA, if exceeding a certain threshold [265]. Furthermore, it has been proposed that MHC class II can be expressed in a CIITA-independent manner in immune-privileged sites, endothelial cells and dendritic cells of CIITA knock-out mice, and that this process facilitates the presentation of cytosolic rather than endolysosomal peptides [266–268]. It remains to be shown to which extent these processes occur in normal or malignant B cells in the context of CIITA-deficiency. In addition, it needs to be addressed if CIITA and CREBBP mutations occur frequently together or if they are mutually exclusive in primary FL and DLBCL cases.  Another mechanism of epigenetic regulation of HLA-DRA and CIITA (in particular of the pIV promoter of CIITA) is the introduction of suppressive histone modifications such a H3K27me3, conferred by EZH2, a histone methyltransferase [269,270]. EZH2 is commonly mutated in DLBCL and FL [70] and further molecular studies need to  111 elucidate the role of this gene for CIITA and MHC class II expression in B cell malignancies.  4.5.2 Post-translational modification and degradation of CIITA and MHC class II The N-terminal portion of the CIITA pIII isoform is known to facilitate interaction with cofactors and components of the transcription machinery, and it is also believed to play a role in recruitment to the HLA-DRA promoter [174,175,180]. Recent studies provided evidence, that this same protein domain is also involved in the rapid degradation of CIITA via the ubiquitination pathway [271,272]. Interestingly, Beaulieu et al. demonstrated that SNVs or short deletions within the acidic domain led to increased protein stability accompanied by a loss or reduction of the transactivation potential [272]. Since some of the CDS mutations described in this thesis were found to affect the acidic domain, further studies would be needed to elucidate the consequences for protein degradation and the interaction of CIITA with the basal transcription machinery. As outlined in section 1.3.2, some APCs, such as macrophages and dendritic cells, but also B cells, can upregulate MHC class II surface expression upon stimulation. Conversely, Thibodeau et al. showed that IL-10 induces transcription of MARCH1, a gene encoding a membrane-associated ubiquitin ligase, therefore leading to internalization and degradation of MHC class II protein [273]. To which extend these mechanisms occur in B cell malignancies is largely unexplored.  4.5.3 Interplay between MHC and the PD-1/PDL axis A recent study provided some evidence that MHC class II expression might be of importance for the response of patients to immune checkpoint blockade [259]. This study was performed in patients with malignant melanomas, a tumour widely considered as being highly immunogenic. We aim on assessing the interplay between MHC and the PD-1/PDL axis in in vitro and syngeneic in vivo mouse models of malignant lymphomas. Specifically, we plan on generating MHC class I/MHC class II deficient cell lines using the CRISPR/Cas9 genome editing tool combined with ectopic overexpression of PDL1 or PDL2, respectively. In vitro co-culture experiments with HLA-matched CD4- or CD8- 112 positive T cells, as well as in vivo mouse models, will be used to measure differences in response to immune checkpoint blockade with Nivolumab.  4.6 Final conclusion Herein, we described genomic rearrangements and coding sequence mutations in CIITA as being frequent across a spectrum of B cell lymphoma subtypes. We demonstrated that these genetic alterations can result in diminished MHC class II expression and subsequently in an altered microenvironment composition with a lower abundance of CD4- and CD8-positive T cells in the tumour microenvironment. We identified that at least some of the genetic alterations are likely a byproduct of AID-mediated somatic hypermutation, as evidenced by the co-occurrence of mutations in the non-coding region of CIITA intron 1. In addition, we described novel translocations involving a broad spectrum of rearrangement partner genes and intra-chromosomal structural variants. 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Immunol. 2008, 38:1225–1230.   143 Appendices Appendix A  - Supplementary methods A.1 Assays and methodology applied to the PMBCL sequencing cohort Case # FISH CIITA ba WGS WTS TSCA Sanger exon coverage pIII Intron1 PCR Intron1 sequencing Intron1 subcloning 1 x   x x x x x x 2 x     x x   3 x   x  x x   4 x   x  x x   5 x   x  x x   6 x   x x x x   7 x   x x x x x x 8 x  x   x x x x 9 x x x x  x x x x 10 x   x x x x x x 11 x    ND x x x x 12 x  x   x x   13 x   x  x x   14 x   x x x x   15 x   x  x x   16 x    x x x x x 17 x   x  x x x x 18 x   x x x x x x 19 x x x x x x x x x 20 ND  x  x x x x x 21 x    x x x x  22 x   x  x x   23 x   x  x x x  24 x  x   x x x x 25 x   x  x x x x 26 x    x x x x x 27 x   x  x x x  28 x   x  x x x  29 x    x x x x x 30 x    x x x x x 31 x   x x x x x  32 x   x  x x x x 33 x   x  x x   34 x    x x x   35 x    x x x   36 x   x  x x x  37 x    x x x x  38 x   x  x x x  39 x   x  x x x  40 x   x x x x x   144 Case # FISH CIITA ba WGS WTS TSCA Sanger exon coverage pIII Intron1 PCR Intron1 sequencing Intron1 subcloning 41 x   x  x x   42 x  x   x x x  43 NE   x  x x x  44 NE   x  x x x  45 ND   x  x x   Abbreviations: ba, break-apart; WGS, whole genome sequencing; WTS, whole transcriptome sequencing (RNA-Seq); TSCA, TrueSeq custom amplicon; ND, not done; NE, not evaluable 145  A.2 TSCA oligos for the PMBCL cohort Amplicon name ULSO sequence DLSO sequence comment CIITA + CIITA_UserDefined (5254060)_5553285 TGGGAGTCCTGGAAGACATACTGGTC CTCAAGAAATGTTTGTTGAATGAATGAATG exon 4 +5 CIITA + CIITA_UserDefined (5254060)_5553286 CTTCAGTTAGACCTTGTTGATTGACTGC CCTGCATTTCCTGCCTTGTTCCCT exon 4 +5 CIITA + CIITA_UserDefined (5254060)_5553287 TGAAAGCCCAAGGTGAGTCTCTATTG CAAACTTACTGAAAATGTCCTTGCTCAG exon 4 +5 CIITA + CIITA_UserDefined (5254060)_5553288 ATTCATTGATGGGCAGTCAGACCC GGCAGAAAAGTCAGAAAAGACGTGAG exon 4 +5 CIITA + CIITA_UserDefined (5254060)_5553289 TTTTAAAGGGCCTCCCAACCAGACAGGAC AACTTCTGCTGGCATCTCCATAC exon 4 +5 CIITA + CIITA_UserDefined (5254061)_5553290 TCTCGGCTCCCACGTCGCAGATGCAG GGGGGAAGGAATCAATATTTATTGCACAAC exon 17 + 18 CIITA + CIITA_UserDefined (5254061)_5553291 CACAGGCCTCCAATCCCTCCCCCT GGGCGGTGGGTGGCTCAGCCCGGGGTGGGA exon 17 + 18 CIITA + CIITA_UserDefined (5254061)_5553292 GCAAGAGAAACTCACCTTGGGGC ACACTCACTCCATCACCCGGAGGGAC exon 17 + 18 CIITA + CIITA_UserDefined (5254061)_5553293 GAGCTGGGGAGTCCCAAGGGCCA GAGAACAACTCACTCCCCAGGCGTGT exon 17 + 18 CIITA_Exon (8620300)_5553342 AAGTGTCAAGTGAATGAGCAATGTGAA ATGGAGAAGCAGGTGCCAGATTTAGG exon 10 CIITA_Exon (8620301)_5553343 AAGCACACAGCCTCATCACTAGCCTC GTTTCTGAACACCCTCTAATTTTACCAC exon 1 CIITA_Exon (8620301)_5553344 TTTGCATGTTGGCTTAGCTTGGC CCTGGCTGGGATTCCTACACAAT exon 1  146 Amplicon name ULSO sequence DLSO sequence comment CIITA_Exon (8620301)_5553345 CAGAATGGTTTCTCTGTTTATCTGGAATGG AGCAGCTCCCGGAGTCTGGCAGC exon 1 CIITA_Exon (8620302)_5553346 ATGCACCATCCCCATCAGACTTGGGCC AAAACATGTGATCAGCTGCCCCAGGG exon 6 CIITA_Exon (8620303)_5553347 ACTTTGGGGGCCCGATTCAGCAGGAA AATCAGATGGGGGCCATCAGCTAGCG exon 15 CIITA_Exon (8620304)_5553348 AGCAGTCGCTCACTGGTCTCACTAG TTGTCATCTTCTCAGCCCTGGCTGC exon 7 CIITA_Exon (8620304)_5553349 CCCCCACTGTGGTGACTGGCAGTCT GAGAGAGTGGGCTTTCTCCCTCTT exon 7 CIITA_Exon (8620305)_5553350 ACTGGGAGGGGGTACTTGGCTGGCCT GAGAGAAGAGAGTAGAACTTCCAAAGGAA exon 9 CIITA_Exon (8620305)_5553351 TATTCTCACACCACTCTCCACCCCCAAT CTGCCCAGCATGCCTGAACCTG exon 9 CIITA_Exon (8620305)_5553352 ATGACCTGTTGTCCCTACAGGCAGCTTT TCAGTGGCTGATGGAGCGAAGGGGC exon 9 CIITA_Exon (8620318)_5553353 TGCAGGGACTCCCACAGCGCCA AGCTCAACCTCTACCTTTCCCAGAAA exon 12 CIITA_Exon (8620318)_5553354 CACCGTGCCTGGGTCTGAGGCCCT CCTGAAGGATGTGGAAGACCTGGGAAA exon 12 CIITA_Exon (8620318)_5553355 ATGGGGTGTCCCAGAGGACAGGGGGC ACTTGGCTTTGAAAGGCTCGATG exon 12 CIITA_Exon (8620312)_5553356 GGAGATTCAGGCAGCTCAACGAG TCCCTAAGAGCAGTAGCTGTTTCTGT exon 8 CIITA_Exon (8620312)_5553357 TCTCTTGCAGTGCCTTTCTCCAGTT GGCCTGGCTCCCCGACCACCTCT exon 8 CIITA_Exon (8620313)_5553358 TGCGGGCTCGGCACCATACGTG ACATCTGTTCCCCACACAGTTTTT exon 11 CIITA_Exon (8620313)_5553359 CGCCCCTGGCCTTTGCAGAGCC TGGAGCGGGAACTGGCCACCCCGGACT exon 11 CIITA_Exon (8620313)_5553360 ACAGCAATCACTCGTGTCTCACGCG TGGCCTGCACCAGATCCACCTCC exon 11 CIITA_Exon (8620313)_5553361 GCCCAAGGAGGCCTGGCTGAGGTGCTGTT GCCGGCTTCCCCAGTACGACTTTGTCTT exon 11 CIITA_Exon (8620313)_5553362 GCCACGAGTGGCTGTGGGCCCA AGCCCAATAGCTCTTGCCCTGACC exon 11  147 Amplicon name ULSO sequence DLSO sequence comment CIITA_Exon (8620313)_5553363 TGCTTGAACCGTCCGGGGGATGCCTAT TGGAAGCGCAAGATGGCTTCCT exon 11 CIITA_Exon (8620313)_5553364 GGTGCAACCTCGGAGCAGCTTC AACGCGGTCAGGTCTCTTCAAGATGT exon 11 CIITA_Exon (8620313)_5553365 CGGACCGGCACCGGCGGAGCCCTGCTCCCT GAGCTGTCCGGCTTCTCCATGGA exon 11 CIITA_Exon (8620313)_5553366 TGAGAAGAAGTGGCCGGTCCCGGAGG TCAGGCTCTGGACCAGGCGGCCCCGG exon 11 CIITA_Exon (8620313)_5553367 GCGCTACTTTGAGAGCTCAGGGATGA TGGGGAGGACGCCAAGCTGCCCTCCA exon 11 CIITA_Exon (8620313)_5553368 TACTTTGATGTCTGCGGCCCAGCTCC CAGGGCCTCTGAGAGCTGGCAC exon 11 CIITA_Exon (8620313)_5553369 GGCAGAGCTGGCCAAGCTGGCCT GCCTTCCCCAGCTTCCTCCTGCAAT exon 11 CIITA_Exon (8620313)_5553370 TGGCACGCCCTCCAGCCAGTTGT AGCTCGGACTCTGCGGCCCGCGGTGGG exon 11 CIITA_Exon (8620313)_5553371 TTGACCCCAAGGAAGAAGAGGCCCTAT TGCTTGCGAGGTACCTGAAGCG exon 11 CIITA_Exon (8620313)_5553372 AGAAAAGAGAGGCGGCCGGGGAGCT TTCTGCTTCCTGTCCACCGAGGCA exon 11 CIITA_Exon (8620313)_5553373 TGGAATTTGGCAGCACGTGGTACA CCCCTCTGGATTGGGGAGCCTC exon 11 CIITA_Exon (8620313)_5553374 CGGCTGCTCTGCATACTAAAAGAGA AAATGCCAGTGCTGCGGAGGTCCAG exon 11 CIITA_Exon (8620314)_5553375 ATGTGGGTTCCCTGCGCTCTGCAGCCCC ACACAGTGAGGGGGAGGGCTCAGGAC exon 16 CIITA_Exon (8620315)_5553376 CAAGATGTGGTTCATTCCGCAGC GGAGGAGCCAGGAGAGGGGGTT exon 20 CIITA_Exon (8620316)_5553377 TACAAGCCCAGCTAATGCTGCAGGGGA AATGTTAGGGGGAGCAGGCACTGCTGT exon 13 CIITA_Exon (8620306)_5553378 TGGAGGTCTTACCCTTGCTCTTT TCTGGGTGCAGTGCTGTGATCATA exon 14 CIITA_Exon (8620308)_5553379 TGTTAAGAAGCTCCAGGTAGCCAC CTGGGGATGAGAGGAGTGAATAAAAGC exon 2 CIITA_Exon (8620308)_5553380 CACCATGGAGTTGGGGCCCCTAGAA ATCCCCCACCCCTCAGCTTGCTGTAGA exon 2  148 Amplicon name ULSO sequence DLSO sequence comment CIITA_Exon (8620309)_5553381 CAGCAAAGAACTCTTGCCCTTGATTGT AGTCCCTTGGATGAAGAAGGAAATTTC exon 3 CIITA_Exon (8620310)_5553382 ACAAGGACACTGCCCCCAACCCACTG GGGGATGGGACTCAGAGCCAGG exon 19 CIITA pIV exon1_UserDefined (8658714)_5553515 TTGAGCAAGTAGCTGACAGTCTCGGA AGCTCGTCCGCTGGTCATCCTAC pIV exon 1   A.3 Primer sets Primer name Primer sequence (5'-3') comment -21M13F TGTAAAACGACGGCCAGT sequencing primer and tag -27M13R CAGGAAACAGCTATGAC sequencing primer and tag CIITA pIII F1 CAAGGGTACCATATTTGGGTTA promoter 3 region + exon 1 CIITA pIII R1 GACTCCTGTTCCCATCCTCA promoter 3 region + exon 1 CIITA F5 GTCCTACCTGTCAGAGCCCCAAG Intron 1 CIITA I1R1 TGGAGTCACCTGGGATAGATGGT Intron 1 CIITA ISEQ F1 AAGGCAGCATGGCAGCTA sequencing primer Intron 1 CIITA ISEQ F2 CCTAGGGCCAGCATCAGA sequencing primer Intron 1 CIITA ISEQ F2.5 GCTCCCTGCAACTCAGGA sequencing primer Intron 1 CIITA ISEQ F3 GGCTCCGAGACTGTCAGC  sequencing primer Intron 1 CIITA ISEQ R1 CTTTCCCACAGGTCCATTG sequencing primer Intron 1 CIITA ISEQ R2 CCGTGAAAGTGGCAAACC sequencing primer Intron 1 CIITA ISEQ R3 GAGTCGTTGCGGGGATG sequencing primer Intron 1 CIITA ISEQ R4 ATTCCGGCTTTCCTGGAC  sequencing primer Intron 1 CIITAe1F1 CCTGGCTGGGATTCCTACAC CDS exon 1 CIITA e1R1 CTCTGACAGGTAGGACCCAGCA CDS exon 1 CIITA_e2e3F1 TCAATTTTCTGCCTCTTTCCA CDS exon 2+3 CIITA_e2e3R1          GACGTGGCTCATGATGAATG CDS exon 2+3  149 Primer name Primer sequence (5'-3') comment CIITA_e4e5F1          CACACAGTGGGCCTTCAGTT CDS exon 4+5 CIITA_e4e5R1          CAGGCTTTGGAGTCAAGGAA CDS exon 4+5 CIITA_e6e7F1 GGCCGTATAGCCTGCTAGAGT CDS exon 6+7 CIITA_e6e7R1          CCTGACAGTCCCTGCCTTAG CDS exon 6+7 CIITA_e8F1            AATCGCAAACACAGGTGCTA CDS exon 8 CIITA_e8R1          GCAGTCAGGTAGGAGGGAGA CDS exon 8 CIITA_e9F1            GGTGACCCAAGTGCATTTCT CDS exon 9 CIITA_e9R1           GCCTCGATCCTGCTTCTAGT CDS exon 9 CIITA_e10F1          GGGGTAACCCTCACCCTAAA CDS exon 10 CIITA_e10R1          GATATGGGCTTCCATCTCCA CDS exon 10 CIITA_e11F1          GTAAATGATGGTGGCAGTGCT CDS exon 11 CIITA e11F2 GCTCTGAGTGGCGAAATCA CDS exon 11 CIITA_e11R1          CTTCCTTGGGGTCAATGCTA CDS exon 11 CIITA_e11R2          GCACCAAGACCGCAGTTAAT CDS exon 11 CIITA_e13F1          GGTAAGGGCTCAGTGACAGC CDS exon 13 CIITA_e13R1          GGTGGTACAAGCCCAGCTAA CDS exon 13 CIITA_e14F1           GAATGAGGGGCTGTGACTGT CDS exon 14 CIITA_e14R1          GAGGCTGCAGTGAGCTATGA CDS exon 14 CIITA_e15F1          GTCAGATGGCCCCAGGAC CDS exon 15 CIITA_e15R1          ACAGCGAGCCCTTGTCTAAA CDS exon 15 CIITA_e16F1          CATGCAAGTTTGGTCCTGAG CDS exon 16 CIITA_e16R1          GCTGTGGTGATTGCTTCTAGG CDS exon 16 CIITA_e17e18F1        AGTGGGACCAGGCTTTTTCT CDS exon 17+18 CIITA_e17e18R1       TGGGGAGTGAGTTGTTCTCC CDS exon 17+18 CIITA_e19F1          CGCCCTCTCTCCTCTAACC CDS exon 19 CIITA_e19R1          AAGGACACTGCCCCCAAC CDS exon 19 CIITA DEV INV F AAGTCTCATGCCTTGGAGGA DEV inversion CIITA, SOCS1 CIITA DEV INV R TGGGTGGGTCTCTGTTTCTC DEV inversion CIITA, SOCS1 SOCS1 DEV INV F  AGGTAGGAGGTGCGAGTTCA DEV inversion CIITA, SOCS1 SOCS1 DEV INV R  GTCCTCCGCGACTACCTGAG DEV inversion CIITA, SOCS1  150 Primer name Primer sequence (5'-3') comment CLEC16A R1 GACAAGGGTCAGCGATTCGAC DEV deletion CIITA, CLEC16A CLEC16A R2 AGAGGAATCTAGCGCGTCTG DEV deletion CIITA, CLEC16A EMP2 R1 TGATGACTGTGCAATTCGTG Karpas1106P TXNDC11-EMP2 fusion EMP2 I1 R4na CTGGGCGTGGTCGTCATAC Karpas1106P TXNDC11-EMP2 fusion EMP2 I1 R1 AGCAGGAATGGCATATGAGC Karpas1106P TXNDC11-EMP2 fusion EMP2 I1 R2 CAAGTCTAAGCCGCATCCTC Karpas1106P TXNDC11-EMP2 fusion EMP2 I1 R3 TCTGTTGCAGAACCCCAAAC Karpas1106P TXNDC11-EMP2 fusion EMP2 I1R5             CTGCAGAGGTGATGTGGAAG Karpas1106P TXNDC11-EMP2 fusion TXNDC11 E3 F1 GTGCTCTGTAACGGGATGGT Karpas1106P TXNDC11-EMP2 fusion TXNDC11 I3F2 CACATTCCATCCCATTTCC Karpas1106P TXNDC11-EMP2 fusion TXNDC11 I3F1 ACAAAGAGGGCTGAAAAACG Karpas1106P TXNDC11-EMP2 fusion TXNDC11 F2 GGGGAAATGCAGAAAACAGA Karpas1106P TXNDC11-EMP2 fusion TXNDC11 F1 AATACCAGCAAAGCCACCTG Karpas1106P TXNDC11-EMP2 fusion TXNDC11 I3F5        TTGAAGGGACCTCAAAGGAA Karpas1106P TXNDC11-EMP2 fusion FAM18A I2 F1 GGTCCCAGGCTTACTTGAGGAGA TVP23A FAM18A I2 F2 TCCAATTCAACGTATCTTGCTGCT TVP23A FAM18A I2 F2.2 AAAAACATTAGCCGGTGTGG  TVP23A FAM18A I2 F3 GGCACACAAAGGTCCTTGAAAAT TVP23A NUBP1_5UTR_F1 GTTCCGGTGACCACGAAG U2940 NUBP1-CIITA fusion NUBP1_e9_F1 ACTTGGAGGTCCCTCTCCTC U2940 NUBP1-CIITA fusion NUBP1_I1F1 TGGAGCATCTCAGTCTGCTG U2940 NUBP1-CIITA fusion NUBP1_I9_F2         GTGCCATGCTCGTCTCAGT U2940 NUBP1-CIITA fusion CIITA xpr F2 CACCATGCGTTGCCTGGCTCC cDNA cloning XhoI-CIITA xprR1* CCTAAGATCTCGAGTCATCTCAGGCTGATCCGTGAATC cDNA cloning XhoI-U2940 CIITA R3* CCTAAGATCTCGAGTCATGGGATACAGCCTGGAGAAGAGC cDNA cloning pCMV F CGCAAATGGGCGGTAGGCGTG Expression clone sequencing PGK-R CAGAGGCCACTTGTGTAG Expression clone sequencing CIITA cD-F2 na GCTCTGGCAAATCTCTGAGG Expression clone sequencing CIITA cD-F2.5na GCTTCCCCAGTACGACTTTG Expression clone sequencing CIITA cD-F3na AGAAGAAGCTGCTCCGAGGT Expression clone sequencing  151 Primer name Primer sequence (5'-3') comment CIITA cD-F4 na GCAGCACGTGGTACAGGAG Expression clone sequencing CIITA cD-R1na    CACTGGGAGGGGGTACTTG Expression clone sequencing CIITA cD-R2na         AAGCCGGACAGCTCAAATAG Expression clone sequencing CIITA cD-R3na GCCCAGTACATGTGCATCAG Expression clone sequencing CIITA F5 GTCCTACCTGTCAGAGCCCCAAG qRT-PCR CIITA E2R1 AGCCAGGTCCATCTGGTCATAGA qRT-PCR Retro_NUBP1 CCGGACTCTAGCGTTTGGAATGGAGGAGGTGCC U2940 NUBP1-CIITA fusion Gibson Assembly Retro_CIITA_end GCTCGGTACCAAGCTTAAGTTTTCATCTCAGGCTGATCC U2940 NUBP1-CIITA fusion Gibson Assembly GAPDH_fwd CATGAGAAGTATGACAACAGCCT qRT-PCR GAPDH R AGTCCTTCCACGATACCAAAGT qRT-PCR A43030_del_CIITA_F CAGGAGGATTGGAGGATCAC oligocapture validation A43030_del_CIITA_R GGACAGGAGAACATGGCTTC oligocapture validation A43031_inv_CIITA_F CAGATGTCGTTCTTGCTTTTG oligocapture validation A43031_inv_CIITA_R TCCAAGCCTCTGTCACCTCT oligocapture validation A43036_inv_F GGGGTGGTATCCCTTTTCTC oligocapture validation A43036_inv_R CTAAGGGCGAAAAAGCAGTT oligocapture validation A43036_tX;16_F CAGGAGCTAGGGAGCCACTT oligocapture validation A43036_tX;16_R TTTTGCAGATCTACTTGCATGA oligocapture validation A43049_inv_CIITA_F AGGCCCTTTTATCAAGTGAGG oligocapture validation A43049_inv_CIITA_R CATCAGCAGGTCCAGGTTCT oligocapture validation A43051_del_CIITA_F CTGGGTTCAAAGCAAACCAT oligocapture validation A43051_del_CIITA_R AGGAGCTCAAGAGCAACCTG oligocapture validation A43052_CIITA-LINC01185_F AGCCCGGGAACCTACATC oligocapture validation A43052_CIITA-LINC01185_R CCGCTCCTGAACTTTAAACC oligocapture validation A43052_LINC01185-CIITA_F GACGCAGCAACCCTCACC oligocapture validation A43052_LINC01185-CIITA_R CGCAGCCTGGAGTGTCTAAC oligocapture validation A43052_IgK-CIITA_F GCATGATACAGAAAAGTGGAAAA oligocapture validation  152 Primer name Primer sequence (5'-3') comment A43052_IgK-CIITA_R CTCCCTAGCTCCTGGCTCCT oligocapture validation A43052_del_CIITA_F TGGTTAAAGGTTTGGCTCCC oligocapture validation A43052_del_CIITA_R AGTTGGGATGCCACTTCTGA oligocapture validation A43067_inv_IL4R_F CATCTTGGCGAAGGTGTGTG oligocapture validation A43067_inv_IL4R_R TCAGGTGTAGGTTTGGCCAG oligocapture validation A43068_del_CIITA_F GGGGCCTAATGTTGTCCTCT oligocapture validation A43068_del_CIITA_R AACTCTGTTTCCTCCCTCGG oligocapture validation A43069_MGAT3_F CCTCTGCCCCGTTTTCATCT oligocapture validation A43069_MGAT3_R GGTCCAAAGTCTGGCGTACA oligocapture validation A43070_del_TXNDC11_F AGAGGCAGCAGCCTTTTTCT oligocapture validation A43070_del_TXNDC11_R TGGGGTAATGCCTACGAGTC oligocapture validation A43070_CIITA-PRDM16_F GATGCTGGAAACGAGGTGTT oligocapture validation A43070_CIITA-PRDM16_R GGAAGAGGAAGCGTCTGGTC oligocapture validation A43072_del_NUBP1_F GGAGATTCAGGCAGCTCAAC oligocapture validation A43072_del_NUBP1_R CCAGCCACGTTAGCCTACAG oligocapture validation A43075_AID-CIITA_F TCCATTTGTTCAGACGTAGCTT oligocapture validation A43075_AID-CIITA_R AACACCTCGTTTCCAGCATC oligocapture validation A43075_CIITA-AID_F CGCCAAGATGTTCAACGAG oligocapture validation A43075_CIITA-AID_R TTGAACTCCAGGGCTCAAG oligocapture validation A43076_CIITA_SNX29_F TGCAGTAAATGCCGTTTGAG oligocapture validation A43076_CIITA_SNX29_R CACCATCTGAGCTCCATTCA oligocapture validation A43077_delCIITA_F TTGCAACAACCTCAGTGGAG oligocapture validation A43077_delCIITA_R GTTGGGATGCCACTTCTGAT oligocapture validation A43078_MYC/PVT1-CIITA_F ACAAAGCTGCCAGAGAAACG oligocapture validation A43078_MYC/PVT1-CIITA_R CCACCACGTGCTTTATCAGA oligocapture validation A43080_delCIITA_F AGAGCTTCGACTGCCTCTTC oligocapture validation A43080_delCIITA_R AACACCTCGTTTCCAGCATC oligocapture validation A43080_del_F TGGGTGGGTCTCTGTTTCTC oligocapture validation  153 Primer name Primer sequence (5'-3') comment A43080_del_R GCCAGACTCCACTCCATACC oligocapture validation A43095_CIITAinv_F CAGGGAAAGTGAAGCTCAGG oligocapture validation A43095_CIITAinv_R AAGGTTTGGCTCCCTACTGC oligocapture validation A43110_del_CIITA_F GCCATCACCTCACTGAACCT oligocapture validation A43110_del_CIITA_R GTACACCCTCTGCGGTATGG oligocapture validation A43115_CIITAinv_F CTGTCAGAGCCCCAAGGTAA oligocapture validation A43115_CIITAinv_R TACAGGCTTTCCCACAGGTC oligocapture validation A43115_tra7_16_F AGCGAGACTCCGTCTCAAAA oligocapture validation A43115_tra7_16_R CTCCTGACCTCAGGTGATCC oligocapture validation   A.4 TSCA design (CIITA) for the DLBCL cohort Amplicon name ULSO Sequence DLSO Sequence CIITA + CIITA_UserDefined (15231807) AAGACCTCCCCACCCACCACAAACTTAC CTCAAGAAATGTTTGTTGAATGAATGAAT CIITA + CIITA_UserDefined (15231807) AGCTGGAGGGCCTGAGCAAGGACATTTT CATAGGACCAGATGAAGTGATCGGTGA CIITA + CIITA_UserDefined (15231807) TGTTGGCTTTTAAAGGGCCTCCC GCTCTACTTTGAGAAAAACCAGAGACC CIITA + CIITA_UserDefined (15969338) TGGTCATAGAAGTGGTAGAGGCACA GAATAAAAGCGCTCATTCAGCACCTCT CIITA + CIITA_UserDefined (15969338) GAGCTTCTTAACAGCGATGCTGA GGACGCTCTCTGCAGATGGGGATGAT CIITA + CIITA_UserDefined (15969338) CTTGATTGTCCTTTTCTGGGCTCAG ACAGACGTGGGAGCTGTCCGTGGTG CIITA_Exon (15192912) GGAGGTCTTACCCTTGCTCTTTGC ACAGGTGCATGCTACAGTGCCCAGCAA CIITA_Exon (16954886) GCTGAGACTGCACGCTAAATTAAGATG AGTTGGGAGCCCGCCAAGCTAAGCCA CIITA_Exon (16756956) TTTGTTCAGGGCTGTGGTGATTGCTTC ACACAGTGAGGGGGAGGGCTCAGGACC CIITA_Exon (15728519) TACATGTCCTCAACCTGCATGGCGTGA TCAGACCCAGGCACGGTGACCAG CIITA_Exon (17651572) ATGAGGGGATGTCTCTGATGACGCAT GGGGGATGGGACTCAGAGCCAG CIITA_Exon (17652495) AAGTGCATGGAGTATGGGGAGGATGA AAAGGCAGTGAGGTGGGATCTTGCAT CIITA_Exon (14742566) TGATGGAGCGAAGGGGCTGGTGGAGC GGAGAGAAGAGAGTAGAACTTCCAAAG  154 Amplicon name ULSO Sequence DLSO Sequence CIITA_Exon (14742566) TCCCAACATCTCCAGACCGGCCA AGTCGGGACAGGGAGGGTCTCCA CIITA_Exon (16530899) TAAATAAATGAGTGTGTGAGCCAACAA AGAAGCAGGTGCCAGATTTAGGGTGAG CIITA_Exon (15777327) CTGCTGGAAGCTATTTCCAAAGTGGT AATGTTAGGGGGAGCAGGCACTGCTG CIITA_Exon (15009032) TTAGAGGACTCTAAGGGACCCCAAGCT AAAACATGTGATCAGCTGCCCCAGGGA CIITA_Exon_1928651_UserDefined (16481070) TGGTTGAACAGCGCAGGCAGTGG TTGATCAGCAACTGCTCTGTGCCAG CIITA_Exon_1928651_UserDefined (16481070) GACTGCTCCACCCTGCCCTGCCT AGCCAGTTTTATCCTTGGGGCC CIITA_Exon_1929553_UserDefined (15485636) AAAACTGTGTGGGGAACAGATGTAAATG GCCAGGCTGGAGAGGAGCAGCAGCAA CIITA_Exon_1929553_UserDefined (15485636) CCGCGTGAGACACGAGTGATTG ACTCGTGGCGGCCGATGAGGTTTTCA CIITA_Exon_1929553_UserDefined (15485636) GGCTGTGAGGAGGAGGGTGCAA CTGTGGGCCCAGGGAGAAGAGC CIITA_Exon_1929553_UserDefined (15485636) CTTTTCCAGAAGAAGCTGCTCCGA GGCCACTTCTTCTCAGTCACAGC CIITA_Exon_1929553_UserDefined (15485636) TTTGATGTCTGCGGCCCAGCTCCCAGGCCA TCCCGGAGGAGCGTCAGGGCTC CIITA_Exon_1929553_UserDefined (15485636) GGGCCCTGGCAGAGCTGGCCAA CTCTGAGTGGCGAAATCAAGGACAA CIITA_Exon_1929553_UserDefined (15485636) TTCAGGTACCTCGCAAGCACCTTCTG AGCCACAGGGCCCCCAGGAAGC CIITA_Exon_1929553_UserDefined (15485636) ATCGGCGGCTGCCTCGGTGGACAGGAA CCTTGGAGGCGGCGGGCCAAGACTTCT CIITA_Exon_1929553_UserDefined (15485636) AATCCATTCTGCCCCACCCGGCTGCTCT CTTGCCCAGTACATGTGCATCAG CIITA_Exon_1928561_UserDefined (17619073) CAGATGGCCCCAGGACGCTAGCTGAT TTTTTAGACAAGGGCTCGCTGTGTCA    155 A.5 Cases selected for oligocapture sequencing BCCRC_ID Library ID Lymphoma subtype Localization CIITA ba PDL1-2 ba TP63 ba TBL1XR1 ba BC_001 B  PMBCL mediastinum 1 0 0 0 BC_002 A43049 PMBCL mediastinum 1 0 0 0 BC_003 A43050 PMBCL mediastinum 1 0 0 0 BC_004 A43051 DLBCL GI 1 0 0 0 BC_005 A43052 DLBCL tonsil 1 0 0 0 BC_006 A43053 DLBCL testis 1 0 0 0 BC_007  FL LN 1 0 0 0 BC_008  FL LN 1 0 0 0 BC_009  FL LN 1 0 0 0 BC_010  FL LN 1 0 0 0 BC_011  FL LN 1 0 0 0 BC_012  FL LN 1 0 0 0 BC_013  FL LN 1 0 0 0 BC_014  FL LN 1 0 0 1 BC_015  FL BM 1 0 0 0 BC_016  FL LN 1 0 0 0 BC_017  PMBCL LN 1 0 NA NA BC_018 B  PMBCL LN 1 0 NA NA BC_019  PMBCL LN 1 0 NA NA BC_020 A43067 PMBCL LN 1 0 NA NA BC_021 A43068 PMBCL LN 1 0 NA NA BC_022 A43069 PMBCL mediastinum 1 0 NA NA BC_023 A43070 PMBCL LN 1 0 NA NA BC_024 A43071 PMBCL mediastinum 1 1 NA NA BC_025 A43072 PMBCL LN 1 1 NA NA BC_026 A43073 PMBCL mediastinum 1 0 NA NA BC_027 B A43074 PMBCL mediastinum 1 1 NA NA BC_028 A43075 PMBCL mediastinum 1 0 NA NA BC_029 A43076 PMBCL mediastinum 1 0 NA NA BC_030 A43077 PMBCL mediastinum 1 0 NA NA BC_031 B A43078 PMBCL mediastinum 1 0 NA NA BC_032 B A43079 PMBCL LN 1 1 NA NA BC_033 A43080 PMBCL LN 1 0 NA NA BC_034 * A43081 PMBCL mediastinum 1 0 NA NA  156 BCCRC_ID Library ID Lymphoma subtype Localization CIITA ba PDL1-2 ba TP63 ba TBL1XR1 ba BC_035 A43082 PMBCL LN 0 1 0 0 BC_036 A43083 DLBCL GI 0 1 0 0 BC_037 A43084 PMBCL mediastinum 0 1 0 0 BC_038 A43085 DLBCL LN 0 1 0 0 BC_039 A43086 DLBCL LN 0 1 0 0 BC_040 A43087 DLBCL LN 0 1 0 0 BC_041 A43088 DLBCL GI 0 1 0 0 BC_042 A43089 DLBCL testis 0 1 0 0 BC_043 A43090 PMBCL LN 0 1 NA NA BC_044 * A43091 PMBCL LN 0 1 NA NA BC_045 A43092 PMBCL mediastinum 0 1 NA NA BC_046 A43093 PMBCL mediastinum 0 1 NA NA BC_047 A43094 PMBCL mediastinum 0 1 NA NA BC_048 A43095 PMBCL soft tissue 0 1 NA NA BC_049 I A43096 PMBCL LN 0 1 NA NA BC_050 A43097 PMBCL mediastinum 0 1 NA NA BC_051 B  PMBCL LN 0 1 NA NA BC_052 A43099 DLBCL LN 0 1 NA NA BC_053 A43100 PMBCL mediastinum 0 up NA NA BC_054 A43101 PMBCL LN 0 up NA NA BC_055B A43102 DLBCL CNS 0 0 1 0 BC_056 A43103 DLBCL LN 0 up NA NA BC_057 A43104 DLBCL LN 0 0 0 1 BC_058 A43105 DLBCL LN 0 0 0 1 BC_060  DLBCL soft tissue 0 0 1 1 BC_061 A43106 DLBCL ENT 0 0 1 1 BC_062 A43107 DLBCL ENT 0 0 1 1 BC_063 A43108 DLBCL ENT 0 0 0 1 BC_064 A43109 DLBCL LN 0 0 1 0 BC_065 A43110 DLBCL sinus 0 1 1 1 BC_066 A43111 DLBCL testis 0 0 1 0 BC_069 B A43030 PMBCL mediastinum 1 1 0 0 BC_071 A43117 HL (L1236) cell line 0 1 NA NA BC_072  PMBCL mediastinum 1 0 NA NA BC_073  DLBCL testis 0 1 0 0 BC_074  DLBCL testis 1 0 0 0  157 BCCRC_ID Library ID Lymphoma subtype Localization CIITA ba PDL1-2 ba TP63 ba TBL1XR1 ba BC_075  DLBCL testis 1 0 0 0 BC_076  DLBCL LN 0 0 1 1 BC_077  DLBCL testis 1 0 0 0 BC_078 A43029 DLBCL GI 1 0 0 0 BC_079 A43031 DLBCL testis 1 0 0 0 BC_080 A43032 DLBCL testis 1 0 0 0 BC_081 A43033 DLBCL testis 1 0 0 0 BC_082 A43034 DLBCL CNS 1 0 0 0 BC_083 A43038 DLBCL testis 0 1 0 0 BC_084 A43042 DLBCL CNS 0 1 0 0 BC_085  DLBCL ENT 0 up NA 1 BC_086 A43045 DLBCL LN 0 0 0 1 BC_087 A43046 DLBCL LN 0 0 0 1 BC_088 A43047 DLBCL bladder 0 0 1 1 BC_089 A43119 FL LN 1 NA NA NA BC_091  DLBCL testis 0 1 0 0 BC_092 B A43041 DLBCL testis 0 1 0 0 BC_093 I A43036 PMBCL LN 1 0 NA NA BC_094 I A43037 PMBCL mediastinum 1 0 NA NA BC_095 I A43043 PMBCL mediastinum 0 1 NA NA BC_097 I A43115 PMBCL LN 1 1 NA NA BC_099 I A43118 PMBCL mediastinum 0 up NA NA  Abbreviations: BM, bone marrow; CNS, central nervous system; DLBCL, diffuse large B cell lymphoma; ENT, enteric: FL, follicular lymphoma; GI, gastro-intestnal; LN, lymph node; NA, not available; PMBCL, primary mediastinal large B cell lymphoma  158  Appendix B  - Supplementary results B.1 CDS mutations and promoter III alterations in primary PMBCL specimens Case # Genomic alteration Putative translational impact Allelic frequency Comments 1 G5136A p.MET1? 0.34 SNV is in cis with CIITA-PDL2 translocation; infer "intron 1 deletion" from 2nd allele because translocation breakpoint renders that allele incapable of amplification 2 T4582G pIII  two alleles are affected by structural variations, all SNVs are linked to pIII/exon 1 deletion T4649C pIII  G4970T pIII  4582_4583insT pIII  4986-5217del deletes pIII and exon 1  3 G5186A p.Gly18Asp*9 0.28   4 A4605T pIII    5 G44204T p.Glu1002* 0.23   6 G35439A ǂ p.Cys715Tyr 0.65   16 T5164C p.Ser11Pro  T5164C, A5168C and 5105_5112del are linked but in trans to p.Pro16Aspfs*65 A5168C p.Tyr12Ser  5105_5112del 5' UTR  5171_5323del p.Pro16Aspfs*65  17 35796delTT p.Phe835Serfs*9 0.31 biallelic intron 1 mutations; linkage of del to which intron1 allele is unknown 18 35897delA ǂ p.Ile868Phefs*22 0.01   19 T35376C ǂ p.Leu694Ser 0.35   20 C26496T  p.Glu107*    21 C23229G p.Ser66*    22 A5183T p.Gln17Leu    23 G5185A p.Gly18Thrfs*9 0.24   G5186C p.Gly18Thrfs*9    35250_35251insC p.Gly655Argfs*60 0.26   25 30588_30591dup p.Phe254Tyrfs*7 0.14   ǂ somatic origin; genomic coordinates according to LRG49  B.2 Intron 1 alterations in primary PMBCL cases Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 1 10971190 10971190 G A transition case 1 10971878 10971878 C G transversion case 1 10972410 10972425  del 16 deletion  159 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 1 10972570 10972570 G A transition case 1 10972687 10972687 G A transition case 1 10972750 10972750 C T transition case 1 10972753 10972753 C T transition case 1 10972847 10972847 C T transition case 1 10972871 10972871 C T transition case 1 10972975 10972975 C G transversion case 1 10972990 10972990 C T transition case 1 10973111 10973111 G C transversion case 1 10973471 10973715  del 245 deletion case 1 10974017 10974017 A C transversion case 1 10974154 10974154 C T transition case 7 10971467 10971467 G T transversion case 7 10971672 10971672 G A transition case 7 10971706 10971706 G T transversion case 7 10971730 10971730 C G transversion case 7 10971744 10971744 T A transversion case 7 10971751 10971751 G A transition case 7 10971777 10971778  ins 11 insertion case 7 10971779 10971779 G T transversion case 7 10971963 10971963 C T transition case 7 10971990 10971990 C T transition case 7 10972096 10972096 G C transversion case 7 10972212 10972212 A C transversion case 7 10972235 10972280  dup duplication case 7 10972269 10972269 G C transversion case 7 10972361 10972361 G A transition case 7 10972377 10972377 C A transversion case 7 10972379 10972379 C T transition case 7 10972382 10972382 C T transition case 7 10972383 10972383 C T transition case 7 10972385 10972385 C T transition case 7 10972397 10972397 C T transition case 7 10972419 10972419 G C transversion case 7 10972571 10972571 C G transversion case 7 10972629 10972640  del 12 deletion case 7 10972678 10972689  del 12 deletion case 7 10972722 10972722 T C transition case 7 10972747 10972747 G C transversion case 7 10972797 10972797 G A transition case 7 10972811 10972811 C A transversion case 7 10972847 10972847 C A transversion case 7 10972900 10972900 G A transition case 7 10972913 10972913 G A transition case 7 10972933 10972933 G A transition  160 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 7 10972975 10972975 C T transition case 7 10973078 10973078 G A transition case 7 10973102 10973102 G A transition case 7 10973112 10973112 C T transition case 7 10973186 10973186 G A transition case 7 10973217 10973217 C T transition case 7 10973218 10973218 C T transition case 7 10973280 10973280 C T transition case 7 10973314 10973336  del 23 deletion case 7 10973347 10973347 C T transition case 7 10973351 10973351 C T transition case 7 10973402 10973402 G A transition case 7 10973403 10973403 G T transversion case 7 10973588 10973588 G A transition case 7 10973610 10973610 G C transversion case 7 10973686 10973686 C T transition case 7 10973690 10973690 G C transversion case 7 10974111 10974111 G A transition case 8 10971559 10971559 C T transition case 8 10971672 10971672 G A transition case 8 10971784 10971784 G T transversion case 8 10971785 10971785 C G transversion case 8 10971840 10971840 G A transition case 8 10971845 10971845 G A transition case 8 10971911 10972044  del deletion case 8 10972125 10972125 G A transition case 8 10972147 10972152  del deletion case 8 10972180 10972180 C T transition case 8 10972300 10972333  del deletion case 8 10972415 10972415 C G transversion case 8 10972421 10972421 T G transversion case 8 10972486 10972486 G T transversion case 8 10972522 10972522 C G transversion case 8 10972532 10972532 C T transition case 8 10972534 10972534 C T transition case 8 10972554 10972554 C A transversion case 8 10972570 10972570 G A transition case 8 10972619 10972619 G A transition case 8 10972651 10972651 C G transversion case 8 10972661 10972891  del deletion case 8 10972897 10972897 G T transversion case 8 10972898 10972898 C A transversion case 8 10972899 10972900  del deletion case 8 10972926 10972926 C T transition case 8 10972933 10972933 G C transversion  161 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 8 10972965 10973055  del deletion case 8 10973079 10973079 G A transition case 8 10973103 10973103 C G transversion case 8 10973110 10973113  del deletion case 8 10973123 10973123 G A transition case 8 10973205 10973205 C T transition case 8 10973253 10973253 C G transversion case 8 10973265 10973363  del deletion case 8 10973436 10973436 G T transversion case 8 10973445 10973445 C T transition case 8 10973478 10973487  dup duplication case 8 10973495 10973495 G A transition case 8 10973544 10973544 C T transition case 8 10973551 10973551 G C transversion case 8 10973602 10973602 G A transition case 8 10973713 10973713 C T transition case 8 10973756 10973756 G A transition case 8 10973852 10973852 C T transition case 8 10973896 10973896 G C transversion case 8 10973977 10973977 C T transition case 9 10971419 10971419 A G transition case 9 10971979 10971979 C T transition case 9 10972019 10972019 C T transition case 9 10972115 10972141  del 27 deletion case 9 10972419 10972419 G C transversion case 9 10972508 10972514  del 7 deletion case 9 10972570 10972570 G A transition case 9 10972668 10972668 C A transversion case 9 10972674 10972684  del 11 deletion case 9 10972743 10972913  del 171 deletion case 9 10973090 10973090  ins A insertion case 9 10973104 10973304  inv 201 inversion case 9 10973208 10973213  del 6 deletion case 9 10973179 10973179 C T transition case 9 10973184 10973184 G A transition case 9 10973320 10973320 C T transition case 9 10973351 10973351 C T transition case 9 10973588 10973588 G A transition case 9 10973686 10973686 C T transition case 9 10974109 10974109 C G transversion case 9 10974123 10974123 G A transition case 10 10971954 10971954 C A transversion case 10 10972229 10972229 G C transversion case 10 10972349 10972349  del C deletion case 10 10972417 10972424  del 8 deletion  162 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 10 10972482 10972482 G C transversion case 10 10972708 10972724  del 17 deletion case 10 10972949 10973705  del 757 deletion case 11 10971525 10971525 C T transition case 11 10971666 10972721  del 1056 deletion case 11 10972742 10972742 G A transition case 11 10972770 10972770 G T transversion case 11 10972916 10972927  del 12 deletion case 11 10972942 10972942 G C transversion case 11 10973054 10973054 G C transversion case 11 10973097 10973097 C T transition case 11 10973112 10973114  del 3 deletion case 11 10973165 10973165 C T transition case 11 10973253 10973257  del 5 deletion case 11 10973686 10973686 C T transition case 11 10973777 10973777 C T transition case 11 10973781 10973781 G C transversion case 11 10973784 10973784 G T transversion case 11 10973821 10973821 G A transition case 11 10973835 10973835 C A transversion case 16 allele 1 10971159 10971166  del 8 deletion case 16 allele 1 10971218 10971218 T C transition case 16 allele 1 10971222 10971222 A C transversion case 16 allele 1 10971462 10971462 T A transversion case 16 allele 1 10971673 10971673 C T transition case 16 allele 1 10971953 10971953 G A transition case 16 allele 1 10972141 10972141 G A transition case 16 allele 1 10972415 10972415 C T transition case 16 allele 1 10972527 10973026  del 500 deletion case 16 allele 1 10973071 10973085  del 15 deletion case 16 allele 1 10973089 10973089 C T transition case 16 allele 1 10974122 10974122 A C transversion case 16 allele 2 10971225 10971377  del 153 deletion case 16 allele 2 10971946 10971946 G A transition case 16 allele 2 10972482 10973617  del 1136 deletion case 16 allele 2 10973899 10973899 A G transition case 17 allele 1 10971352 10971352 G C transversion case 17 allele 1 10971395 10971395 G C transversion case 17 allele 1 10971546 10971546 C T transition case 17 allele 1 10971587 10971997  del 411 deletion case 17 allele 1 10972017 10972017 T A transversion case 17 allele 1 10972208 10972208 G C transversion case 17 allele 1 10972299 10972299 G A transition case 17 allele 1 10972415 10972415 C T transition case 17 allele 1 10972423 10972423 G A transition  163 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 17 allele 1 10972506 10972520  del 15 deletion case 17 allele 1 10972522 10972522 C T transition case 17 allele 1 10972534 10972534 C G transversion case 17 allele 1 10972570 10972570 G A transition case 17 allele 1 10972577 10972577 G A transition case 17 allele 1 10972634 10972634 C G transversion case 17 allele 1 10972674 10972674 G C transversion case 17 allele 1 10972677 10972691  del 15 deletion case 17 allele 1 10972694 10972694 C G transversion case 17 allele 1 10972704 10972704 C T transition case 17 allele 1 10972719 10972719 G C transversion case 17 allele 1 10972747 10972747 G C transversion case 17 allele 1 10972750 10972750 C T transition case 17 allele 1 10972763 10972763 G A transition case 17 allele 1 10972777 10972777 G A transition case 17 allele 1 10972786 10972786 G A transition case 17 allele 1 10972797 10972797 G C transversion case 17 allele 1 10972799 10972810  del 12 deletion case 17 allele 1 10972870 10972870 G A transition case 17 allele 1 10972879 10972879 G C transversion case 17 allele 1 10972993 10972993 G C transversion case 17 allele 1 10973096 10973096 C T transition case 17 allele 1 10973097 10973097 C T transition case 17 allele 1 10973103 10973103  del C deletion case 17 allele 1 10973123 10973123 G T transversion case 17 allele 1 10973165 10973165 C T transition case 17 allele 1 10973186 10973186 G A transition case 17 allele 1 10973351 10973351 C G transversion case 17 allele 1 10973364 10973364 G C transversion case 17 allele 1 10973814 10973814 G A transition case 17 allele 2 10971388 10971388 T A transversion case 17 allele 2 10971660 10971660 C A transversion case 17 allele 2 10971829 10971829 C G transversion case 17 allele 2 10971921 10971921 G C transversion case 17 allele 2 10971925 10971925 G A transition case 17 allele 2 10972019 10972019 C T transition case 17 allele 2 10972094 10972094 G T transversion case 17 allele 2 10972200 10972200 C G transversion case 17 allele 2 10972342 10972342 G A transition case 17 allele 2 10972343 10972365  del 23 deletion case 17 allele 2 10972396 10972396 G C transversion case 17 allele 2 10972411 10972414  del 4 deletion case 17 allele 2 10972419 10972429  del 11 deletion case 17 allele 2 10972468 10972501  dup 34 duplication case 17 allele 2 10972494 10972494 C T transition  164 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 18 10971673 10971673 C T transition case 18 10971940 10971940 G A transition case 18 10972031 10972031 G A transition case 18 10972032 10972032 G C transversion case 18 10972035 10972058  del deletion case 18 10972293 10972293 G C transversion case 18 10972304 10972304 G A transition case 18 10972327 10972327 G C transversion case 18 10972361 10972361 G T transversion case 18 10972423 10972423 G A transition case 18 10972550 10972550 C G transversion case 18 10972562 10972562 G A transition case 18 10972570 10972570 G C transversion case 18 10972660 10972660 G A transition case 18 10972679 10972679 C T transition case 18 10972749 10972749 G A transition case 18 10972782 10972782 G A transition case 18 10973040 10973040 A C transversion case 18 10973040 10973040 A C transversion case 18 10973041 10973042  ins 11 insertion case 18 10973042 10973042 A G transition case 18 10973111 10973111 G C transversion case 18 10973315 10973315 C T transition case 19 10974015 10974015 A G transition case 20 10971446 10971446 T C transition case 20 10971574 10971574 A G transition case 20 10971584 10971584 G A transition case 20 10971635 10971635 G A transition case 20 10972052 10972052 T C transition case 20 10972240 10972444  del 205 deletion case 20 10972490 10972490 G A transition case 20 10972750 10972750 C T transition case 20 10972798 10972798 G T transversion case 20 10972818 10972818 G C transversion case 20 10973014 10973014 G T transversion case 20 10973103 10973103 C T transition case 20 10973123 10973123 G A transition case 20 10973252 10973322  del 71 deletion case 23 10971239 10971239 G A transition case 23 10971240 10971240 G C transversion case 23 10971903 10971903 C T transition case 23 10972119 10972132  del 14 deletion case 23 10972703 10972703 G C transversion case 23 10972782 10972790  del 9 deletion case 24  10971673 10971673 C A transversion  165 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 24  10971892 10971892 C A transversion case 24  10971903 10971903 C T transition case 24  10972016 10972495  del 480 deletion case 24  10972504 10972504 C T transition case 24  10972713 10972713 G A transition case 24  10972715 10973045  del 331 deletion case 24  10973078 10973079  del 2 deletion case 24  10973193 10973214  del 22 deletion case 24  10973254 10973254 C A transversion case 24  10973621 10973621 C A transversion case 24  10973686 10973686 C T transition case 24  10974096 10974096 T C transition case 25 allele 1 10971494 10971514  dup 21 duplication case 25 allele 1 10971514 10971514 C G transversion case 25 allele 1 10971545 10971545  del G deletion case 25 allele 1 10971699 10971699 A G transition case 25 allele 1 10971840 10971840 G A transition case 25 allele 1 10971854 10971854 G A transition case 25 allele 1 10971855 10971855 C T transition case 25 allele 1 10971856 10971856 C T transition case 25 allele 1 10972200 10972200 C T transition case 25 allele 1 10972208 10972208 G C transversion case 25 allele 1 10972317 10972317 C T transition case 25 allele 1 10972423 10972444  del 22 deletion case 25 allele 1 10972471 10972471 G A transition case 25 allele 1 10972649 10972649 A C transversion case 25 allele 1 10972679 10972679 C G transversion case 25 allele 1 10972743 10972743 C A transversion case 25 allele 1 10972819 10972819 C T transition case 25 allele 1 10972870 10972875  del 6 deletion case 25 allele 1 10972906 10973687  del 782 deletion case 25 allele 1 10973691 10973691 C T transition case 25 allele 1 10973713 10973713 C G transversion case 25 allele 1 10974124 10974124 G A transition case 25 allele 2 10971654 10971654 A G transition case 25 allele 2 10971954 10971954 C T transition case 25 allele 2 10972521 10972521 G A transition case 25 allele 2 10972619 10972633  del 15 deletion case 25 allele 2 10972743 10972750   del 8 deletion case 25 allele 2 10972873 10972873 G A transition case 25 allele 2 10973212 10973215  del 4 deletion case 25 allele 2 10973269 10973269 C T transition case 25 allele 2 10973274 10973274 C A transversion case 25 allele 2 10973586 10973586 A C transversion case 25 allele 2 10974124 10974124 G A transition  166 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 26 10971346 10971346 G A transition case 26 10972201 10972201  del C deletion case 26 10972348 10972348 C T transition case 26 10972414 10972428  del 15 deletion case 26 10972570 10972570 G C transversion case 26 10972577 10972577 G A transition case 26 10973124 10973124 C T transition case 26 10973268 10973282  del 15 deletion case 26 10973314 10973314 G C transversion case 26 10973418 10973441  del 24 deletion case 26 10973588 10973588 G T transversion case 26 10973610 10973621  del 12 deletion case 26 10973813 10973813 A G transition case 26 10973914 10973914 G A transition case 27 10971581 10971581 G C transversion case 27 10972365 10972365 C G transversion case 27 10973111 10973111 G A transition case 27 10973789 10973813  del 25 deletion case 28 10971989 10971989 G A transition case 28 10972472 10972472 G A transition case 28 10972845 10972852  del 8 deletion case 28 10973478 10973478 G A transition case 28 10973583 10973583 G A transition case 29 allele 1 10971545 10971545 G A transition case 29 allele 1 10971627 10973574  del 1948 deletion case 29 allele 1 10973585 10973592  del 8 deletion case 29 allele 1 10973690 10973690 G C transversion case 29 allele 1 10973712 10973712 G C transversion case 29 allele 2 10971730 10971730 C G transversion case 29 allele 2 10972000 10972000 C G transversion case 29 allele 2 10972093 10972646  del 554 deletion case 29 allele 2 10972679 10972679 C G transversion case 29 allele 2 10972725 10972725 T A transversion case 29 allele 2 10972743 10972876  del 134 deletion case 29 allele 2 10973052 10973052 C T transition case 29 allele 2 10973124 10973124 C T transition case 29 allele 2 10973148 10973148 G T transversion case 29 allele 2 10973468 10973468 G A transition case 29 allele 2 10973484 10973484 T C transition case 29 allele 2 10973613 10973613 T C transition case 29 allele 2 10973854 10973854 G A transition case 29 allele 2 10974016 10974016 C G transversion case 30 10971240 10971240 G A transition case 30 10971356 10973764  del 2409 deletion case 30 10973977 10973977 C T transition  167 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration case 31 10973002 10973002 G A transition case 31 10973078 10973078 G A transition case 31 10973394 10973394 C T transition case 31 10973426 10973426 C T transition case 31 10973846 10973846 C T transition case 32 allele 1 10972019 10972019 C A transversion case 32 allele 1 10972021 10972021 G A transition case 32 allele 1 10972180 10972180 C T transition case 32 allele 1 10972255 10972255 C T transition case 32 allele 1 10972387 10972388  ins 4 insertion case 32 allele 1 10972562 10972571  del 10 ins T deletion case 32 allele 1 10972737 10972743  del 7 deletion case 32 allele 1 10972847 10972847 C G transversion case 32 allele 1 10973090 10973090 C T transition case 32 allele 1 10973103 10973103 C T transition case 32 allele 1 10973111 10973111 G C transversion case 32 allele 1 10973183 10973194  del  12 deletion case 32 allele 2 10972000 10972000 C G transversion case 32 allele 2 10972019 10972019 C T transition case 32 allele 2 10972078 10972078 G C transversion case 32 allele 2 10972129 10972315  del 187 deletion case 32 allele 2 10972414 10972414 G A transition case 32 allele 2 10972521 10972521 G A transition case 32 allele 2 10972748 10972763  del 16 deletion case 32 allele 2 10972798 10972818  del 21 deletion case 32 allele 2 10972847 10972847 C T transition case 32 allele 2 10972870 10972870 G A transition case 32 allele 2 10973060 10973060 C T transition case 32 allele 2 10973103 10973103 C T transition case 32 allele 2 10973124 10973124 C T transition case 32 allele 2 10973315 10973315 C T transition case 32 allele 2 10973360 10973360 C T transition case 32 allele 2 10973459 10973473  del 15 deletion case 32 allele 2 10973757 10973757 C T transition case 32 allele 2 10973962 10973962 C G transversion case 32 allele 2 10974070 10974081  del 12 deletion case 32 allele 2 10974134 10974145  del 12 deletion  B.3 Intron 1 alterations in tFL cases Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration  168 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1001T1 10973365 10973365 G A transition FL1001T2 10973365 10973365 G A transition FL1002T1 10971690 10971690 G A transition FL1002T1 10972967 10972967 G A transition FL1002T1 10973365 10973365 G A transition FL1002T1 10974732 10974732 G A transition FL1002T2 10971672 10971672 G A transition FL1002T2 10972967 10972967 G A transition FL1002T2 10973365 10973365 G A transition FL1002T2 10974732 10974732 G A transition FL1004T1 10972128 10972128 G A transition FL1004T2 10972128 10972128 G A transition FL1006T1 10971524 10971524 G A transition FL1006T2 10971524 10971524 G A transition FL1006T2 10971672 10971672 G T transversion FL1006T2 10973146 10973146 C T transition FL1006T2 10973520 10973520 C T transition FL1006T2 10973595 10973595 C T transition FL1010T1 10972019 10972019 C T transition FL1010T1 10974165 10974165 G A transition FL1010T1 10974364 10974364 C T transition FL1010T2 10972019 10972019 C T transition FL1010T2 10974165 10974165 G A transition FL1011T1 10972864 10972865  ins insertion FL1011T1 10974856 10974856 A C transversion FL1011T1 10974902 10974902 G A transition FL1011T1 10974905 10974905 T A transversion FL1011T1 10974906 10974906 G A transition FL1011T1 10974918 10974918 G C transversion FL1011T1 10974928 10974928 C T transition FL1011T1 10974960 10974960 A G transition FL1011T2 10972864 10972865  ins insertion FL1014T1 10972424 10972424 C T transition FL1014T1 10972679 10972679 C T transition FL1014T2 10972424 10972424 C T transition FL1014T2 10972637 10972637 C A transversion FL1014T2 10973058 10973065  del deletion FL1014T2 10973111 10973111 G C transversion FL1014T2 10973730 10973737  del deletion FL1016T2 10971426 10971426 C T transition FL1017T1 10973085 10973098  del deletion FL1017T1 10973098 10973098 C A transversion FL1017T1 10973917 10973917 C G transversion FL1017T2 10971789 10971789 G A transition  169 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1017T2 10972615 10972615 G A transition FL1017T2 10973085 10973098  del deletion FL1017T2 10973098 10973098 C A transversion FL1018T1 10972743 10972743 C G transversion FL1018T2 10971672 10971672 G A transition FL1019T1 10971549 10971549 G A transition FL1019T1 10972407 10972407 G C transversion FL1019T1 10972409 10972409 G T transversion FL1019T1 10972521 10972523  del deletion FL1019T1 10972555 10972555 C A transversion FL1019T1 10972562 10972562 G A transition FL1019T1 10973686 10973686 C T transition FL1019T1 10973687 10973687 T A transversion FL1019T1 10973773 10973773 A C transversion FL1019T1 10973942 10973942 C G transversion FL1019T1 10974153 10974153 G C transversion FL1019T1 10974191 10974191 C T transition FL1019T2 10971701 10971701 C T transition FL1019T2 10972032 10972032 G A transition FL1019T2 10972048 10972048 C T transition FL1019T2 10972121 10972121 G A transition FL1019T2 10972521 10972523  del deletion FL1019T2 10972661 10972661 C T transition FL1019T2 10972801 10972801 G C transversion FL1019T2 10973533 10973533 C G transversion FL1019T2 10974191 10974191 C T transition FL1101T1 10972367 10972367 G A transition FL1101T1 10972419 10972419 G T transversion FL1101T1 10973063 10973063 C T transition FL1101T2 10971546 10971546 C T transition FL1101T2 10972340 10972340 C G transversion FL1101T2 10972367 10972367 G A transition FL1101T2 10973063 10973063 C T transition FL1101T2 10973530 10973530 G A transition FL1102T1 10972939 10972939 G T transversion FL1102T1 10989650 10989650 A G transition FL1102T2 10972939 10972939 G T transversion FL1103T1 10972749 10972749 G A transition FL1103T2 10972749 10972749 G A transition FL1105T1 10971545 10971545 G A transition FL1105T2 10971545 10971545 G A transition FL1105T2 10973082 10973082 C T transition FL1106T1 10972397 10972397 C T transition FL1106T2 10972397 10972397 C T transition  170 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1107T2 10975028 10975028 T C transition FL1108T1 10972750 10972750 C G transversion FL1108T1 10973829 10973829 C G transversion FL1108T1 10974109 10974109 C T transition FL1108T1 10975020 10975020 C T transition FL1108T2 10972750 10972750 C G transversion FL1108T2 10973204 10973204 G A transition FL1108T2 10973829 10973829 C G transversion FL1108T2 10974109 10974109 C T transition FL1108T2 10975028 10975028 T C transition FL1108T2 10975061 10975061 A G transition FL1110T1 10972661 10972661 C T transition FL1110T1 10973314 10973314 G A transition FL1110T1 10973986 10973998  del deletion FL1110T1 10974928 10974928 C T transition FL1110T2 10971315 10971315 C G transversion FL1110T2 10971316 10971316 C T transition FL1110T2 10971379 10971379 A G transition FL1110T2 10971513 10971513 A T transversion FL1110T2 10971700 10971700 G A transition FL1110T2 10971855 10971855 C T transition FL1110T2 10971954 10971954 C T transition FL1110T2 10972105 10972109  del deletion FL1110T2 10972396 10972396 G A transition FL1110T2 10972424 10972424 GC G deletion FL1110T2 10972482 10972482 G A transition FL1110T2 10972570 10972570 G A transition FL1110T2 10972679 10972679 C T transition FL1110T2 10972693 10972693 G T transversion FL1110T2 10972696 10972696 C T transition FL1110T2 10972743 10972743 C T transition FL1110T2 10972797 10972797 G C transversion FL1110T2 10972819 10972819 C T transition FL1110T2 10972822 10972822 C T transition FL1110T2 10972844 10972844 G A transition FL1110T2 10972846 10972846 G A transition FL1110T2 10972886 10972886 C T transition FL1110T2 10972975 10972975 C T transition FL1110T2 10973103 10973103 C T transition FL1110T2 10973111 10973111 G T transversion FL1110T2 10973277 10973277 G C transversion FL1110T2 10973314 10973314 G A transition FL1110T2 10973351 10973351 C T transition FL1110T2 10973568 10973568 C T transition  171 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1110T2 10973614 10973614 G A transition FL1111T2 10972195 10972195 C T transition FL1111T2 10973473 10973473 G T transversion FL1112T1 10973124 10973124 C T transition FL1114T2 10973728 10973728 G T transversion FL1116T1 10972423 10972423 G A transition FL1116T2 10972423 10972423 G A transition FL1117T1 10971672 10971672 G A transition FL1117T2 10971672 10971672 G A transition FL1118T1 10972570 10972570 G A transition FL1118T2 10972570 10972570 G A transition FL1118T2 10972967 10972967 G A transition FL1119T1 10972397 10972397 C T transition FL1120T1 10971546 10971546 C T transition FL1120T1 10972141 10972141 G A transition FL1120T1 10972316 10972316 G A transition FL1120T1 10972747 10972747 G A transition FL1120T1 10972782 10972782 G A transition FL1120T1 10973165 10973165 C T transition FL1120T1 10973168 10973168 C T transition FL1120T1 10973326 10973326 C T transition FL1120T1 10973351 10973351 C G transversion FL1120T1 10974195 10974195 C G transversion FL1120T2 10971546 10971546 C T transition FL1120T2 10972747 10972747 G A transition FL1120T2 10972782 10972782 G A transition FL1122T2 10972629 10972629 G A transition FL1122T2 10972783 10972783 C T transition FL1122T2 10973108 10973108 C G transversion FL1127T1 10974148 10974148 G C transversion FL1127T1 10974384 10974384 G A transition FL1127T1 10974905 10974905 T A transversion FL1127T1 10974918 10974918 G C transversion FL1127T1 10975051 10975051 A G transition FL1128T1 10972419 10972419 G C transversion FL1128T1 10972422 10972422 A G transition FL1128T1 10972740 10972740 G A transition FL1128T1 10973205 10973205 C T transition FL1128T2 10972419 10972419 G C transversion FL1128T2 10972422 10972422 A G transition FL1128T2 10972740 10972740 G A transition FL1128T2 10973103 10973103 C T transition FL1128T2 10973205 10973205 C T transition FL1128T2 10973691 10973691 C T transition  172 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1130T2 10971903 10971903 C T transition FL1130T2 10971990 10971990 C T transition FL1130T2 10972338 10972338 C T transition FL1130T2 10972570 10972570 G A transition FL1130T2 10972777 10972777 G C transversion FL1130T2 10973277 10973277 G C transversion FL1132T1 10973115 10973115 T C transition FL1132T1 10973078 10973118  del deletion FL1132T1 10973118 10973118 C G transversion FL1132T1 10974841 10974841 C T transition FL1132T2 10973115 10973115 T C transition FL1132T2 10973078 10973118  del deletion FL1132T2 10973118 10973118 C G transversion FL1132T2 10974841 10974841 C T transition FL1134T1 10971467 10971467 G C transversion FL1134T1 10971989 10971989 G C transversion FL1134T1 10972482 10972482 G C transversion FL1134T1 10972870 10972870 G A transition FL1134T1 10973124 10973124 C T transition FL1134T2 10971467 10971467 G C transversion FL1134T2 10971545 10971545 G A transition FL1134T2 10971672 10971672 G A transition FL1134T2 10971921 10971921 G A transition FL1134T2 10971929 10971929 G C transversion FL1134T2 10972118 10972124  del deletion FL1134T2 10972364 10972364 C T transition FL1134T2 10972424 10972424 C T transition FL1134T2 10972577 10972577 G A transition FL1134T2 10973112 10973112 C T transition FL1134T2 10973315 10973315 C T transition FL1134T2 10973784 10973784 G T transversion FL1134T2 10973896 10973896 G A transition FL1134T2 10974175 10974175 G A transition FL1135T1 10973455 10973455 G A transition FL1135T2 10971672 10971672 G A transition FL1135T2 10971979 10971979 C T transition FL1135T2 10972013 10972013 G A transition FL1135T2 10972045 10972045 T A transversion FL1135T2 10972571 10972571 C G transversion FL1135T2 10973455 10973455 G A transition FL1135T2 10973479 10973479 T G transversion FL1135T2 10973492 10973492 G T transversion FL1135T2 10973610 10973610 G A transition FL1135T2 10973690 10973690 G A transition  173 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1135T2 10974565 10974565 C T transition FL1136T1 10973021 10973021 C T transition FL1136T2 10973021 10973021 C T transition FL1136T2 10975009 10975009 A G transition FL1140T1 10972926 10972926 C T transition FL1140T2 10971672 10971672 G A transition FL1140T2 10972299 10972299 G A transition FL1143T1 10971821 10971821 C T transition FL1143T1 10972733 10972733 C A transversion FL1143T1 10973690 10973690 G A transition FL1143T2 10971821 10971821 C T transition FL1143T2 10972322 10972322 G A transition FL1143T2 10972733 10972733 C A transversion FL1143T2 10972913 10972913 G T transversion FL1143T2 10973690 10973690 G A transition FL1145T1 10973257 10973257 C T transition FL1145T1 11002015 11002015 A G transition FL1147T1 10971318 10971318 T C transition FL1147T1 10971635 10971635 G A transition FL1147T1 10972019 10972019 C T transition FL1147T1 10972592 10972592 C A transversion FL1147T1 10972604 10972604 C A transversion FL1147T1 10972742 10972742 G C transversion FL1147T1 10972797 10972797 G C transversion FL1147T1 10972968 10972968 C G transversion FL1147T1 10973103 10973103 C T transition FL1147T1 10973695 10973695 G A transition FL1147T1 10974181 10974181 G A transition FL1147T2 10971318 10971318 T C transition FL1147T2 10971635 10971635 G A transition FL1147T2 10972592 10972592 C A transversion FL1147T2 10972604 10972604 C A transversion FL1147T2 10972742 10972742 G C transversion FL1147T2 10972797 10972797 G C transversion FL1147T2 10972968 10972968 C G transversion FL1147T2 10973695 10973695 G A transition FL1147T2 10974181 10974181 G A transition FL1148T1 10974902 10974902 G A transition FL1148T1 10974905 10974905 T A transversion FL1148T1 10974918 10974918 G C transversion FL1148T1 10974928 10974928 C T transition FL1148T1 10975061 10975061 A G transition FL1148T2 10974905 10974905 T C transition FL1148T2 10975061 10975061 A G transition  174 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1149T1 10972948 10972948 C T transition FL1149T1 10973019 10973019 T C transition FL1149T2 10973019 10973019 T C transition FL1149T2 10973312 10973312 G C transversion FL1149T2 10973690 10973690 G C transversion FL1150T1 10972311 10972311 C A transversion FL1150T1 10973411 10973411 G T transversion FL1150T2 10972311 10972311 C A transversion FL1150T2 10973411 10973411 G T transversion FL1153T1 10971989 10971989 G A transition FL1153T2 10971989 10971989 G A transition FL1160T1 10972397 10972397 C T transition FL1160T1 10973686 10973686 C G transversion FL1160T1 10974313 10974313 G A transition FL1160T2 10972397 10972397 C T transition FL1160T2 10973686 10973686 C G transversion FL1160T2 10974313 10974313 G A transition FL1162T1 10972846 10972846 G A transition FL1162T1 10974901 10974901 C T transition FL1162T2 10972846 10972846 G A transition FL1170T1 10975005 10975005 G T transversion FL1170T1 10975028 10975028 T C transition FL1175T1 10972719 10972719 G A transition FL1179T1 10972348 10972348 C T transition FL1179T1 10972448 10972460  del deletion FL1179T1 10972511 10972511 G C transversion FL1179T1 10972571 10972571 C T transition FL1179T1 10973314 10973314 G A transition FL1179T2 10971878 10971878 C G transversion FL1179T2 10971966 10971966 T G transversion FL1179T2 10973314 10973314 G A transition FL1188T1 10971525 10971525 C T transition FL1188T1 10998557 10998557 G A transition FL1188T2 10971470 10971470 C T transition FL1188T2 10998557 10998557 G A transition FL1189T2 10974008 10974008 G A transition FL1190T1 10972847 10972847 C G transversion FL1190T1 10974348 10974348 G A transition FL1192T1 10972311 10972311 C T transition FL1192T1 10973010 10973010 G C transversion FL1192T1 10973103 10973103 C A transversion FL1192T2 10971829 10971829 C T transition FL1192T2 10972311 10972311 C T transition FL1192T2 10973010 10973010 G C transversion  175 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1192T2 10973103 10973103 C A transversion FL1193T1 10972770 10972770 G T transversion FL1193T1 10972846 10972846 G A transition FL1194T1 10971520 10971520 G A transition FL1194T1 10971672 10971672 G A transition FL1194T1 10971765 10971765 G A transition FL1194T1 10971834 10971834 C T transition FL1194T1 10971953 10971953 G C transversion FL1194T1 10972138 10972138 G C transversion FL1194T1 10972222 10972222 G A transition FL1194T1 10972252 10972253  ins insertion FL1194T1 10972254 10972255  ins insertion FL1194T1 10972257 10972258  ins insertion FL1194T1 10972251 10972260  del deletion FL1194T1 10972314 10972314 C T transition FL1194T1 10972364 10972364 C T transition FL1194T1 10972423 10972423 G A transition FL1194T1 10972522 10972522 C T transition FL1194T1 10972573 10972573 C T transition FL1194T1 10972596 10972596 G A transition FL1194T1 10972599 10972599 C G transversion FL1194T1 10972633 10972633 C T transition FL1194T1 10972651 10972651 C T transition FL1194T1 10972694 10972694 C T transition FL1194T1 10972742 10972742 G A transition FL1194T1 10972797 10972797 G C transversion FL1194T1 10972818 10972818 G A transition FL1194T1 10972840 10972846  del deletion FL1194T1 10972858 10972858 G C transversion FL1194T1 10972974 10972974 G C transversion FL1194T1 10973001 10973001 G A transition FL1194T1 10973014 10973014 G T transversion FL1194T1 10973089 10973089 C A transversion FL1194T1 10973092 10973092 G T transversion FL1194T1 10973123 10973123 G A transition FL1194T1 10973164 10973164 G C transversion FL1194T1 10973202 10973202 G A transition FL1194T1 10973204 10973204 G A transition FL1194T1 10973250 10973250 G A transition FL1194T1 10973351 10973351 C G transversion FL1194T1 10973533 10973533 C T transition FL1194T1 10973690 10973690 G C transversion FL1194T1 10973691 10973691 C T transition FL1194T1 10973713 10973713 C G transversion  176 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1194T1 10973829 10973829 C T transition FL1194T1 10973884 10973884 T A transversion FL1194T1 10973886 10973886 C G transversion FL1194T1 10974098 10974098 G A transition FL1194T1 10974424 10974424 C G transversion FL1194T2 10971450 10971450 G C transversion FL1194T2 10971520 10971520 G A transition FL1194T2 10971672 10971672 G A transition FL1194T2 10971765 10971765 G A transition FL1194T2 10971834 10971834 C T transition FL1194T2 10971953 10971953 G C transversion FL1194T2 10972138 10972138 G C transversion FL1194T2 10972222 10972222 G A transition FL1194T2 10972252 10972253  ins insertion FL1194T2 10972254 10972255  ins insertion FL1194T2 10972257 10972258  ins insertion FL1194T2 10972251 10972260  del deletion FL1194T2 10972314 10972314 C T transition FL1194T2 10972364 10972364 C T transition FL1194T2 10972423 10972423 G A transition FL1194T2 10972522 10972522 C T transition FL1194T2 10972573 10972573 C T transition FL1194T2 10972596 10972596 G A transition FL1194T2 10972599 10972599 C G transversion FL1194T2 10972633 10972633 C T transition FL1194T2 10972651 10972651 C T transition FL1194T2 10972694 10972694 C T transition FL1194T2 10972742 10972742 G A transition FL1194T2 10972797 10972797 G C transversion FL1194T2 10972818 10972818 G A transition FL1194T2 10972840 10972846  del deletion FL1194T2 10972858 10972858 G C transversion FL1194T2 10972974 10972974 G C transversion FL1194T2 10973001 10973001 G A transition FL1194T2 10973014 10973014 G T transversion FL1194T2 10973089 10973089 C A transversion FL1194T2 10973092 10973092 G T transversion FL1194T2 10973123 10973123 G A transition FL1194T2 10973202 10973202 G A transition FL1194T2 10973204 10973204 G A transition FL1194T2 10973250 10973250 G A transition FL1194T2 10973351 10973351 C G transversion FL1194T2 10973533 10973533 C T transition FL1194T2 10973690 10973690 G C transversion  177 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1194T2 10973691 10973691 C T transition FL1194T2 10973713 10973713 C G transversion FL1194T2 10973829 10973829 C T transition FL1194T2 10973884 10973884 T A transversion FL1194T2 10973886 10973886 C G transversion FL1194T2 10974098 10974098 G A transition FL1194T2 10974424 10974424 C G transversion FL1197T1 10972770 10972770 G A transition FL1197T1 10973058 10973058 C T transition FL1197T1 10973059 10973059 C T transition FL1197T2 10973058 10973058 C T transition FL1197T2 10973059 10973059 C T transition FL1198T1 10971672 10971672 G A transition FL1198T1 10971673 10971673 C T transition FL1198T1 10972215 10972215 C T transition FL1198T1 10972724 10972724 C T transition FL1198T1 10972726 10972726 C T transition FL1198T1 10972749 10972749 G A transition FL1198T1 10973436 10973436 G A transition FL1198T1 10973630 10973650  del deletion FL1198T2 10971545 10971545 G A transition FL1198T2 10971673 10971673 C T transition FL1198T2 10972082 10972082 G A transition FL1198T2 10972129 10972129 C T transition FL1198T2 10972215 10972215 C T transition FL1198T2 10972424 10972424 C T transition FL1198T2 10972724 10972724 C T transition FL1198T2 10972726 10972726 C T transition FL1198T2 10973184 10973184 G C transversion FL1198T2 10973320 10973320 C T transition FL1198T2 10973332 10973332 G A transition FL1198T2 10973372 10973372 G A transition FL1198T2 10973436 10973436 G A transition FL1202T1 10973677 10973677 G A transition FL1202T2 10973677 10973677 G A transition FL1211T2 10972562 10972562 G T transversion FL1211T2 10972975 10972975 C T transition FL1212T1 10972780 10972780 C T transition FL1212T1 10972847 10972847 C T transition FL1212T2 10972780 10972780 C T transition FL1212T2 10972847 10972847 C T transition FL1212T2 10974960 10974960 A G transition FL1216T1 10974901 10974901 C T transition FL1216T2 10974905 10974905 T C transition  178 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1218T1 10972968 10972968 C T transition FL1218T2 10972968 10972968 C T transition FL1219T2 11016378 11016378 A G transition FL1222T1 10973036 10973036 G T transversion FL1222T1 10998557 10998557 G A transition FL1222T2 10972522 10972522 C T transition FL1222T2 10973036 10973036 G T transversion FL1222T2 10973123 10973123 G A transition FL1222T2 10998557 10998557 G A transition FL1223T2 10974491 10974491 C G transversion FL1225T1 10973314 10973314 G A transition FL1225T1 10973814 10973814 G A transition FL1225T1 10974901 10974901 C T transition FL1225T1 10974905 10974905 T C transition FL1225T1 10975005 10975005 G T transversion FL1225T1 10975036 10975036 T C transition FL1225T2 10973314 10973314 G A transition FL1225T2 10973814 10973814 G A transition FL1233T1 10971672 10971672 G C transversion FL1233T1 10972082 10972082 G A transition FL1233T1 10972277 10972277 C A transversion FL1233T1 10972743 10972743 C T transition FL1233T1 10972750 10972750 C T transition FL1233T1 10972967 10972967 G A transition FL1233T1 10973021 10973021 C T transition FL1233T1 10973253 10973253 C T transition FL1233T1 10973685 10973685 G A transition FL1233T1 10974111 10974111 G A transition FL1233T1 10974397 10974397 G A transition FL1233T2 10972082 10972082 G A transition FL1233T2 10972277 10972277 C A transversion FL1233T2 10973253 10973253 C T transition FL1233T2 10973685 10973685 G A transition FL1233T2 10974111 10974111 G A transition FL1234T1 10971409 10971409 C T transition FL1234T1 10971673 10971673 C T transition FL1234T1 10971840 10971840 G T transversion FL1234T1 10971850 10971850 G C transversion FL1234T1 10972032 10972032 G C transversion FL1234T1 10972334 10972334 G T transversion FL1234T1 10972777 10972777 G A transition FL1234T1 10972933 10972933 G T transversion FL1234T1 10973020 10973020 G A transition FL1234T1 10973517 10973517 G A transition  179 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1234T1 10973588 10973588 G T transversion FL1234T1 10973691 10973691 C T transition FL1234T1 10973766 10973766 G C transversion FL1234T2 10971409 10971409 C T transition FL1234T2 10971673 10971673 C T transition FL1234T2 10971840 10971840 G T transversion FL1234T2 10971850 10971850 G C transversion FL1234T2 10972032 10972032 G C transversion FL1234T2 10972334 10972334 G T transversion FL1234T2 10972747 10972747 G C transversion FL1234T2 10972770 10972770 G A transition FL1234T2 10972777 10972777 G A transition FL1234T2 10972933 10972933 G T transversion FL1234T2 10973020 10973020 G A transition FL1234T2 10973123 10973123 G C transversion FL1234T2 10973691 10973691 C T transition FL1240T1 10974905 10974905 T C transition FL1246T1 10971820 10971820 G A transition FL1246T1 10972504 10972504 C T transition FL1246T1 10972846 10972846 G C transversion FL1246T1 10972967 10972967 G A transition FL1246T1 10973261 10973264  del deletion FL1246T1 10973752 10973752 G C transversion FL1246T2 10971820 10971820 G A transition FL1246T2 10972504 10972504 C T transition FL1246T2 10972846 10972846 G C transversion FL1248T1 10972129 10972129 C T transition FL1248T1 10972400 10972400 C T transition FL1248T1 10972461 10972461 C T transition FL1248T1 10972732 10972732 C A transversion FL1248T1 10972733 10972733 C A transversion FL1248T1 10972846 10972846  Del G deletion FL1248T1 10972952 10972952 G T transversion FL1248T1 10972968 10972968 C T transversion FL1248T1 10973123 10973123 G A transition FL1248T1 10973595 10973598  del deletion FL1248T1 10973900 10973900 G A transition FL1248T2 10972082 10972082 G C transversion FL1248T2 10972400 10972400 C T transition FL1248T2 10972486 10972486 G A transition FL1248T2 10972577 10972577 G A transition FL1248T2 10973096 10973096 C T transition FL1248T2 10973164 10973164 G A transition FL1248T2 10973285 10973285 G A transition  180 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1248T2 10973900 10973900 G A transition FL1248T2 10973980 10973980 A G transition FL1249T1 10972042 10972066  del deletion FL1249T2 10971940 10971940 G A transition FL1249T2 10972042 10972066  del deletion FL1250T1 10973103 10973103 C T transition FL1250T2 10973103 10973103 C T transition FL1254T1 10972682 10972682 C T transition FL1254T1 10972693 10972693 G A transition FL1254T1 10972780 10972780 C G transversion FL1254T2 10972682 10972682 C T transition FL1254T2 10972693 10972693 G A transition FL1254T2 10972780 10972780 C G transversion FL1255T1 10972765 10972765 G A transition FL1255T1 10972770 10972770 G A transition FL1255T1 10972780 10972780 C T transition FL1255T1 10973112 10973112 C T transition FL1255T2 10971672 10971672 G C transversion FL1255T2 10972513 10972513 G A transition FL1255T2 10972685 10972685 C A transversion FL1255T2 10972780 10972780 C T transition FL1255T2 10973014 10973014 G T transversion FL1255T2 10973718 10973718 G A transition FL1255T2 10973951 10973951 C G transversion FL1256T1 10972927 10972927 C T transition FL1256T2 11009406 11009406 C T transition FL1258T1 10973310 10973314  del deletion FL1258T2 10973310 10973314  del deletion FL1259T1 10971701 10971701 C T transition FL1259T1 10973277 10973277 G A transition FL1259T2 10971701 10971701 C T transition FL1259T2 10973277 10973277 G A transition FL1260T1 10972189 10972189 C G transversion FL1260T1 10972599 10972599 C G transversion FL1260T1 10972780 10972780 C T transition FL1260T1 10973837 10973837 G A transition FL1260T1 11010189 11010189 G A transition FL1260T2 10971672 10971672 G A transition FL1260T2 10972189 10972189 C G transversion FL1260T2 10972424 10972424 C T transition FL1260T2 10972456 10972456 G A transition FL1260T2 10972659 10972659 T A transversion FL1260T2 10972661 10972661 C A transversion FL1260T2 10972780 10972780 C T transition  181 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL1260T2 10972759 10972785  del deletion FL1260T2 10972733 10972786  del deletion FL1260T2 10973102 10973102 G A transition FL1260T2 10973468 10973468 G A transition FL1260T2 11010189 11010189 G A transition FL1261T1 10973686 10973686 C T transition FL1261T2 10974319 10974319 G A transition FL1262T1 10972178 10972178 A C transversion FL1262T1 10972208 10972208 G C transversion FL1262T1 10972461 10972461 C A transversion FL1262T1 10972571 10972571 C T transition FL1262T1 10973102 10973102 G A transition FL1262T2 10971999 10971999 G A transition FL1262T2 10972424 10972424 C G transversion FL1262T2 10972571 10972571 C T transition  B.4 Intron 1 alterations in pFL and npFL Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL2002T1 10972087 10972087 G A transition FL2002T1 10974524 10974536  del deletion FL2005T1 10973123 10973123 G C transversion FL2101T1 10972870 10972870 G A transition FL2101T1 10973082 10973082 C G transversion FL2101T1 10973084 10973084 A C transversion FL2101T1 10973686 10973686 C T transition FL2102T1 10971730 10971730 C A transversion FL2102T1 10972396 10972396 G A transition FL2102T1 10972472 10972472 G A transition FL2102T1 10973103 10973103 C T transition FL2104T1 10971828 10971828 G A transition FL2105T1 10971922 10971922 C T transition FL2108T1 10971690 10971690 G A transition FL2108T1 10972521 10972521 G A transition FL2108T1 10972886 10972886 C A transversion FL2110T1 11012426 11012426 G C transversion FL2114T1 10971789 10971789 G A transition FL2114T1 10972731 10972731 G A transition FL2114T1 10972967 10972967 G A transition FL2114T1 10973112 10973112 C G transversion FL2115T1 10973019 10973019 T C transition FL2115T1 10973900 10973900 G A transition FL2118T1 10971741 10971741 G A transition  182 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL2119T1 10973429 10973429 G A transition FL2119T1 10973588 10973588 G A transition FL2120T1 10971672 10971672 G C transversion FL2120T1 10971766 10971766 G A transition FL2120T1 10972675 10972675 G A transition FL2120T1 10973115 10973115 T G transversion FL2120T1 10973126 10973126 C T transition FL2120T1 10973128 10973128 G T transversion FL2120T1 10973551 10973551 G A transition FL2121T1 10971550 10971550 G A transition FL2121T1 10971808 10971808 G A transition FL2121T1 10971915 10971915 G A transition FL2121T1 10972138 10972138 G A transition FL2121T1 10972235 10972235 G A transition FL2121T1 10972334 10972334 G A transition FL2121T1 10972364 10972364 C T transition FL2121T1 10972365 10972365 C T transition FL2121T1 10972482 10972482 G A transition FL2121T1 10972546 10972546 A G transition FL2121T1 10972571 10972571 C T transition FL2121T1 10972718 10972718 T C transition FL2121T1 10972763 10972763 G C transversion FL2121T1 10972798 10972798 G A transition FL2121T1 10972846 10972846 G A transition FL2121T1 10973001 10973001 G A transition FL2121T1 10973111 10973111 G A transition FL2121T1 10973123 10973123 G A transition FL2121T1 10973372 10973372 G A transition FL2121T1 10973610 10973610 G A transition FL2121T1 10973678 10973678 C T transition FL2121T1 10973691 10973691 C T transition FL2121T1 10973759 10973759 C T transition FL2121T1 10973784 10973784 G A transition FL2122T1 10971829 10971829 C G transversion FL2122T1 10971953 10971953 G A transition FL2123T1 10972424 10972424 C T transition FL2125T1 10971954 10971954 C T transition FL2125T1 10972019 10972019 C T transition FL2125T1 10972096 10972096 G T transversion FL2125T1 10972266 10972266 C A transition FL2125T1 10972424 10972424 C T transition FL2125T1 10972494 10972494 C T transition FL2125T1 10972743 10972743 C A transversion FL2125T1 10972769 10972770  del 2 deletion FL2125T1 10973096 10973096 C T transition  183 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL2125T1 10973102 10973102 G A transition FL2125T1 10973111 10973111 G C transversion FL2125T1 10973685 10973685 G A transition FL2128T1 10975051 10975051 A G transition FL3001T1 10972679 10972679 C T transition FL3003T1 10972846 10972846 G A transition FL3003T1 10973107 10973107 G A transition FL3008T1 10973365 10973365 G A transition FL3009T1 10972247 10972247 G A transition FL3009T1 10972780 10972780 C T transition FL3009T1 10972933 10972933 G A transition FL3009T1 10972974 10972974 G A transition FL3009T1 10973437 10973437 G C transversion FL3009T1 10974205 10974205 T A transversion FL3010T1 10974928 10974928 C T transition FL3010T1 10974997 10974997 A G transition FL3013T1 10972192 10972192 C T transition FL3013T1 10972193 10972193 C T transition FL3013T1 10972846 10972846 G A transition FL3013T1 10972871 10972871 C T transition FL3015T1 10972571 10972571 C T transition FL3016T1 10972770 10972770 G T transversion FL3017T1 10972870 10972870 G A transition FL3018T1 10972255 10972255 C T transition FL3020T1 10972348 10972348 C T transition FL3020T1 10972396 10972396 G A transition FL3020T1 10972415 10972415 C G transversion FL3020T1 10972419 10972419 G A transition FL3020T1 10972679 10972679 C T transition FL3020T1 10972748 10972748 C A transversion FL3020T1 10972968 10972968 C G transversion FL3020T1 10973123 10973123 G A transition FL3020T1 10973264 10973265  del 2 deletion FL3020T1 10973332 10973332 G C transversion FL3020T1 10973368 10973373  del deletion FL3020T1 10973557 10973557 G A transition FL3020T1 10973615 10973615 C G transversion FL3020T1 10973797 10973797 C T transition FL3020T1 10973869 10973869  del G deletion FL3020T1 10974854 10974854 G A transition FL3102T1 10972635 10972635 G A transition FL3106T1 10972125 10972125 G A transition FL3106T1 10972247 10972247 G A transition FL3106T1 10972763 10972763 G A transition FL3110T1 10971492 10971492 C T transition  184 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL3111T1 10974538 10974538 C T transition FL3114T1 10971279 10971279 C G transversion FL3114T1 10971291 10971291 T C transition FL3114T1 10971337 10971337 G C transversion FL3114T1 10971398 10971398 T C transition FL3114T1 10971659 10971659 G C transversion FL3114T1 10971666 10971666 G A transition FL3114T1 10971667 10971667 G A transition FL3114T1 10971673 10971673 C G transversion FL3114T1 10971697 10971697 A C transversion FL3114T1 10971766 10971766 G T transversion FL3114T1 10971815 10971815 A C transversion FL3114T1 10971840 10971840 G A transition FL3114T1 10971903 10971903 C T transition FL3114T1 10971925 10971925 G T transversion FL3114T1 10971972 10971972 A G transition FL3114T1 10971979 10971979 C T transition FL3114T1 10972019 10972019 C G transversion FL3114T1 10972032 10972032 G C transversion FL3114T1 10972055 10972055 C G transversion FL3114T1 10972074 10972074 T A transversion FL3114T1 10972142 10972142 C G transversion FL3114T1 10972178 10972178 A T transversion FL3114T1 10972266 10972266 C G transversion FL3114T1 10972363 10972363 A G transition FL3114T1 10972397 10972397 C G transversion FL3114T1 10972462 10972462 C T transition FL3114T1 10972505 10972505 C G transversion FL3114T1 10972571 10972571 C T transition FL3114T1 10972668 10972668 C T transition FL3114T1 10972679 10972679 C T transition FL3114T1 10972993 10972993 G A transition FL3114T1 10973093 10973093 G A transition FL3114T1 10973351 10973351 C A transversion FL3114T1 10973433 10973433 A G transition FL3114T1 10973951 10973951 C G transversion FL3115T1 10975028 10975028 T C transition FL3115T1 10975051 10975051 A G transition FL3115T1 10975072 10975072 T G transversion FL3116T1 10971669 10971669 G A transition FL3116T1 10971672 10971672 G A transition FL3116T1 10972305 10972305 C T transition FL3116T1 10972521 10972521 G A transition FL3116T1 10972522 10972522 C T transition FL3116T1 10972968 10972968 C T transition  185 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL3116T1 10973315 10973315 C T transition FL3116T1 10973690 10973690 G C transversion FL3116T1 10974285 10974285 C G transversion FL3117T1 10971751 10971751 G C transversion FL3117T1 10972847 10972847 C G transversion FL3117T1 10973103 10973103 C T transition FL3117T1 10995609 10995609 G C transversion FL3118T1 10973120 10973120 A G transition FL3118T1 10973105 10973129  del deletion FL3120T1 10972716 10972716 C G transversion FL3120T1 10972895 10972895 C T transition FL3121T1 10972944 10972944 G C transversion FL3123T1 10973589 10973589 C T transition FL3124T1 10972424 10972424 C G transversion FL3124T1 10972521 10972521 G A transition FL3124T1 10972743 10972743 C T transition FL3124T1 10972898 10972898 C A transversion FL3124T1 10972967 10972967 G C transversion FL3124T1 10973124 10973124 C T transition FL3126T1 10971779 10971779 G A transition FL3126T1 10972277 10972277 C A transversion FL3126T1 10972461 10972461 C A transversion FL3126T1 10973123 10973123 G A transition FL3128T1 10972090 10972090 C T transition FL3128T1 10972316 10972316 G T transversion FL3128T1 10973372 10973372 G A transition FL3132T1 10973320 10973320 C G transversion FL3138T1 10971779 10971779 G A transition FL3138T1 10972409 10972409 G A transition FL3138T1 10972446 10972446 C G transversion FL3138T1 10972682 10972682 C G transversion FL3138T1 10972694 10972694 C T transition FL3138T1 10972770 10972770 G T transversion FL3138T1 10973675 10973675 G A transition FL3138T1 10974179 10974179 C T transition FL3138T1 10974620 10974620 G A transition FL3139T1 10972456 10972456 G A transition FL3140T1 10972032 10972032 G A transition FL3140T1 10972709 10972709 G A transition FL3140T1 10972847 10972847 C G transversion FL3141T1 10972570 10972570 G A transition FL3142T1 10972989 10972989 G A transition FL3144T1 10973551 10973551 G A transition FL3145T1 10972019 10972019 C T transition FL3145T1 10972967 10972967 G A transition  186 Case # SNV or indel Position Start (hg19) SNV or indel Position End (hg19) ref alt type of genetic alteration FL3145T1 10973103 10973103 C T transition FL3145T1 10973712 10973712 G C transversion FL3145T1 10973717 10973717 G A transition FL3145T1 10973718 10973718 G A transition FL3147T1 10972494 10972494 C T transition FL3147T1 10972818 10972818 G A transition FL3147T1 10972915 10972915 C G transversion FL3147T1 10973074 10973074 C T transition FL3147T1 10973123 10973123 G C transversion FL3147T1 10973414 10973414 C G transversion FL3147T1 10974506 10974506 G A transition FL3148T1 10972926 10972926 C A transversion FL3148T1 10973061 10973061 C G transversion FL3148T1 10974617 10974617 G A transition FL3149T1 10972742 10972742 G A transition FL3150T1 10971537 10971537 G A transition FL3150T1 10971545 10971545 G A transition FL3152T1 10972019 10972019 C T transition FL3152T1 10972504 10972504 C T transition FL3152T1 10973756 10973756 G A transition FL3155T1 10971711 10971711 C T transition FL3156T1 10972775 10972775 A G transition FL3156T1 10972776 10972776 A G transition FL3156T1 10972780 10972780 C A transversion FL3156T1 10973061 10973061 C G transversion FL3156T1 10973829 10973829 C T transition FL3157T1 10972660 10972660 G A transition FL3157T1 10972900 10972900 G A transition FL3162T1 10972255 10972255 C T transition FL3162T1 10972305 10972305 C T transition FL3162T1 10972770 10972770 G A transition FL3162T1 10972895 10972895 C T transition FL3162T1 10974631 10974631 G T transversion FL3163T1 10973257 10973257 C T transition FL3163T1 10973315 10973315 C T transition FL3166T1 10972415 10972415 C T transition     187 B.5 High confidence predictions for the chromosome 16 capture space Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43029 INV 16 11201073 CLEC16A 16 11785708 TXNDC11 67 8 584 kb inversion, breakpoints in intron 18 of CLEC16A and exon 8 of TXNDC11, likely disruptive, functional impact unclear A43030 DEL 16 10947070 CIITA 16 11116222 CLEC16A 38 4 169 kb deletion, breakpoints upstream of CIITA and in intron 11 of CLEC16A, complete loss of this CIITA allele INV 16 11348882 SOCS1 16 11351572 SOCS1 14 3 breakpoint in exon 2 of SOCS1 and upstream of the SOCS1 gene, disrupts SOCS1 TRA 14 106326048 IGH 16 11349135 SOCS1 19 2 t(14;16), breakpoints in IGH intronic region and SOCS1 exon 2 , strand direction different, therefore no fusion, disruption of SOCS1, effect on IGH locus unclear A43031 INV 16 11013706 CIITA 16 11033187 DEXI 149 8 19 kb inversion, breakpoints in intron 16 of CIITA and intron 1 of DEXI, fuses CIITA exon 1-16 to DEXI exon 2, the latter is non-coding but a putative fusion protein can be derived (B.6) INV 16 11013709 CIITA 16 11033083 DEXI 110 7 reciprocal event, stop codon in exon 1 of DEXI, creates no fusion with CIITA exon 17-19  188 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43036 INV 16 10972119 CIITA 16 11349103 SOCS1 144 6 377 kb inversion, breakpoints in intron 1 of CIITA and exon 2 of SOCS1, likely disruptive for both genes INV 16 10972127 CIITA 16 11349114 SOCS1 65 4 reciprocal event TRA 16 10972522 CIITA X 41548791 GPR34 68 6 t(X;16), breakpoints in CIITA intron 1 and GPR34 intron 1, putative fusion of CIITA exon 1 to GPR34 exon 2, 51 aa protein predicted (B.7), likely non-functional TRA 16 10972530 CIITA X 41548793 GPR34 70 2 reciprocal event, t(X;16), small ORFs, non-functional DEL 16 10972770 CIITA 16 10973118 CIITA 112 4 347 bp deletion CIITA intron 1 A43037 DEL 16 10973706 CIITA 16 10972948 CIITA 252 6 757 bp deletion intron 1 CIITA INV 16 11062836 CLEC16A 16 57168099 CPNE2 234 6 nested inversion, pericentric, breakpoints in exon 4 of CLEC16A and intron 12 of CPNE2, strand direction different, therefore no fusion INV 16 11063029 CLEC16A 16 30683452 FBRS 148 6 nested inversions INV 16 10537483 ATF7IP2 16 11080769 CLEC16A 36 6 nested inversions INV 16 11110612 CLEC16A 16 28448129 EIF3C 217 3 nested inversions INV 16 11059965 CLEC16A 16 21428484 NPIPL3 18 2 nested inversions DUP 16 11106289 CLEC16A 16 21748652 OTOA 10 2 duplication, functional impact unclear A43043 DEL 16 10972316 CIITA 16 10972128 CIITA 94 4 187 bp deletion CIITA intron 1 A43049 INV 16 3056935 CLDN6 16 10966595 CIITA 21 8 8 Mb inversion, breakpoints upstream of CLDN6 and upstream of CIITA, results in dislocation of the green BAC probe but no structural damage to CIITA   189 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43050 DEL 16 10972395 CIITA 16 10973044 CIITA 108 6 648 bp deletion CIITA intron 1, FISH not explained but apparently small clone (5 %) A43051 DEL 16 7638085 RBFOX1 16 10972040 CIITA 19 5 3.3 Mb deletion, breakpoints in intron 4 of RBFOX1 and intron 1 of CIITA, leads to fusion of RFBOX1 exon 4 to exon 2 of CIITA (B.8), resulting in a truncated protein A43052 TRA 2 61108467 REL 16 10974031 CIITA 21 8 t(2;16), breakpoints in CIITA intron 1 and upstream of REL, fusion transcript possible (CIITA exon 1 to REL exon 2) TRA 2 61108477 REL 16 10974001 CIITA 13 7 reciprocal event TRA 2 89159665 IGK 16 10972714 CIITA 15 6 t(2;16), breakpoints in CIITA intron 1 and centromeric on chromosome 2, close to IGK gene region DEL 16 10973286 CIITA 16 10972769 CIITA 13 2 516 bp deletion CIITA intron 1 A43067 INV 16 10973601 CIITA 16 27326617 IL4R 39 6 16 Mb inversion, breakpoints in CIITA intron 1 and IL4R intron 1, same strand direction, therefore no fusion transcript upon inversion, likely disruptive INV 16 10973610 CIITA 16 27326640 IL4R 16 6 reciprocal event A43068 DEL 16 10962704 CIITA 16 11310352 CLEC16A 54 8 348 kb deletion, deletes CIITA, DEXI and CLEC16A entirely TRA 14 106211708 IGHG1 16 11348887 SOCS1 28 3 t(14;16), breakpoints in IGH intron 1 and SOCS1 exon 2, different chromosome arms, same strand direction, therefore no fusion, disrupts SOCS1, effect on IGH locus unclear TRA 14 106213380 IGHG1 16 11348899 SOCS1 106 3 reciprocal event  190 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43069 TRA 16 10973113 CIITA 22 39854860 MGAT3 55 6 t(16;22), breakpoints in intron 1 of CIITA and intron 1 of MGAT3, different chromosome arms, same strand direction, therefore no fusion, likely disruptive TRA 16 10973113 CIITA 22 39854856 MGAT3 40 6 reciprocal event A43070 DEL 16 10983031 CIITA 16 11812699 TXNDC11 41 8 830 kb deletion, breakpoints in CIITA intron 1 and TXNDC11 intron 5, different strand directions, therefore no fusion transcript TRA 1 2985148 PRDM16 16 10972750 CIITA 102 5 t(1:16), breakpoints in CIITA exon 1 and upstream of PRDM16, results in fusion of CIITA exon 1 to PRDM16 exon 2 TRA 1 2984655 PRDM16 16 10972919 CIITA 56 8 reciprocal event translocation CIITA intron 1 and upstream of PRDM16, no promoter swap, disruption of CIITA allele DEL 16 11215236 CLEC16A 16 11480301 RMI2 26 3 265 kb deletion, breakpoints in intron 19 of CLEC16A and downstream of RMI2 DEL 16 11215210 CLEC16A 16 11480299 RMI2 24 2 reciprocal event INV 16 11215206 CLEC16A 16 11480274 RMI2 19 2 265 kb inversion, breakpoints in intron 19 of CLEC16A and downstream of RMI2 A43071 DEL 16 10756488 TEKT5 16 11339356 SOCS1 21 7 417 kb deletion, deletes CIITA allele A43072 DEL 16 10861924 NUBP1 16 10996431 CIITA 73 8 134 kb deletion, breakpoints in NUBP1 intron 9 and CIITA intron 1, creates in-frame fusion transcript NUBP1 exon 9 - CIITA exon 8  191 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43075 DEL 16 11349240 SOCS1 16 11348417 SOCS1 90 7 800 bp deletion SOCS1 TRA 16 8762984 AICDA 12 10973366 CIITA 48 6 t(12;16), breakpoints in CIITA intron1 and AICDA intron 1, same chromosome arms, different strand direction, therefore no fusion transcript TRA 12 8764607 AICDA 16 10973178 CIITA 133 5 reciprocal event A43076 INV 16 11037301 CLEC16A 16 11352433 RMI2 40 7 315 kb inversion involves CLEC16A DEL 16 10982313 CIITA 16 12374408 SNX29 20 6 1.4 Mb deletion, breakpoints in CIITA intron 1 and SNX29 intron 15, putative 29 aa fusion transcript (B.9) DUP 16 10972350 CIITA 16 10972662 CIITA 45 4 300 bp duplication intron 1 CIITA A43077 DEL 16 10972806 CIITA 16 12062507 TNFRSF17 81 6 1 Mb deletion, breakpoints in CIITA intron 1 and downstream of TNFRSF17 A43078 TRA 8 128808741 PVT1 16 10972594 CIITA 90 4 t(8;16), breakpoints in CIITA intron 1 and PVT1 intron 1, different chromosome arms, same strand direction, therefore no fusion transcript TRA 8 128808716 PVT1 16 10972569 CIITA 39 3 reciprocal event DEL 16 10972600 CIITA 16 10972919 CIITA 55 2 318 bp deletion CIITA intron 1  192 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43079 TRA 10 46794179 CTSL1P5 16 10972823 CIITA 18 2 t(10;16) TRA 10 48989246 GLUD1P7 16 10972800 CIITA 146 7 t(10;16) DEL 16 10973892 CIITA 16 10973408 CIITA 189 6 483 bp deletion intron 1 CIITA TRA 14 106325853 IGH 16 11349095 SOCS1 29 4 t(14;16), breakpoints in IGH and SOCS1 exon 2, different chromosome arms, same strand direction, therefore no fusion, disrupts SOCS1, effect on IGH locus unclear A43080 DEL 16 11348838 SOCS1 16 10973122 CIITA 195 8 375 kb deletion, breakpoints in intron 1 CIITA and SOCS1 exon 2 DEL 16 10972446 CIITA 16 10971699 CIITA 106 8 752 bp deletion intron 1 CIITA A43081 DEL 16 10973504 CIITA 16 10971906 CIITA 21 5 401 bp deletion intron 1 CIITA DEL 16 10972143 CIITA 16 10971940 CIITA 12 4 202 bp deletion intron 1 CIITA INV 16 10972733 CIITA 16 10973111 CIITA 17 3 367 bp inversion CIITA intron 1 INV 16 10973005 CIITA 16 10972714 CIITA 18 3 reciprocal event  A43082 DEL 16 10972338 CIITA 16 10972492 CIITA 28 2 153 bp deletion intron 1 CIITA DEL 16 11349550 SOCS1 16 11349119 S 45 6 175 bp deletion intron 1 CIITA DEL 16 10972737 CIITA 16 10972561 CIITA 29 2 281 bp deletion intron 1 CIITA DEL 16 10972598 CIITA 16 10972316 CIITA 20 2 281 bp deletion intron 1 CIITA A43084 DEL 16 10972598 CIITA 16 10972316 CIITA 97 2 752 bp deletion intron 1 CIITA A43090 DEL 16 11180645 CLEC16A 16 11179301 CLEC16A 70 8 1.3 kb deletion CLEC16A intron 18 DEL 16 11348970 SOCS1 16 11348503 SOCS1 16 4 ~470 bp deletion SOCS1 exon 2 - 3'UTR  193 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43092 TRA 8 128749207 MYC 16 11349139 SOCS1 23 7 translocation intron 1 MYC, exon 2 SOCS1, likely no splice donor/acceptor, disruption of SOCS1 TRA 8 128749148 MYC 16 11349126 SOCS1 13 4 reciprocal event A43093 DEL 16 10975142 CIITA 16 10973558 CIITA 80 8 1.5 kb deletion CIITA intron 1 INV 16 10971536 CIITA 16 10972727 CIITA 90 6 1.2 kb inversion CIITA intron 1 INV 16 10971870 CIITA 16 10972644 CIITA 83 3 773 bp inversion CIITA intron 1 DUP 16 10972945 CIITA 16 10973145 CIITA 35 2 199 bp duplication CIITA intron 1 A43094 DEL 16 11348834 SOCS1 16 9992019 GRIN2A 111 7 del 16p 1.3 Mb, intron 3 of GRIN2A to exon 2 of SOCS1 A43095 DEL 16 10974070 CIITA 16 10972127 CIITA 20 6 2 kb deletion CIITA intron 1 DEL 16 11349373 SOCS1 16 11348681 SOCS1 85 5 296 bp deletion CIITA intron 1 DEL 16 10972312 CIITA 16 10972015 CIITA 76 5 185 bp inversion CIITA intron 1 INV 16 10973186 CIITA 16 10973372 CIITA 66 3 reciprocal event INV 16 10973169 CIITA 16 10973376 CIITA 37 3 262 bp deletion CIITA intron 1 DEL 16 10974698 CIITA 16 10974425 CIITA 83 2 2 kb deletion CIITA intron 1 A43097 DEL 16 10971998 CIITA 16 10971586 CIITA 138 5 411 bp deletion CIITA intron 1 A43101 INV 16 10971827 CIITA 16 10973681 CIITA 52 6 ~1.8 kb inversion CIITA intron 1 INV 16 10971821 CIITA 16 10973687 CIITA 36 5 reciprocal event A43110 DEL 16 11143548 CLEC16A 16 10810673 NUBP1 63 7 333 kb deletion of NUBP1, CIITA, DEXI and parts of CLEC16A  194 Library ID SV type chr1 position1 gene1 chr2 position2 gene2 max spanning reads num events interpretation of chr16         oligocapture results A43115 DEL 16 10973158 CIITA 16 10972963 CIITA 141 5 194 bp deletion intron 1 CIITA INV 16 10971282 CIITA 16 10971688 CIITA 251 3 405 bp inversion in CIITA intron 1 INV 16 10971301 CIITA 16 10971709 CIITA 236 3 reciprocal event DEL 16 11349494 SOCS1 16 11349402 SOCS1 25 3  TRA 7 128309229 FAM71F2 16 10980174 CIITA 15 2 t(7:16) breakpoints in CIITA intron 1 and upstream of FAM71F2, different chromosome arms, same reading direction, no fusion A43117 DEL 16 10973536 CIITA 16 10972620 CIITA 349 6 915 bp deletion CIITA intron 1 Abbreviations: aa, amino acid; BAC, bacterial artificial chromosome; chr, chromosome; N, not validated; N*, not validated because of limited material or PCR failure; num, number; ORF, open reading frame; SV, structural variant; Val, validation; Y, validated; Y*, validated, but different mapping  195 B.6 Putative fusion transcript A43031  MRCLAPRPAG SYLSEPQGSS QCATMELGPL EGGYLELLNS DADPLCLYHF YDQMDLAGEE EIELYSEPDT DTINCDQFSR LLCDMEGDEE TREAYANIAE LDQYVFQDSQ LEGLSKDIFK HIGPDEVIGE SMEMPAEVGQ KSQKRPFPEE LPADLKHWKP AEPPTVVTGS LLVGPVSDCS TLPCLPLPAL FNQEPASGQM RLEKTDQIPM PFSSSSLSCL NLPEGPIQFV PTISTLPHGL WQISEAGTGV SSIFIYHGEV PQASQVPPPS GFTVHGLPTS PDRPGSTSPF APSATDLPSM PEPALTSRAN MTEHKTSPTQ CPAAGEVSNK LPKWPEPVEQ FYRSLQDTYG AEPAGPDGIL VEVDLVQARL ERSSSKSLER ELATPDWAER QLAQGGLAEV LLAAKEHRRP RETRVIAVLG KAGQGKSYWA GAVSRAWACG RLPQYDFVFS VPCHCLNRPG DAYGLQDLLF SLGPQPLVAA DEVFSHILKR PDRVLLILDG FEELEAQDGF LHSTCGPAPA EPCSLRGLLA GLFQKKLLRG CTLLLTARPR GRLVQSLSKA DALFELSGFS MEQAQAYVMR YFESSGMTEH QDRALTLLRD RPLLLSHSHS PTLCRAVCQL SEALLELGED AKLPSTLTGL YVGLLGRAAL DSPPGALAEL AKLAWELGRR HQSTLQEDQF PSADVRTWAM AKGLVQHPPR AAESELAFPS FLLQCFLGAL WLALSGEIKD KELPQYLALT PRKKRPYDNW LEGVPRFLAG LIFQPPARCL GALLGPSAAA SVDRKQKVLA RYLKRLQPGT LRARQLLELL HCAHEAEEAG IWQHVVQELP GRLSFLGTRL TPPDAHVLGK ALEAAGQDFS LDLRSTGICP SGLGSLVGLS CVTRFRAALS DTVALWESLQ QHGETKLLQA AEEKFTIEPF KAKSLKDVED LGKLVQTQRT RSSSEDTAGE LPAVRDLKKL EFALGPVSGP QAFPKLVRIL TAFSSLQHLD LDALSENKIG DEGVSQLSAT FPQLKSLETL NLSQNNITDL GAYKLAEALP SLAASLLRLR PAPLKSFVPT ERFLFEPRRV EERLGLSAEV GKAPAPTEGG TQEASQDLIC LQCQIDGLAL ASDYLQLRWM FTGTQPEFAS LHFIPERTCF PHFTFGEDTS NCGHTQKRLP APFDVSSTOP  B.7 Putative fusion transcript A43036  MRCLAPRPAG SYLSEPQAVN AILKHALNRF SHYQVKLKTV KGCDYYQIGK ISTOP  B.8 Putative fusion transcript A43051  MLASQGVLLH PYGVPMIVPA APYLPGLIQG NQEAAAAPDT MAQPYASAQF APPQNGIPAE YTAPHPHPAP EYTGQTTVPE HTLNLYPPAQ THSEQSPADT SAQTVSGTAT QTDDAAPTDG QPQTQPSENT ENKSQPKRLH VSNIPFRFRD PDLRQMFGQF GKILDVEIIF NERGSKAAHS VPPWSWGPSTOP  B.9 Putative fusion transcript A43076  MRCLAPRPAG SYLSEPQGGR DAWRADSTOP  

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