Medicine, Faculty of
Medical Genetics, Department of
DSpace
UBCV
Mufti, Kheireddin
Doctor of Philosophy - PhD
University of British Columbia
Vincristine is a cornerstone chemotherapeutic agent widely used for the treatment of various pediatric cancers. However, its clinical utility is often compromised by the occurrence of vincristine-induced peripheral neuropathy, which significantly impacts quality of life due to pain and disability, and may require dose reduction, treatment delays or discontinuation that increases the risk of relapse. While several studies have identified genetic factors that are associated with vincristine peripheral neuropathy risk, these variants do not fully explain the variability in the risk of this reaction, and the clinical relevance of many variants remains unclear. As result, there are currently no established predictors of peripheral neuropathy risk prior to the start of vincristine treatment. This dissertation aims therefore to identify, and validate, novel genomic markers of vincristine-induced neuropathy in pediatric cancer patients. A systematic review of existing genetic associations with vincristine-induced peripheral neuropathy was performed and demonstrated that variations in genes implicated in vincristine pharmacokinetics, pharmacodynamics, and neuropathy-related pathways are associated with vincristine-induced peripheral neuropathy susceptibility. Among these, the CEP72 rs924607 gene variant emerged as the most robustly supported variant influencing neuropathy risk. I subsequently conducted a genome-wide association study uncovering 13 novel genomic variants significantly associated with vincristine neuropathy risk or protection. Of these, I successfully validated two variants an independent replication cohort. Notably, patients carrying protective variants in both NRG3 and ACTN1 genes exhibited a substantial reduction in neuropathy incidence over time (HR=0.36, 95% CI: 0.124–0.602; p<0.001). A follow-up pathway analysis revealed involvement of four key pathways, including nerve development, nerve myelination, neuronal transmission, and cytoskeleton/microfibril functions-related pathways. Finally, a targeted analysis of the CEP72 rs924607 variant was conducted in a subset group of patients revealing its association with significant increase in neuropathy risk following prolonged vincristine therapy (OR=3.457, 95% CI: 1.143-10.45; p=0.028). These findings present potential actionable genomic markers of vincristine-induced neuropathy and offer opportunities for tailored interventions to improve vincristine safety in children with cancer. Overall, the work discussed in this dissertation contributes to expanding the existing vincristine pharmacogenomic literature and provides needed insights into the underlying pathology of vincristine-induced peripheral neuropathy reaction in pediatric oncology patients.
PHARMACOGENOMIC STUDY OF VINCRISTINE-INDUCED PERIPHERAL NEUROPATHY IN PATIENTS WITH PEDIATRIC CANCERS by Kheireddin Mufti B.Pharm., University of Aleppo, 2016 M.Sc., McGill University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2025 © Kheireddin Mufti, 2025ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Pharmacogenomic study of vincristine-induced peripheral neuropathy in patients with pediatric cancers Examining Committee: Bruce Carleton, Professor, Department of Pediatrics, UBC Supervisor Jan Friedman, Professor, Department of Medical Genetics, UBC Supervisory Committee Member Steven Miller, Professor, Department of Pediatrics, UBC University Examiner Michael Cox, Professor, Department of Experimental Medicine, UBC University Examiner Additional Supervisory Committee Members: Colin Ross, Professor, Department of Medical Genetics, UBC Co-supervisor S. Rod Rassekh, Clinical Associate Professor, Department of Pediatrics, UBC Supervisory Committee Member William Gibson, Professor, Department of Medical Genetics, UBC Supervisory Committee Member submitted by Kheireddin Mufti in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Medical Genetics iii Abstract Vincristine is a cornerstone chemotherapeutic agent widely used for the treatment of various pediatric cancers. However, its clinical utility is often compromised by the occurrence of vincristine-induced peripheral neuropathy, which significantly impacts quality of life due to pain and disability, and may require dose reduction, treatment delays or discontinuation that increases the risk of relapse. While several studies have identified genetic factors that are associated with vincristine peripheral neuropathy risk, these variants do not fully explain the variability in the risk of this reaction, and the clinical relevance of many variants remains unclear. As result, there are currently no established predictors of peripheral neuropathy risk prior to the start of vincristine treatment. This dissertation aims therefore to identify, and validate, novel genomic markers of vincristine-induced neuropathy in pediatric cancer patients. A systematic review of existing genetic associations with vincristine-induced peripheral neuropathy was performed and demonstrated that variations in genes implicated in vincristine pharmacokinetics, pharmacodynamics, and neuropathy-related pathways are associated with vincristine-induced peripheral neuropathy susceptibility. Among these, the CEP72 rs924607 gene variant emerged as the most robustly supported variant influencing neuropathy risk. I subsequently conducted a genome-wide association study uncovering 13 novel genomic variants significantly associated with vincristine neuropathy risk or protection. Of these, I successfully validated two variants an independent replication cohort. Notably, patients carrying protective variants in both NRG3 and ACTN1 genes exhibited a substantial reduction in neuropathy incidence over time (HR=0.36, 95% CI: 0.124–0.602; p<0.001). A follow-up pathway analysis revealed involvement of four key pathways, including nerve development, nerve myelination, iv neuronal transmission, and cytoskeleton/microfibril functions-related pathways. Finally, a targeted analysis of the CEP72 rs924607 variant was conducted in a subset group of patients revealing its association with significant increase in neuropathy risk following prolonged vincristine therapy (OR=3.457, 95% CI: 1.143-10.45; p=0.028). These findings present potential actionable genomic markers of vincristine-induced neuropathy and offer opportunities for tailored interventions to improve vincristine safety in children with cancer. Overall, the work discussed in this dissertation contributes to expanding the existing vincristine pharmacogenomic literature and provides needed insights into the underlying pathology of vincristine-induced peripheral neuropathy reaction in pediatric oncology patients. v Lay Summary Adverse reactions to chemotherapy can lead to significant long-term consequences for patients undergoing childhood cancer treatment. More specifically, children treated with vincristine chemotherapy often develop severe neurological reactions including pain and challenges with walking. The overall goal of this dissertation was to identify genetic markers for this adverse reaction to enhance our understanding of its underlying physiology, improve risk prediction, and ultimately enable personalized treatment through genetic testing. This research uncovered and validated several genetic variations related to specific nerve-related pathways that underly the pathology of vincristine-induced neurological reactions in patients undergoing vincristine therapy. Overall, this dissertation contributes to advancing the understanding of vincristine-induced neurological reactions and lays the groundwork for future efforts to improve patient outcomes. This work has the potential to enhance the prediction and prevention of this adverse reaction, ultimately improving quality of life of children undergoing cancer treatment. vi Preface This dissertation has been prepared following the guidelines provided by the Faculty of Graduate and Postdoctoral Studies at University of British Columbia. The work presented in this thesis was authored by Kheireddin Mufti, under the guidance, revision and input from Drs. Bruce Carleton, Colin Ross, Jan Friedman, William Gibson and Rod Rassekh in collaboration with the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). Ethical approval for all studies was obtained from the University of British Columbia Children’s and Women’s Research Ethics Board (reference number: H04-70358). The trial is registered with ClinicalTrials.gov and is publicly accessible under the registry name “National Active Surveillance Network and Pharmacogenomics of Adverse Drug Reactions in Children” and registration number NCT00414115, registered on December 21, 2006. Written informed consent and/or assent were obtained from all patients or their parents/legal guardians/substitute decision-maker prior to study enrollment. The content of Chapter 3 has been published as a peer-reviewed manuscript and has been adapted from: © Mufti K, Cordova M, Scott EN, Trueman JN, Lovnicki JM, Loucks CM, Rassekh SR, Ross CJD, and Carleton BC. Genomic variations associated with risk and protection against vincristine-induced peripheral neuropathy in pediatric cancer patients. NPJ Genomic Medicine, 9(1): 56 (2024). https://www.nature.com/articles/s41525-024-00443-7. The work discussed in this chapter was authored by me, and I was responsible for all major areas of concept formation, data analysis, as well as manuscript composition. Drs. Bruce Carleton and vii Colin Ross were the supervisory authors, and all the co-authors contributed to manuscript revisions. Chapter 3 has also been published as two conference papers: Mufti K, Scott E, Cordova-Delgado M, Trueman J, Lovnicki J, Loucks C, Rassekh S, Ross C, Carleton BC. Genetic variations related to nerve myelination and synapse assembly are associated with the risk of vincristine-induced peripheral neuropathy. In Pediatric Blood & Cancer. 2023 Nov 1 (Vol. 70, pp. S153-S154). Mufti K, Cordova-Delgado M, Scott E, Trueman J, Lovnicki J, Loucks C, Rassekh S, Ross C, Carleton BC. Genomic risk factors of vincristine-induced peripheral neuropathy. In Canadian Journal of Physiology and Pharmacology. 2024 Apr 1 (Vol. 102, pp. S1-S17). Chapters 2 and 4 are original and unpublished. Manuscript versions of these chapters are in preparation to be submitted for publication. I was the lead author, being responsible for concept development, data analysis and interpretation, as well as writing the manuscripts. I performed the article screening for the systematic review in Chapter 2 in collaboration with Spencer Anderson. Drs. Bruce Carleton and Colin Ross were the supervisory authors. Generative AI tool (ChatGPT) was used in this dissertation to help with refining the R codes I generated for propensity score matching and statistical analyses, and to improve the linguistic clarity and grammar of drafted text. All content, analyses, and interpretations – however – remain the original work of the authors. Throughout this thesis, I was responsible for all major areas of concept development, including developing the design and research analytical planviii alongside Drs. Bruce Carleton and Colin Ross, performing the grading of vincristine peripheral neuropathy reactions, conducting the case-control matching and quality control steps for both clinical and genomic data, calculating vincristine cumulative-dose-to-neuropathy in all cases, and closely analyzing treatment protocols and dose intensities to ensure comparable drug exposure in both case and control groups. Additionally, I was responsible for conducting all the statistical analyses of the clinical, physiological and demographic data, performing the primary and secondary genetic analyses for discovery and replication cohorts, including the genome-wide association analysis, replication analysis, pathway analysis, phenotypic analysis and meta-analyses, as well as interpreting the results and findings. ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................. v Preface ............................................................................................................................................vi Table of Contents ...........................................................................................................................ix List of Tables ................................................................................................................................ xii List of Figures .............................................................................................................................. xiii List of Abbreviations ..................................................................................................................... xv Acknowledge ...............................................................................................................................xviii Dedication ...................................................................................................................................... xx Chapter 1: General Introduction .................................................................................................... 1 1.1 Adverse Drug Reactions (ADRs) .............................................................................................. 1 1.2 ADRs in Pediatric Oncology ..................................................................................................... 2 1.3 Vincristine Chemotherapy ......................................................................................................... 4 1.3.1 Vincristine Mechanism of Action ..................................................................................... 4 1.3.2 Clinical Use of Vincristine ................................................................................................ 6 1.4 Vincristine-Induced Neuropathy ............................................................................................... 7 1.4.1 Types of Vincristine-Induced Neuropathy ......................................................................... 8 1.4.2 Pathophysiology of Vincristine-Induced Peripheral Neuropathy ....................................... 9 1.4.3 Clinical Characterization and Assessment ....................................................................... 12 1.4.4 Risk Factors of Vincristine-Induced Peripheral Neuropathy ............................................ 13 1.4.5 Current Treatment and Prevention/Therapeutic Implications ........................................... 17 1.5 Pharmacogenetic and Pharmacogenomic Studies ..................................................................... 20 1.6 Thesis Hypothesis and Objectives ........................................................................................... 22 CHAPTER 2: Pharmacogenomic Factors of Vincristine-induced peripheral neuropathy in Patients with Childhood Cancers: A Systematic Review ....................................................... 24 2.1 Introduction ............................................................................................................................ 24 2.2 Objectives ............................................................................................................................... 26 2.3 Methods .................................................................................................................................. 27 2.3.1 Literature Search Strategy............................................................................................... 27 2.3.2 Eligibility Criteria........................................................................................................... 28 2.3.3 Study Screening and Data Collection .............................................................................. 29 ix 2.3.4 Data Synthesis ................................................................................................................ 30 2.4 Results .................................................................................................................................... 30 2.4.1 Literature Search Results and Study Selection ................................................................ 30 2.4.2 Study Characteristics ...................................................................................................... 33 2.4.3 Overview of Studied Genes ............................................................................................ 37 2.4.4 Summary of Significant Genetic Variants ....................................................................... 41 2.5 Discussion .............................................................................................................................. 46 2.6 Conclusion .............................................................................................................................. 53 CHAPTER 3: Genomic Variations Associated with Risk and Protection Against Vincristine-induced peripheral neuropathy in Pediatric Cancer Patients ............................................... 55 3.1 Introduction ............................................................................................................................ 55 3.2 Methods .................................................................................................................................. 56 3.2.1 Patient Recruitment and Characterization ....................................................................... 56 3.2.2 Genotyping and Quality Control ..................................................................................... 61 3.2.3 Statistical Analyses ......................................................................................................... 62 3.3 Results .................................................................................................................................... 63 3.3.1 Patient Characteristics .................................................................................................... 63 3.3.2 Cohort Exclusions ......................................................................................................... 65 3.3.3 Multivariable Analysis and Confounding Variables ....................................................... 65 3.3.4 Time to Neuropathy ....................................................................................................... 66 3.3.5 Genome-Wide Analysis ................................................................................................. 68 3.3.6 Pathway Analysis .......................................................................................................... 71 3.4 Discussion .............................................................................................................................. 74 CHAPTER 4: Validation of Genome Wide Association Analysis Results ................................... 82 4.1 Introduction ............................................................................................................................ 82 4.2 Methods .................................................................................................................................. 83 4.2.1 Patients and Clinical Assessment .................................................................................... 83 4.2.2 Statistical and Genetic Analyses ..................................................................................... 86 4.3 Results .................................................................................................................................... 87 4.3.1 Patient Characteristics .................................................................................................... 87 4.3.2 Replication of Genetic Associations with Vincristine Peripheral Neuropathy .................. 89 xi 4.3.3 Phenotypic Sub-Analysis of the Replicated Gene Variants .............................................. 91 4.3.4 Risk Stratification Using Replicated Genetic Variants..................................................... 92 4.4 Discussion .............................................................................................................................. 94 CHAPTER 5: Targeted CEP72 Gene Variant (rs924607) Analysis ............................................ 98 5.1 Introduction ............................................................................................................................ 98 5.2 Methods .................................................................................................................................. 99 5.2.1 Patient Inclusion/Exclusion Criteria ................................................................................ 99 5.2.2 Analysis of Clinical and Demographic Data .................................................................. 100 5.2.3 Genetic and Statistical Analysis .................................................................................... 100 5.2.4 Meta Analysis............................................................................................................... 101 5.3 Results .................................................................................................................................. 103 5.3.1 Patients Characteristics ................................................................................................. 103 5.3.2 Replication of CEP72 rs924607 Association with Vincristine Neuropathy .................... 105 5.4 Discussion ............................................................................................................................ 107 CHAPTER 6: General Discussion and Conclusions .................................................................. 109 6.1 Summary of Key Findings .................................................................................................... 110 6.2 Strength and Significance ...................................................................................................... 114 6.3 Limitations............................................................................................................................ 116 6.4 Future Directions .................................................................................................................. 118 6.5 Final Remarks ....................................................................................................................... 120 References .................................................................................................................................... 123 Appendices ................................................................................................................................... 157 Appendix A: Additional Tables and Figures .............................................................................. 157 xii List of Tables Table 2.1 Summary of characteristics of included studies ................................................................ 36 Table 2.2 Summary of statistically significant genetic associations with vincristine-induced peripheral neuropathy in the pediatric oncology population ............................................................. 44 Table 2.3. Ancestry-specific allele frequencies of variants associated with 3-fold increase/decrease of vincristine-induced peripheral neuropathy risk................................................................................. 49 Table 3.1 Clinical and demographic characteristics of the CPNDS pediatric patients ....................... 64 Table 3.2 SNPs associated with vincristine-induced peripheral neuropathy ...................................... 70 Table 3.3. Summary of the vincristine-induced peripheral neuropathy GWAS-nominated pathway analysis gene-sets ............................................................................................................................ 73 Table 4.1 Clinical and demographic characteristics of the replication cohort of CPNDS .................. 88 Table 4.2 Variants associated with vincristine-induced neuropathy risk in discovery and independent replication cohort ........................................................................................................................... 90 Table 5.1 Summary of studies investigated CEP72 (rs924607) for the risk of vincristine-induced neuropathy in pediatric cancer patients .......................................................................................... 102 Table 5.2 Clinical and demographic characteristics of the CPNDS pediatric patients ..................... 104 Table A1. Non-significant genetic associations with vincristine-induced peripheral neuropathy in patients with pediatric cancers ................................................................................................. 157 Table A2. Patients clinical and treatment characteristics of discovery cohort ................................. 159 Table A3. Timing and overlap of concomitant therapy with the onset of vincristine-induced peripheral neuropathy .................................................................................................................... 160 Table A4. Sensitivity analysis for potential confounding by age in the discovery cohort ......... 164 Table A5. Patients clinical and treatment characteristics of replication cohort ................................ 165 xiii List of Figures Figure 1.1 Mechanism of action of vincristine ................................................................................... 5 Figure 2.1 Full EMBASE and MEDLINE search strategy ................................................................ 28 Figure 2.2 PRISMA 2020 flow diagram of articles screened and included in the final review .......... 32 Figure 2.3 Schematic overview of the function of genes associated with vincristine-induced peripheral neuropathy in pediatric cancer patients ............................................................................ 40 Figure 2.4 Discovery of genetic variants associated with vincristine peripheral neuropathy risk ....... 52 Figure 3.1 Propensity score matching of cases and controls using vincristine cumulative dose and genetic ancestry ............................................................................................................................... 59 Figure 3.2 CONSORT flow diagram of CPNDS-recruited pediatric patients with Vincristine-induced peripheral neuropathy ...................................................................................................................... 60 Figure 3.3 Cumulative incidence of vincristine-induced peripheral neuropathy cases over time ....... 67 Figure 3.4. Manhattan plot of the vincristine-induced peripheral neuropathy GWAS summary statistics .......................................................................................................................................... 69 Figure 3.5 Vincristine neuropathy pathways associated with genes nominated by GWAS. ............... 72 Figure 3.6 Vincristine-induced peripheral neuropathy-related pathophysiology ............................... 78 Figure 4.1 CONSORT flow diagram of CPNDS-recruited pediatric patients with vincristine-induced peripheral neuropathy ...................................................................................................................... 86 Figure 4.2 Distribution of patients with different neuropathy subtype (motor or sensory) ................. 91 Figure 4.3 Kaplan-Meier plot of the cumulative incidence of vincristine-induced peripheral neuropathy over a 24-month follow-up period. ................................................................................ 93 Figure 5.1 CEP72 association with vincristine-induced peripheral neuropathy ............................... 106 Figure A1. Top 4 principal components (PCs) representing the distribution of patients compared to samples from the 1000 Genomes Project using PCs 1-4 ................................................................. 158xiv Figure A2. LocusZoom regional Manhattan plots for the GWAS-nominated vincristine neuropathy-associated risk loci ........................................................................................................................ 161 Figure A3. Summary of gene expression of GWAS-nominated genes across different tissues ........ 163 xv List of Abbreviations ABC ATP-binding cassette transporter ACTG1 Actin gamma 1 ACTN1 Alpha-actinin 1 ADRs Adverse Drug Reactions ALL Acute Lymphoblastic Leukemia AML Acute Myeloid Leukemia ARHGAP5 Rho GTPase Activating Protein 5 ATXN7L3B Ataxin-7-like protein 3B BAHD1 Bromo Adjacent Homology Domain-Containing Protein 1 BSA Body Surface Area CADD Combined Annotation Dependent Depletion CaMKII Calcium/calmodulin-dependent protein kinase II CAPG Capping Actin Protein, Gelsolin-like CCG Children’s Cancer Group CEP72 Centrosomal protein 72 CI Confidence Interval CNS Central Nervous System COCH Coagulation Factor C Homolog COG Children’s Oncology Group CPIC Clinical Pharmacogenetics Implementation Consortium CPNDS Canadian Pharmacogenomics Network for Drug Safety CTCAE Common Terminology Criteria for Adverse Events CXCL12 C-X-C Motif Chemokine Ligand 12 CXCR4 CD184, C-X-C Chemokine Receptor Type 4 CYP3A4 Cytochrome P450 3A4 CYP3A5 Cytochrome P450 3A5 DPWG Dutch Pharmacogenetics Working Group DPYD Dihydropyrimidine Dehydrogenasexvi EA Effect Allele ETAA1 Ewing's Tumor-Associated Antigen 1 EWAS Exome-Wide Association Study FBN2 Fibrillin 2 FDA Food and Drug Administration FDR False Discovery Rate FGD4 FYVE, RhoGEF And PH Domain-Containing Protein 4 FIG4 Phosphatidylinositol 3,5-Bisphosphate 5-Phosphatase GARS Glycyl-tRNA synthetase 1 GLCCI1 Glucocorticoid-Induced Transcript 1 GTEx Genotype-Tissue Expression GTP Guanosin-5'-Triphosphate GWAS Genome-Wide Association Study HR Hazard Ratio HWE Hardy-Weinberg Equilibrium IBD Identity-by-Descent IQR Interquartile Range LAMB3 Laminin Subunit Beta-3 LIPA Lipase A LRRTM3 Leucine Rich Repeat Transmembrane Neuronal 3 MAF Minor Allele Frequency MCM3AP Minichromosome Maintenance Complex Component 3 Associated Protein MTNR1B Melatonin receptor 1B NCI National Cancer Institute NFIB Nuclear factor 1 B-type NRG3 Neuregulin 3 OR Odds Ratio OS Overall Survival PAPPA Pappalysin 1 PCA Principal Component Analysis PD Pharmacodynamicsxvii PDE4D Phosphodiesterase 4D ped-mTNS Pediatric-Modified Total Neuropathy Scale PharmGKB Pharmacogenomics Knowledgebase PK Pharmacokinetics PMID PubMed ID POG Pediatric Oncology Group PROSPERO International Prospective Register of Systematic Reviews PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses QC Quality Control qPCR Quantitative Polymerase Chain Reaction SD Standard Deviation SLC5A7 Solute Carrier Family 5 Member 7 SNP Single Nucleotide Polymorphism SPYDA Speedy/RINGO Cell Cycle Regulator Family Member A STAT3 Signal Transducer and Activator of Transcription 3 SYNE2 Spectrin Repeat Containing Nuclear Envelope Protein 2 TNS-PV Total Neuropathy Scale Pediatric Version TMEM215 Transmembrane Protein 215 TPMT Thiopurine S-methyltransferase TRPA1 Transient Receptor Potential TUBB3 Tubulin Class III US United States VDR Vitamin D Receptor VIPN Vincristine-Induced Peripheral Neuropathy VTI1A Vesicle Transport Through Interaction With T-SNAREs 1A WHO World Health Organization ZFAND3 Zinc Finger AN1-Type Containing 3 xviii Acknowledgements And it’s a wrap… What a great feeling to bring this chapter of my academic career to a close! As I reach the culmination of this work, I reflect on the journey with immense gratitude and a deep sense of fulfillment on the many individuals whose support and help made this achievement possible. First and foremost, my sincere gratitude goes to Almighty God (Allah) for granting me the strength, resilience, and perseverance throughout every challenge along the way. I would like to thank to my supervisors, Dr. Bruce Carleton and Dr. Colin Ross for their mentorship and guidance throughout this important stage in my career. This dissertation work would not have been possible without your valuable insights, thoughtful feedback and directions over the years. I would like to extend my gratitude to all members of the CPNDS for their valuable contributions, thoughtful suggestions, and collaborative spirit that helped drive my research forward. A special thank you goes to Dr. Erika Scott, Dr. Miguel Córdova-Delgado, Dr. Kathy Chang, Dr. Kathy Li, and Dr. Catrina Loucks. It was truly a great pleasure working with you all. Your guidance, responsiveness, and willingness to share your expertise were instrumental to my learning and growth throughout my graduate studies. To Dr. Spencer Anderson and Jimmy Raack, I cannot fully express how grateful I am to have shared this PhD journey with you, and I could not have asked for better colleagues and friends along the way. Thank you for being incredible steadfast companions through the highs and lows of this chapter.xix I would also like to express my gratitude to my PhD supervisory committee members – Dr. Jan Friedman, Dr. William Gibson and Dr. Rod Rassekh. I am incredibly thankful for your time, valuable comments, constructive feedback and insights to improve my research work. Your guidance has been critical in shaping the design, analysis, and interpretation of my research, and I am so grateful for your support in helping me refine my work throughout my PhD journey. Lastly, I owe my deepest and most profound appreciation to my family for their unconditional love, sacrifice, and encouragement throughout my life and this degree. To my lovely wife, Najwa Younes, your belief in me and constant support have been my greatest source of strength. You have made this journey not only bearable but truly meaningful, and I am deeply grateful for your love, patience, and understanding. You have been my asset, and I could not have done this without you. To my parents, Mr. Safia Karahamo and Mr. Mohammad Mufti – thank you for your endless sacrifices, prayers, and faith in me. Your resilience and values have shaped who I am today, and I carry your love with me in all that I do. To my siblings – Fatima, Abdulla, Bana, and Bayan – thank you for your encouragement, understanding, and the warmth you have brought into my life, even from afar. Your support has meant the world to me. To all who have contributed to my journey, thank you for being a part of this experience. xx Dedication I dedicate this dissertation to my beloved parents, Mrs. Safia Karahamo and Mr. Mohammad Mufti, and to the memory of all children whose lives were cut short by adverse drug reactions. 1 Chapter 1: General Introduction 1.1 Adverse Drug Reactions (ADRs) Adverse drug reactions (ADRs) are defined as any unintended, harmful effects that arise during drug therapy, occurring beyond the anticipated therapeutic outcomes. 1, 2 Such reactions can vary in severity from mild discomfort to serious and life-threatening complications, potentially resulting in hospitalization, permanent disability, or even death. 3 In Canada, approximately 200,000 severe ADRs are reported annually, contributing to an estimated 10,000–22,000 deaths and making them the fourth leading cause of mortality in the country. 4 Managing these reactions costs the Canadian healthcare system between $13.7 and $17.7 billion every year, 4 which is likely an underestimation since up to 95% of ADRs remain either under-reported or misattributed to other causes. 5 Many ADRs are considered preventable; this, however, requires a more comprehensive understanding of the underlying mechanisms and the inter-individual variability that causes ADRs in some patients but not others. 6-8 Although the incidence of ADRs is notably higher in pediatric populations compared to adults, 9 the majority of clinical drug trials assessing the safety and efficacy of treatments focus on adult populations, with children often excluded from these studies due to ethical and safety concerns. 10 As a result, over half of the available pharmaceutical products lack specific pediatric dosing recommendations, despite regulatory efforts like those from the U.S. Food and Drug Administration (FDA) to provide child-specific labeling. 11 This is especially concerning as children's pharmacokinetics – the processes of drug absorption, distribution, metabolism, and excretion – differ markedly from adults’. 11-14 Factors 2 such as the development of drug-metabolizing enzymes, renal and hepatic function, and the maturation of transport systems vary during childhood, evolving as the child grows. 13, 15 Consequently, extrapolating adult drug safety data to pediatric populations is both challenging and unreliable, leaving a critical gap in optimizing pediatric drug therapy. 1.2 ADRs in Pediatric Oncology The prognosis for pediatric oncology patients has drastically improved over the past few decades, with survival rates climbing from approximately 30% in the 1960s to over 80%.16, 17 However, despite this success, chemotherapeutic agents used in pediatric oncology are typically nonspecific, meaning they indiscriminately target both cancerous and healthy cells. 18 This lack of selectivity, combined with the narrow therapeutic window of many chemotherapeutic agents–defined as the range between the minimum effective dose and the dose at which toxicity occurs–places pediatric cancer patients at an elevated risk of ADRs. 18 This is particularly concerning for children undergoing cancer treatment, with more than 75% of children receiving chemotherapy experiencing treatment-related ADRs, accounting for 22% of their hospital admissions. 3, 19 An estimated 42% of children suffer from life-threatening or permanently disabling ADRs due to their cancer treatment. 20-22 In addition, survivors of childhood cancers rarely walk away unscathed from cancer therapy, with up to 25% of survivors exhibiting adverse health outcomes, such as functional impairments, activity limitations, cancer-related pain, and mental health challenges, as they transition into adulthood. 23 Given their potential for harm, increasing attention is being given to the adverse effects of cancer 3 therapy in pediatric patients. 16, 17 The negative impact of ADRs in pediatric oncology has prompted the development of several key initiatives aimed at addressing this issue. Notable examples include the Precision Medicine Initiative, 24 the FDA Sentinel Initiative, 25 the Dutch Pharmacogenetics Working Group (DPWG), 26 the Clinical Pharmacogenetics Implementation Consortium (CPIC), 27 and the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). 28 Collectively, these initiatives aim to mitigate ADR risk by implementing active surveillance systems, 25, 28 developing evidence-based clinical guidelines, 26, 29-33 and implementing pharmacogenetic testing into routine clinical practice to detect and prevent ADRs. 34 These initiatives and research groups also employ advances in multidisciplinary fields such as pharmacology, molecular biology, genomics, and bioinformatics to understand disease progression and risk factors to optimize therapy. 24 For instance, the CPNDS has established an extensive active surveillance network across Canada, currently with 10 pediatric health centres, monitoring ADRs in pediatric populations. 28 By combining detailed clinical data with advanced molecular techniques—such as genomics, transcriptomics, and bioinformatics—these initiatives seek to perform patient-oriented genetic analyses to identify genetic markers associated with ADR risk. 28, 35, 36 The identification of such markers can enable more personalized treatment strategies, thereby improving patient outcomes and reducing the incidence of ADRs. 29, 34 Additionally, these efforts may lead to the development of new therapeutic interventions designed to prevent or mitigate serious ADRs in vulnerable patient populations. 37-39 4 1.3 Vincristine Chemotherapy Vincristine is a naturally occurring alkaloid compound composed of carbon, hydrogen, nitrogen, and oxygen (C46H56N4O10). Its medicinal properties have been recognized since the 17th century, as it is derived from the leaves of Madagascar periwinkle plant, Catharanthus roseus (formerly known Vinca rosea), whence it was first extracted in 1961. 40 In July 1963, vincristine was approved by the U.S. FDA as a chemotherapeutic agent, under the trade name Oncovin. 41, 42 Vincristine's mechanism of action is primarily mediated through its ability to disrupt microtubule dynamics, 43 which are critical for a variety of essential cellular functions. Microtubules are key components of the cellular cytoskeleton which play pivotal roles in chromosomal segregation during mitosis and meiosis, intracellular axonal transport (retrograde and anterograde), and maintenance of cell shape. 44-46 1.3.1 Vincristine Mechanism of Action During cell division, microtubules form the mitotic spindle, which is necessary for the proper alignment and segregation of chromosomes. 47 Specifically, vincristine binds to the plus (+) ends of β-tubulin subunits within the microtubules, inhibiting the incorporation of new tubulin monomers. 48, 49 This impedes microtubule polymerization, thereby arresting cells at metaphase. 50 The inability to complete mitosis due to defective spindle formation results in prolonged metaphase arrest, which ultimately triggers apoptosis, or programmed cell death. 51, 52 Of note, vincristine exhibits concentration-dependent effects on microtubule dynamics: at low concentrations, it binds to the plus end of the microtubules (high-affinity binding sites), preventing elongation by inhibiting guanosine-5'-triphosphate (GTP) binding to β-tubulin, and at 5 higher concentrations, it can bind to tubulin along the microtubule surface (lower affinity binding sites) and actively promote microtubule depolymerization, causing structural disassembly (Figure 1.1). 53 Figure 1.1 Mechanism of action of vincristine. This figure illustrates vincristine binding to the β-subunit of tubulin-dimer at the vincristine binding site in the exterior of microtubules. Vincristine generally has two distinct binding sites on microtubules: a high affinity binding site at the microtubule plus end and a low affinity binding site on the tubulin along the microtubule surface. 54 The destabilization caused by this binding leads to microtubule depolymerization through disruption of longitudinal cross-linking within the β-tubulin, further impairing cellular function and inducing cell death. 55 Figure was created with BioRender.com. 6 1.3.2 Clinical Use of Vincristine Vincristine is one of the oldest and most widely used chemotherapeutic agents in both pediatric and adult patients. Since the 17th century, vinca alkaloids have been investigated for their therapeutic potential in managing conditions such as hemorrhage and scurvy, as an analgesic in toothache, as a promoter of wound and diabetic ulcer healing, and to lower blood sugar levels. 56-59 However, the anticancer properties of vincristine were first observed by Noble et al. in 1957, who noted that certain extracts of Catharanthus roseus caused bone marrow suppression and granulocytopenia. 60 Following this, Svoboda discovered in 1958 that the plant extracts exhibited antileukemic activity in mice with lymphoblastic leukemia. 61 In the 1960s and early 1970s, the clinical application of vincristine in pediatric oncology was studied in a variety of pediatric cancer types, including acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), Hodgkin’s and non-Hodgkin’s lymphomas, Wilm’s tumor, rhabdomyosarcoma, Ewing’s sarcoma, neuroblastoma, and brain tumors such as gliomas and medulloblastomas. 62-68 Vincristine was administered as a monotherapy in the early 1960s in patients who were refractory to existing treatments at the time, which included steroids, methotrexate, mercaptopurine, and alkylating agents. 69 Although patients treated with vincristine often had a partial or complete remission, these remissions as a result of single agent vincristine treatment were often incomplete and brief. 69, 70 Today, vincristine is incorporated within a multi-agent and multimodality treatment protocol and is widely used as a first-line chemotherapeutic component in the treatment of pediatric cancers, including leukemias, lymphomas, and solid tumors, such as Wilm’s tumor, neuroblastoma, and rhabdomyosarcoma. 71, 72 7 Vincristine dosing is typically calculated based on body surface area (BSA), with a standard dose of 1.5 mg/m², up to at a maximum of 2 mg per dose. In younger patients (<3 years old), doses are generally calculated based on body weight as mg/kg (typically 0.5 mg/kg/dose). Dose recommendations for infants less than one-year of age vary by tumour type and protocol, ranging from weight-based dosing of 0.17 mg/kg/dose to 0.05 mg/kg/dose (e.g., 0.17 mg/kg/dose for neuroblastomas, 0.025 mg/kg/dose for Wilms tumour and rhabdomyosarcoma, 0.03 to 0.05 mg/kg/dose for infant ALL), to BSA-based dosing (e.g., 0.6 mg/m2/dose for Ewing’s sarcoma) and dose escalation (e.g., first dose at 50%, second dose at 75%, third dose at 100% for Ewing’s sarcoma). Additionally, the frequency of vincristine doses can also be highly variable. Within one protocol, a patient could receive doses that can change over time, ranging from weekly doses, bi-monthly doses, to one dose every month. Depending on the phase of protocol, patients with leukemia or lymphoma receive vincristine once every seven to 84 days, for a total of 1.5 to three years. Patients with solid tumours (e.g., Wilms tumor, rhabdomyosarcoma, Ewing’s sarcoma, hepatoblastomas, and hepatic cellular carcinomas) have less variable vincristine doses that range from once every week to every six weeks, for a total of six to nine months. 1.4 Vincristine-Induced Neuropathy Despite being one of the most effective and widely used chemotherapeutic agents for the treatment of childhood cancers, the clinical utility of vincristine is significantly limited by the occurrence of severe neuropathy reactions in susceptible patients. These reactions are one of the main reasons for interruption or discontinuation of chemotherapy until the patient has 8 sufficiently recovered, which may increase relapse risk, reduce cancer prognosis, and potentially affect patient’s quality of life and survival during and after cancer therapy. 73-75 1.4.1 Types of Vincristine-Induced Neuropathy Vincristine-induced neuropathy can manifest in multiple forms, affecting various components of the nervous system, and is classified into 1) Peripheral neuropathy, which can be further subdivided into sensory neuropathy (paresthesia [i.e., tingling or numbness], pain in the jaw and extremities or impaired touch sensitivity/temperature recognition), 76 and motor neuropathy (typically characterized by muscle weakness, foot or wrist drop, reduced dorsiflexion, ataxia, gait disturbances, or decreased/loss of deep tendon reflexes); 77 2) Autonomic neuropathy, characterized by constipation, ileus, bladder dysfunction (i.e., incontinence or urinary retention), or orthostatic hypotension; 78-80 3) Cranial neuropathies, leading to ocular issues, such as ptosis, optic atrophy, pupil paralysis, and ophthalmoplegia, or laryngeal nerve or vocal cord paresis or paralysis, resulting in hoarseness, weak voice, dysphagia, and difficulty swallowing, facial muscle atrophy or hearing loss can occur; and lastly 4) Central nervous system (CNS) neuropathy, though less common, may include the syndrome of inappropriate antidiuretic hormone secretion, which is associated with hyponatremia and fluid overload. These diverse manifestations of neurotoxicity highlight the broad range of vincristine’s impact 9 on the nervous system. Of these types, vincristine-induced peripheral neuropathy (i.e., sensory and motor nerve symptoms) is the most common type of vincristine toxicity, 81 which usually manifests as numbness and pain in the hands and feet, as well as muscle weakness and impairment. 82 In addition, these symptoms can vary in severity, as distinguished by the intervention required for management. For example, common reactions with low severity usually occur as mild pain and paresthesia that require oral analgesics and close observation. Severe mobilization difficulties of the arms and legs that affect walking and the ability to feed oneself require assistive devices as well as rehabilitation/physiotherapy. Vocal cord paralysis may require emergency intubation and long term tracheostomy with prolonged mechanical ventilation. 83 Paralytic ileus or severe constipation may require colostomy to treat bowel perforation. 84 More severe reactions include an inability to eat or sleep, or inability to perform fine motor tasks. These usually require hospitalization and intervention with narcotics, as well as vincristine dose reduction, which increases the risk of therapeutic failure. Life-threatening reactions such as complete loss of sensation and paralysis are less common; however, they require hospitalization, urgent intervention (e.g., tracheotomy) and discontinuation of vincristine therapy. 85 1.4.2 Pathophysiology of Vincristine-Induced Peripheral Neuropathy Vincristine induces peripheral neuropathy through a complex mechanism of damages that are directly connected to its mechanism of action through which it carries out its antineoplastic effects. As vincristine disrupts the microtubule dynamics, not only is mitosis blocked, but all the other critical functions that involve microtubules (e.g., cytoskeletal organization, axonal 10 transportation, and nerve myelination) 86 are also inevitably compromised. In neurons, microtubules serve as structural scaffolds within axons and dendrites, facilitating intracellular transport and supporting the normal function and morphology of neurons. 43, 87 Since neurons are not in active replication, the ability of vincristine to cause their death is attributed to the disruptions in the structure and distribution of axonal microtubules. 88-90 Microtubules act as the main long-distance railway along which proteins and organelles are actively transported in both directions within the axons and dendrites, allowing for the normal transmission function of the nerve impulse. 91 They also play a fundamental role in the myelination of nervous fibers as they are essential constituents of oligodendrocytes. 92 Thus, damage to tubulin structures in the cytoskeleton of myelinated axons by vincristine can lead to alterations in the microtubular retrograde and anterograde axonal transport system, 46, 93 blockage of nerve regeneration, demyelination of the myelin sheaths, and loss of peripheral sensory fibers. 92, 94-96 These processes consequently alter nerve impulse transmission and lead to axonal degradation and, ultimately, neuronal death. 53, 94 In addition to its direct structural and functional damage of nerve cells, vincristine can initiate an immune response by inducing the expression of integrins on the surface of endothelial cells, allowing immune cells such as macrophages to adhere to the endothelium and infiltrate the nervous tissue. 52 This immune activation results in the production of reactive oxygen species (ROS), which contribute to further neuronal injury by activating pain pathways, particularly through the activation of transient receptor potential (TRPA1) channels in sensory neurons. 97 Furthermore, vincristine facilitates the binding of the Signal Transducer and Activator of Transcription 3 (STAT3) to the CXCL12 (C-X-C Motif Chemokine Ligand 12) gene promoter, 11 determining the upregulation of CXCL12 in dorsal horn ganglia. 98 CXCL12 is a member of the integrin family and acts as a ligand of CXCR4 (CD184, C-X-C chemokine receptor type 4); which increases the intracellular concentration of calcium, resulting in the approaching of T-lymphocytes and monocytes. This series of events leads to the onset of an inflammatory process in the peripheral nervous system, with consequent worsening of the neurological damage. 98 The third mechanism of peripheral neuropathy is damage to the mitochondria. 99 It has been recognized that vincristine can influence the movement of Ca2+ across the mitochondrial membrane, reducing both the quantity and the rate of Ca2+ absorption and decreasing its efflux. 100 The modification of the mitochondrial absorption and concentration of Ca2+ alters mitochondrial function, 101 with consequently increased exocytosis of neurotransmitters102 and elevated release of ROS. 53 These changes lead to reduced neuronal excitability and glial function, activating apoptosis. In support of this damage hypothesis, Flatters et al. reported a high incidence of swollen and vacuolated mitochondria with disrupted cristae localized at the periphery of the organelle. 103 These overlapping mechanisms—microtubule disruption, immune activation, and mitochondrial dysfunction—act synergistically to induce peripheral neuropathy. The severity and progression of neuropathy are influenced by both patient-related and treatment-related factors, which will be explored in detail in later sections (section 1.4.4). 12 1.4.3 Clinical Characterization and Assessment of Vincristine-Induced Peripheral Neuropathy Vincristine peripheral neuropathy is not only very heterogeneous in pathology, but also in its clinical presentation. Accurately assessing vincristine-induced peripheral neuropathy in pediatric patients can be challenging, especially young children, who may struggle to verbalize their symptoms. As a result, clinicians often rely on proxy assessments from caregivers or use standardized assessment tools to estimate the severity of neuropathy. While peripheral nerve damage can be partially measured by changes in nerve conduction velocity and amplitude, 104 nerve conduction studies are typically not feasible for use as a standard neuropathy measurement approach due to the high associated costs, limited accessibility to testing, the inconvenience (requires neurologist referral) and the discomfort associated with the testing, which reduces their practicality for routine clinical use. The current standard tool for assessment of toxicities from cancer treatment-related neurotoxicity is the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE), which is commonly used in both clinical and research settings for the evaluation of cancer treatment-related adverse events, including peripheral neuropathy. 105 The CTCAE grading scale provides numeric score reflecting sensory and motor neuropathy severity, with scores ranging from “1” (mild neuropathy) to “5” (neuropathy-related death). 106 Other grading scales, such as the pediatric-modified Total Neuropathy Scale (ped-mTNS) 107 and the Total Neuropathy Scale Pediatric Version (TNS-PV), 108 incorporate interview-based questionnaires along with physical assessment of sensory function, muscle strength, and reflexes. These tools often identify a greater number of children with vincristine-induced neuropathy compared to the 13 CTCAE. 106, 109 However, both of these tools have limitations. Neither of them has been properly evaluated for their reliability and validity. In addition, both instruments are not suitable for evaluating vincristine peripheral neuropathy in children aged ≤ 6 years, which limits their applicability in young pediatric populations. 110 Recently, the pediatric-modified Total Neuropathy Score (ped-mTNS) was developed to provide a rapid, inexpensive, and non-invasive, interview-based questionnaire and physical examination, with better psychometric characteristics compared to the other tools available for the assessment of pediatric vincristine-induced peripheral neuropathy. 111 The peds-mTNS has three items that quantify subjective sensory, motor, and autonomic symptom severity. This tool also provides a rubric for scoring several objective neuropathy measures, including light touch, pin and vibration sensation, strength, and deep tendon reflexes. However, despite its demonstrated reliability for children aged 5-18, 77 peds-mTNS may lack reliability for neuropathy assessment in children aged less than five years. Thus, other types of validated neuropathy assessment tools are still needed to assess long-term neuropathy-associated outcomes – such as pain, psychological effects, functional and cognitive impairments, and quality of life impacts – in pediatric oncology patients. 1.4.4 Risk Factors of Vincristine-Induced Peripheral Neuropathy The risk of developing vincristine-neuropathy is influenced by several factors that include treatment-related and patient-related factors. Understanding these factors is critical for optimizing vincristine therapy and minimizing the occurrence of this adverse reaction in 14 pediatric cancer patients. 1.4.4.1 Treatment-related risk factors One of the key determinants of vincristine neuropathy is vincristine dose, with both the incidence and severity of neuropathy strongly correlated with cumulative vincristine exposure. 103, 112 The rate of axonal degeneration resulting from vincristine is dependent on the concentration of vincristine, 113, 114 with higher dose intensity typically results in more severe neuropathy, which underscores the need for careful dose management during treatment. 115 Concomitant use of medications that interfere with vincristine metabolism and elimination can also impact the risk of vincristine neuropathy. 116-120 Vincristine is metabolized in the liver by the cytochrome P450 3A4 (CYP3A4) enzyme, 121-124 and co-administration of CYP3A4 inhibitors can increase systemic concentrations of vincristine, thereby increasing the risk of neurotoxicity. 125 This is particularly evident with azole antifungal drugs, which are commonly used in pediatric cancer patients for the treatment and prevention of systemic fungal infections. 126 Antifungal azoles such as fluconazole, itraconazole, ketoconazole, posaconazole, and voriconazole are known CYP3A4 inhibitors that have been associated with increased incidence and severity of neuropathy in patients receiving vincristine therapy. 127, 128 Among these azoles, a relatively milder vincristine-induced neuropathy has been seen with concurrent fluconazole, likely due to its weaker CYP3A4 inhibitor than other azoles. 116 Itraconazole is a stronger inhibitor of CYP3A4 than posaconazole and voriconazole, which are more potent inhibitors than fluconazole. 129 Lin et al. report the case of pediatric ALL patient treated with posaconazole for a mucormycosis infection. This patient developed severe 15 vincristine-induced neuropathic pain and constipation from the association of posaconazole with vincristine chemotherapy. 117 Itraconazole has shown the strongest association with severe vincristine-induced neuropathy, likely due to its dual inhibition of both CYP3A4 and the P-glycoprotein efflux pump, which significantly increases vincristine intracellular concentrations. 118-120 Pana et al. collected 26 cases of children affected by ALL, who received azole treatment (with itraconazole, posaconazole or voriconazole) and developed vincristine neuropathy, with a high incidence of autonomic neuropathy (abdominal pain, constipation and paralytic ileus). 130 Other examples of concomitant medications that impact vincristine neuropathy risk include clarithromycin, another potent CYP3A4 inhibitor, which can inhibit vincristine metabolism and subsequently elevate its plasma concentration, 131 phenytoin, which can exacerbate vincristine neurotoxicity and thus should either be avoided or used cautiously, 42 and nifedipine, a calcium channel blocker, which modulates vincristine pharmacokinetics by decreasing its excretion, and consequently increasing the risk of vincristine-induced neuropathy. 131, 132 1.4.4.2 Patient-related risk factors Age, sex and ancestry are three patient-related factors that are known to influence the occurrence of vincristine neuropathy. Available literature pertaining to the role of age on vincristine neuropathy risk has been divergent. 133 In theory, younger children may be more susceptible to vincristine neuropathy due to the incomplete maturation and myelination of their peripheral nervous system, making them more vulnerable to microtubule disruption. 133, 134 On the other hand, younger children have more rapid vincristine metabolism than older patients, which could prevent the risk of reaching vincristine toxic plasma levels. 135, 136 One challenge in assessing the 16 influence of age is that neuropathy symptoms such as numbness, tingling and neuropathy pain are difficult concepts for young children to effectively describe. 137 Thus, the true incidence of neuropathy in this age group may be underreported. Sex-based differences in the incidence of vincristine neuropathy have also been explored, though evidence remains inconclusive. Of the 58 papers evaluated by van de Velde et al., no clear evidence was identified regarding the influence of sex on the incidence of vincristine neuropathy. 133 Overall, the influence of sex on neuropathy risk remains uncertain, with no evidence at the genetic level having been established to explain these disparities. Ancestry is a significant factor influencing the risk of vincristine neurotoxicity. The incidence of vincristine-induced neuropathy differs across patients of different ancestries, which is influenced by the activity of key enzymes involved in vincristine metabolism such as the CYP3A family. 138-142 For instance, reduced CYP3A5 activity is observed more frequently in patients of Caucasian ancestry compared to those who are African-American (70% of whom express at least one allele of the active form of CYP3A5 enzyme). 143 Consequently, increased metabolic clearance of vincristine is exhibited in the African-American population, 144, 145 which accounts for a 7-fold lower rate of vincristine neuropathy among African-Americans than among Caucasians (i.e., 35% Caucasians developed vincristine-related neurotoxicity, compared to only 5% of African-Americans who received a comparable cumulative dose). 146 Despite this increased clearance rate, vincristine dosing is not routinely adjusted based on CYP3A5 expression or ancestry. 17 1.4.4.3 Genetic risk factors Beyond clinical and demographic factors, several genetic variations have been associated with the risk of vincristine-induced neuropathy. Since the first pharmacogenetic study of vincristine-induced neuropathy by Aplenc et al. (2003) demonstrating the role of genetic variants in CYP3A4 and CYP3A5 in vincristine neuropathy risk, 123 several studies have provided evidence implicating genetic variations in vincristine-induced neuropathy. Genes encoding components of inflammatory signalling pathways (e.g., PPARD, LTA), 147 vincristine pharmacokinetics (PK) – affecting metabolism (e.g., CYP3A4, CYP3A5, DPYD), 124, 148 transport (e.g., ABCC1, ABCC2) , 148, 149 and elimination (e.g., ABCB1, ABCC2), 149, 150 – as well as vincristine pharmacodynamics (PD), including cellular targets of vincristine (e.g., CEP72, CAPG, MAPT), 150-152 and neuropathy-related pathways (e.g., SLC5A7, NKAIN3) 148 have all been implicated. A detailed review of the current literature on these genetic risk factors, including their effect sizes, statistical significance, and clinical relevance, is provided in Chapter 2. 1.4.5 Current Treatment and Prevention/Therapeutic Implications Currently, despite several drugs having been investigated to mitigate neuropathy in pediatric oncology patients, there are currently no effective strategies to treat or prevent vincristine-induced neuropathy. Available treatment options are primarily symptomatic, focusing on pain relief and physical rehabilitation. Several trials sought to determine whether putative neuroprotective agents such as gabapentin, vitamin B6, pyridostigmine, glutamine or glutamate can be used to treat or prevent vincristine-induced peripheral neuropathy. 153-165 However, most of these treatment options have shown only 18 limited success, 166 and future research is needed to determine the best treatment strategy. For instance, gabapentin is one of the top medications that have been studied to treat neuropathic pain in children receiving vincristine. Anghelescu et al. conducted a retrospective study evaluating the use of gabapentin for both the prophylaxis and treatment of neuropathic pain in pediatric ALL patients. 161 Gabapentin was administered after the first episode of pain and continued as prophylaxis for any subsequent episodes, however, there was no significant advantage of gabapentin over opioids in reducing the recurrence of neuropathic pain. 161 Additionally, a more recent randomized, double-blind, placebo-controlled trial assessed gabapentin in combination with opioids versus placebo plus opioids in 51 ALL pediatric patients who developed vincristine-induced neuropathy, and gabapentin plus opioid was not associated with a better analgesic efficacy than therapy with placebo plus opioid. 164 Other pharmacological agents, such as pyridoxine (vitamin B6), have shown potential neuroprotective effects against vincristine-induced neuropathy. Müller et al. reported the successful recovery of a 2-year-old boy with synovial sarcoma from bilateral ptosis after treatment with a combination of pyridoxine and pyridostigmine (the latter being an acetylcholinesterase inhibitor). 167 Subsequently, Akbayram et al. documented four pediatric ALL cases wherein patients fully recovered from neuropathy symptoms within 1–2 weeks following treatment with pyridoxine and pyridostigmine, with no significant adverse effects. 160 More recently supporting these findings, Köker et al. evaluated the features of vincristine peripheral neuropathy and the effectiveness of pyridoxine plus pyridostigmine therapy in children with ALL; they studied 23 patients with ALL and vincristine neuropathy and administered an oral dose of pyridoxine and pyridostigmine to 21 of them for three months, 19 observing an improvement in symptoms and the absence of adverse effects. 165 Of note, none of these studies included a blinded or even open control group, which weakens the evidence for the efficacy of pyridoxine and pyridostigmine. Additionally, neuropathic symptoms may improve over time regardless of treatment, further complicating the interpretation of these findings regarding drug efficacy. Such limitations highlight the need for well-designed, controlled clinical trials to validate the neuroprotective effects of pyridoxine and pyridostigmine in alleviating vincristine-induced neuropathy. Glutamic acid, an excitatory neurotransmitter, has also been investigated for its potential role in managing vincristine sensory neuropathy. 168 Bradfield et al. conducted a randomized, placebo-controlled trial in 250 pediatric patients with Wilms’ tumor, rhabdomyosarcoma, non-Hodgkin’s lymphoma, and ALL, administering glutamic acid before vincristine treatment at doses adjusted for body surface area. They found that glutamic acid was effective for the prevention of peripheral neuropathy only in patients aged 13 years or older, but not in younger patients. 162 In their randomized single-blinded placebo-controlled clinical trial, Mokhtar et al. similarly investigated the use of glutamic acid for preventing neurotoxicity in pediatric patients undergoing chemotherapy for ALL, non-Hodgkin’s lymphoma, or Wilms’ tumor, finding a reduction in neurotoxicity in the group treated with glutamic acid, with no significant adverse effects. 159 In preclinical models, glutamine has been shown to upregulate circulating nerve growth factor mRNA, a key factor reduced in patients undergoing chemotherapy with neurotoxic agents. 169 Furthermore, pilot laboratory and human studies suggest that glutamine may improve 20 microtubule formation and stability. 155 Sands et al. performed a double-blind, randomized, placebo-controlled trial assessing the efficacy of glutamine in preventing vincristine neuropathy in pediatric patients with non-Hodgkin’s lymphoma, Ewing’s sarcoma, Wilm’s tumor, or rhabdomyosarcoma. The study reported significant improvements in sensory function (p=0.022) and overall quality of life (higher by 8.42 points on PedsQL total score; p=0.031) among patients receiving glutamine supplementation compared to those receiving placebo. 163 However, these trials suffered from several limitations including small sample, insufficient power, a high drop-out rate, and inconsistencies in primary outcomes. Additionally, these trials were performed in a variety of treatment settings with various chemotherapy regimens, including different combinations of other neurotoxic medications (e.g., vinblastine, platinum derivatives, taxanes), making the interpretation and extrapolation of the results a major challenge. Thus, despite the widespread interest and numerous clinical trials aiming to treat peripheral neuropathy, no clear standard has been determined or can be recommended at the current time. 1.5 Pharmacogenetic and Pharmacogenomic Studies Combining the fields of pharmacology and human genetics, pharmacogenetics aims to discover relevant genetic variations that influence individual responses to drugs, including therapeutic effects and ADRs. The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. 170, 171 In 1962, Werner Kalow, after having studied how different genetic variants led to variable metabolism of the drug succinylcholine using new spectrophotometric techniques, published a book entitled Pharmacogenetics: Heredity and the Response to Drugs which laid the 21 foundation for pharmacogenetics to grow into its own field. 170 Over the next few decades, advancements in molecular biology techniques such as fluorescence in situ hybridization, Sanger sequencing, and polymerase chain reaction, enabled pharmacogenetic studies to identify many gene-drug associations. Among the most extensively studied genes is CYP2D6, a member of the CYP450 enzyme family involved in the phase I metabolism of a broad range of drugs. 172 Genetic polymorphisms in CYP2D6 correlate with distinct metabolic phenotypes—including ultra-rapid, extensive, intermediate, and poor metabolizers—which can critically impact drug efficacy and toxicity. 172 CYP2D6 alone metabolizes approximately 20-25% of all prescribed drugs, underscoring its importance in clinical pharmacology. 172 A well-documented example is codeine metabolism, where ultra-rapid metabolizers of CYP2D6 convert codeine to morphine at accelerated rates, risking elevated morphine levels and potential life-threatening central nervous system (CNS) depression in both infants and mothers. 173, 174 Until the 1990s, pharmacogenetic studies were primarily focused on single-gene effects in drug metabolism and response. However, ADRs frequently involve complex interactions among multiple genes, such as those related to immune response and mitochondrial function. The completion of the Human Genome Project in 2003, coupled with further advancements in DNA genotyping and high-throughput sequencing technologies, marked the beginning of pharmacogenomics—the genome-wide application of pharmacogenetics. 175 Since then, pharmacogenomic research has significantly contributed to our understanding of the genomic variability that underpins inter-individual differences in ADRs and therapeutic outcomes. 176 A 22 genome-wide approach to elucidating the pharmacogenomics of a drug is especially valuable for medications with high inter-individual variability in response or those with narrow therapeutic windows, such as chemotherapeutic agents. Ultimately, incorporating evidence-based pharmacogenomic findings into clinical practice may enhance drug safety, guide policy, and improve risk-benefit decision-making frameworks in healthcare. 1.6 Thesis Hypothesis and Objectives Despite the fact that vincristine has been used for decades, vincristine-induced peripheral neuropathy is still a major concern in pediatric oncology, with dose reductions or even withdrawal of treatment sometimes being the only solution to reduce vincristine-induced peripheral neuropathy. Given the drastic improvements in childhood cancer survival, there is a need to improve the safety of chemotherapy in pediatric oncology in order to avoid the serious, lifelong complications of chemotherapy-induced ADRs. Since vincristine is a key component of many pediatric oncology treatment protocols all over the world, optimization of vincristine treatment is of high importance. This and consistently associated with the risk of vincristine-induced peripheral neuropathy in pediatric patients signal important underlying mechanisms that contribute to the development of vincristine peripheral neuropathy. Overall, the main goal of this thesis was to understand the pathophysiology of vincristine-induced peripheral neuropathy and to identify and validate predictive genetic markers for the risk of neuropathy. 23 Specific objectives of the current study were: 1. To identify and evaluate, through an up-to-date systematic review, genetic variants that have been associated with vincristine-induced peripheral neuropathy in the existing literature (genome-wide association studies, candidate gene and candidate variant studies). 2. To thoroughly investigate the role of genomic factors in the risk and severity of vincristine peripheral neuropathy in a large cohort of patients with childhood cancers using a genome-wide approach to identify novel pharmacogenomic markers implicated with pathology and risk of neuropathy. 3. To validate and determine the relevance of the identified pharmacogenomic variants and variants that had been previously associated with vincristine peripheral neuropathy in pediatric cancer patients. 24 Chapter 2: Pharmacogenomic Factors of Vincristine-Induced Peripheral Neuropathy in Patients with Childhood Cancers: A Systematic Review 2.1 Introduction Vincristine is a cornerstone chemotherapeutic agent widely given for the treatment of various adult and pediatric cancers, including ALL, Hodgkin and non-Hodgkin lymphoma, neuroblastoma, rhabdomyosarcoma, low-grade glioma, and nephroblastoma. 72, 177, 178 However, its clinical utility and safety are severely limited by the presence of vincristine-induced peripheral neuropathy, which often manifests as sensory-motor neuropathy, 82 with symptoms including foot drop, loss of deep tendon reflexes, impaired balance, and pain or tingling sensations. Autonomic symptoms such as constipation and orthostatic hypotension may also occur. 78, 79 The prevalence of vincristine-induced neuropathy varies depending on the population studied and the methods used for assessment, with up to 78% of patients receiving vincristine experiencing peripheral neuropathy during the therapy. 106, 179 Severe neuropathy, which requires dose reduction or even treatment withdrawal, can affect up to 30% of patients. 106, 133 Furthermore, vincristine peripheral neuropathy significantly affects patients’ quality of life, as demonstrated through both self and proxy measures using different assessment tools. 74 Importantly, the detrimental effects of vincristine neuropathy on quality of life often persist beyond treatment, as over 16% of ALL survivors suffer from long-term neuropathy, adversely impacting their physical health and social functioning. 78 25 Pharmacogenomic studies aim to explore the impact of genetic variations on treatment response and susceptibility to ADRs such as vincristine peripheral neuropathy. Two main study designs are usually employed: candidate gene studies and genome-wide or exome-wide association studies (GWAS or EWAS). 180, 181 Candidate gene studies focus on genes preselected based on existing knowledge or mechanistic hypotheses, while GWAS and EWAS are gene-agnostic studies that uncover associations across the entire genome or exome. 180 These approaches can reveal novel genotype-phenotype associations, potentially providing valuable insights into the genetic underpinnings of vincristine peripheral neuropathy. Pharmacogenetic testing has been successfully implemented for certain drugs, such as thiopurines (e.g., TPMT genotyping); however, its application to vincristine therapy remains limited. 182, 183 A comprehensive understanding of the genetic factors contributing to the risk of vincristine peripheral neuropathy is critical to advancing precision medicine in this context. Given the multifactorial nature of vincristine-induced neuropathy, it is likely that genetic factors influencing vincristine pharmacokinetics, cellular sensitivity to vincristine and neuronal pathways may contribute significantly to individual variability in neuropathy risk. Identifying such genes and pathways could enable clinicians to stratify patients based on their risk of developing significant vincristine peripheral neuropathy. Ultimately, the goal is to establish tailored clinical interventions that minimize severe vincristine peripheral neuropathy while preserving its effectiveness. High-risk patients might benefit from closer monitoring, dose adjustments, or early initiation of physiotherapeutic interventions, while 26 patients who tolerate vincristine well could potentially receive higher doses without dose capping at 1.5 mg/m², to maximize therapeutic efficacy. However, achieving this requires a robust evaluation of the existing evidence on genetic factors influencing vincristine peripheral neuropathy. Attention must be given to understanding the high levels of heterogeneity that exist in such studies, and how these differences impact the potential reliability and/or generalizability of the results. These sources of heterogeneity include variations in genetic variants assessed, treatment protocols, neuropathy assessment methods, patient age, and definition/assessment of neuropathy. Addressing these challenges is essential for translating pharmacogenomic insights into clinically actionable strategies. 2.2 Objectives The primary objective of this systematic review is to identify and summarize the impact of genetic factors reported in the literature on vincristine-induced peripheral neuropathy risk in pediatric cancer patients. By summarizing existing evidence, this review aims to discuss the potential clinical relevance of previously published findings, providing insights into their applicability in clinical practice. Additionally, this work seeks to identify gaps in the current body of literature, offering guidance for the design of future pharmacogenomic studies that aim to optimize vincristine therapy for children with cancer. 27 2.3 Methods 2.3.1 Literature Search Strategy The protocol for this systematic review was prospectively registered with the PROSPERO International Register of Systematic Reviews (Registration Number: CRD42024526022). A comprehensive search of Medline and EMBASE databases was conducted on March 21, 2024, including all studies published in the literature up to this date. The search strategy employed a combination of keywords and medical subject headings (MeSH) to reflect the eligibility criteria, incorporating concepts such as vincristine, peripheral neuropathy, pharmacogenetics, and pharmacogenomics. The detailed search strategy for Medline and EMBASE is presented in Figure 2.1 Additionally, a supplementary search of the Pharmacogenomics Knowledgebase (PharmGKB) 184 was performed to identify genetic variants associated with vincristine-induced peripheral neuropathy that may have been overlooked during the database searches. Although PharmGKB primarily curates literature from major pharmacogenomics journals and does not systematically capture all relevant studies. Therefore, this search was conducted in parallel with the Medline and EMBASE searches to ensure comprehensive coverage of the available literature. 28 Figure 2.1 Full EMBASE and MEDLINE search strategy. Search was conducted on March 21, 2024, and included studies that contained relevant terms from all three key concepts. 2.3.2 Eligibility Criteria This systematic review adhered to the PRISMA 2020 guidelines. 185 Studies were included if they analyzed the influence of genetic variations on the risk of vincristine-induced peripheral neuropathy in pediatric patients aged 0 to 18 years and were published in the English language. Studies were excluded if they involved non-human animal research, were case studies, conference abstracts, or non-genetic studies, or focused on non-pediatric patient populations. Studies that did not specifically examine vincristine-induced peripheral neuropathy were also excluded. 29 Review articles were included in the search strategy but were utilized solely for cross-referencing their bibliographies to identify potentially relevant studies that may not have been captured by the initial search. The systematic review included studies of patients who received vincristine treatment but no restrictions were made regarding vincristine dose, treatment regimens, tumor types, or patients' ancestral backgrounds. 2.3.3 Study Screening and Data Collection The titles and abstracts of studies identified through the search were reviewed by two independent reviewers (Kheireddin Mufti and Spencer J. Anderson) to minimize bias and ensure that the articles met the predefined eligibility criteria for inclusion in this systematic review. Using the COVIDENCE as a tool, 186 the reviewers screened and categorized each study into one of three groups: 1) studies that fulfilled the inclusion criteria, 2) studies that did not meet the inclusion criteria or met an exclusion criterion, or 3) studies where eligibility was unclear, necessitating a full-text review. If both reviewers agreed that a study met the inclusion criteria or required further review due to unclear eligibility, the study was retrieved for full-text review. If both reviewers agreed that a study did not meet the eligibility criteria, it was excluded from further consideration. Any disagreements between the reviewers were resolved through discussion to reach a consensus. Data extracted from included studies encompassed several key elements, including the first author, year of publication, study design, cohort size, sex distribution of the included patients, tumour type, reported ancestral backgrounds, cumulative vincristine dose, method of neuropathy assessment, case/control number and definitions, genes and genetic variants studied (including 30 variant rsID, type, and effect size), and the genetic model tested. The two reviewers independently extracted these data, and any discrepancies were addressed and resolved through discussion to ensure accuracy and consistency. 2.3.4 Data Synthesis Associations between genetic variants and vincristine-induced peripheral neuropathy identified in the included studies were captured for analysis. A qualitative synthesis was planned and subsequently performed due to the anticipated heterogeneity across studies. This synthesis evaluated whether the investigated genetic variations were associated with an increased, decreased, or unchanged risk of vincristine-induced peripheral neuropathy. Additionally, the synthesis incorporated observed similarities and differences within and across included studies. These included factors such as vincristine cumulative dose, methods of neuropathy assessment, cohort sizes, case/control definitions, patients’ median ages, and distributions of sex and ancestry. This comprehensive approach ensured that the analysis captured both the diversity and the commonalities in findings across studies, facilitating a deeper understanding of the genetic contributions to vincristine-induced peripheral neuropathy. 2.4 Results 2.4.1 Literature Search Results and Study Selection A total of 719 articles were initially identified through the literature search conducted using the Medline and Embase databases. After the removal of duplicate records (n=44), the remaining 675 articles underwent abstract screening by the two independent reviewers. During this process, 602 irrelevant reports were excluded, leaving 73 articles for full-text review. Following a 31 detailed full-text screening, assessment of eligibility resulted in the exclusion of 45 reports based on: Wrong outcome/ not focused on peripheral neuropathy (n=13), case studies (n=9), conference abstracts/ no full text available (n=17), wrong patient population/ non-pediatric patients (n=5), and wrong drug exposure/ no administration of vincristine (n=1). Following the full-text screening, 28 studies met the eligibility criteria and were included in this systematic review. The study selection process is summarized in Figure 2.2 32 Figure 2.2 PRISMA 2020 flow diagram of articles screened and included in the final review. PRISMA=preferred reporting items for systematic reviews and meta-analyses. 33 2.4.2 Study Characteristics The full study characteristics of the included studies are detailed in Table 2.1 All studies were published on or before the original search date in March 2024. The majority (89.29%) of the included studies used a candidate gene approach, 123, 124, 145, 146, 148-150, 152, 187-203 while only three studies conducted genome-wide or exome-wide analyses. 151, 204, 205 Four studies included replication cohorts to validate the findings observed in their discovery cohorts. 150, 151, 204, 205 Across all studies, a total of 6,481 patients was investigated, comprising 5,112 controls and 1,369 cases, with 1,596,537 genetic markers analyzed. The sample size of patients with both genotype and vincristine peripheral neuropathy data ranged from 24 to 1,131 (Table 1). Most patients were diagnosed with ALL and were of European ancestry. The prevalence of moderate to severe peripheral neuropathy (grade 2–4) varied across studies, ranging from 19.5 to 53.2%, except for one study by Skiles et al., which reported a much lower incidence (2.8%) in Black Kenyan patients. 195 In addition, definitions of cases (patients with peripheral neuropathy) and controls (patients without peripheral neuropathy) also varied among the studies. Several different tools were used to assess neuropathy. The CTCAE was the most commonly employed tool, being used in 17 studies. 124, 145, 146, 148, 150, 151, 189, 190, 192-195, 198, 200-202, 205 Other assessment tools included the modified Balis scale191, 195, 196 and World Health Organization (WHO) scale, 149, 152, 197 each used in three studies, while the pediatric modified total neuropathy (ped-mTNS) score was used in two studies. 195, 202 Less frequently used tools included the Children’s Cancer Group (CCG) toxicity criteria, 123 National Cancer Institute (NCI) common toxicity criteria, 187 Total 34 Neuropathy Score–Pediatric Vincristine (TNS–PV), 205 Spanish Society of Medical Oncology criteria, 203 and motor performance criteria, 188 each reported in a single study. One study did not provide details on the neuropathy assessment method used. 199 35 Author’s name (published year) Study design Sample size (patients n, neoplasm type) Patients Characteristics Vincristine Dose Neuropathy Data Genetic analysis Sex distribution, males, n (%) Reported ancestral distributions Dose, TCD (mg/m2) Neuropathy assessment method N case/ control (definition) N of tested variants Genetic model Aplenc (2003) Candidate gene 533, ALL 173 (32.3%) 94.2% African Americans, 5.8% non-African Americans 1.5, 46.5–64.5 CCG toxicity criteria 28 (grade 3–4) / 505 (grade 0–2) 3 Allelic Plasschaert (2004) Candidate gene 52, ALL 32 (62%) 98.0% white 2.0 other 1.5, 13.5 NCI common toxicity criteria constipation 14 (grade 3–4) / 30 (grade 1–2) 2 Additive Kishi 2007 Candidate gene 240, ALL 142 (59.2%) 69.6% white, 18.3% black, 12.1% other 1.5, 54.0–97.5 NCI-CTCAE 1.0 30 (grade 2–4) / 210 (grade 0–1) 16 Recessive Renbarger (2008) Candidate gene 113, ALL 57 (50.4%) 81.4% Caucasian, 18.6% African Americans Not available NCI-CTCAE 3.0 33 (grade 1–4) / 80 (grade 0) Ancestry as surrogate for genotype Not described Hartman (2010) Candidate gene 34, ALL 18 (53%) Not reported 2.0, 62.0–68.0 Motor performance (Dutch version of the m-ABC) Not reported 10 Additive Egbelakin (2011) Candidate gene 107, ALL Not available 92.92% Caucasians, 5.32% Hispanic or Latino, 0.88% African American, 0.88% Asian 1.5, not reported NCI-CTCAE 3.0 105 (grade 1–4) / 2 (grade 0) 3 Recessive Guilhaumou (2011) Candidate gene 24, solid tumors 14 (58%) All white 1.5, 1.33 (±0.28) NCI-CTCAE 3.0 8 (score ≥3) / 16 controls 3 Not described Moore (2011) Candidate gene 50, various types 25 (50%) 45 Caucasian, 2 Asian, 2 Pacific Islander and 1 Australian Aboriginal. 1.5,1.48 (±0.25) NCI-CTCAE 3.0 6 (grade 3-4) / 44 (grade 1-2) 2 Additive Ceppi (2014) Candidate gene 320, ALL 177 (55.3%) Predominantly French-Canadian 1.5–2.0, 73.5–74.0 NCI-CTCAE 3.0 102 (grade 1–4) / 218 (grade 0) 17 Dominant + Additive Diouf (2015) GWAS Total of 321, ALL: St. Jude cohort: 222, COG cohort: 99 153 (47.6%) St. Jude cohort: 94 (42.3%) COG cohort: 59 (59.6%) 65.1% European, 13.4% African, 0.6% Asian, 13.7% Hispanic, 7.2% Other 1.5, COG cohort: 54.0, St. Jude cohort: 78.0–97.5 NCI-CTCAE 1.0 86 (grade 2-4) / 235 (grade 0–1) 1,576,016 Allelic + Recessive Sims (2016) Candidate gene 53, ALL 33 (62%) 68% white 32% black, 36 Caucasian patients and 17 patients of African descent. 1.5, not reported Modified Balis scale 42 (grade 1–4) / 11 (grade 0) 1 Recessive Lopez-Lopez (2016) Candidate gene 152, ALL 86 (56.6%) Mainly White 1.5, 15.0–30.0 WHO criteria 46 (grade 1–4) / 103 (grade 0) 150 Dominant Gutierrez-Camino (2016) Candidate gene 142, ALL 81 (57%) All European (Spanish) 1.5, 15.0–30.0 NCI-CTCAE 1.0, 36 (grade 2–4) / 106 (grade 0–1) 1 Recessive Kayılıog ̆lu (2017) Candidate gene 115, ALL & solid tumors 46 (63.9%) All European (Turkish) 1.5, ALL patients: 7.7, solid tumors patients: 6.5 NCI-CTCAE 3.0 25 (grade 2–5) / 90 (grade 0) 4 Recessive Abo-Bakr (2017) Candidate gene 97, ALL 57 (59%) Not available (All white) 1.5, not reported NCI-CTCAE 3.0 Not reported 3 Recessive 36 Table 2.1 Summary of characteristics of included studies. PMID=PubMed ID; SD=standard deviation; ALL=acute lymphoblastic leukemia; m-ABC=Movement Assessment Battery for Children; CCG=Children’s Cancer Group; NCI=National Cancer Institute; CTCAE=Common Terminology Criteria for Adverse Events; COG=Children’s Oncology Group; WHO=World Health Organization; ped-mTNS=Pediatric-Modified Total Neuropathy Scale; POG=Pediatric Oncology Group; TNS-PV=Total Neuropathy Scale Pediatric Version. *WES data were available for only 179 patients (24 cases [CTCAE grade 3-4 ] and 155 controls); §Defined according to the presence of any of the following symptoms: progressive confusion, hallucinations, aphasia, speech disturbance, lethargy, drowsiness, seizures, ataxia, dysmetria, dysarthria, nystagmus, facial droop, loss of sensation in extremities, or paresthesia.Skiles (2018) Candidate gene 72, ALL & solid tumors 39 (54%) All black (Kenyan) 2.0, 8.5 NCI-CTCAE 4.0, modified Balis scale, ped–mTNS 2 (grade 2) / 57 (grade 0), 13 with grade 1 5 Additive McClain (2018) Candidate gene 239, ALL 127 (53.1%) All white (Hispanic) Not reported Modified Balis scale 44 (grade 3-4) / 195 (grade 0–1) 5 Additive + Recessive Gutierrez-Camino (2018) Candidate gene (miRNA) 155, ALL 91 (58.7%) Mainly white 1.5, 15.0–30.0 WHO criteria 39 (grade 1-4) / 116 (grade 0) 1910 Dominant Wright (2018) Candidate gene 244, ALL 124 (50.8%) Mainly white 1.5, cases: 48.0–72.0, controls: 51.0–74.8 NCI-CTCAE 4.0 167 (grade 2-4) / 57 (grade 0) 7,908 Recessive + Additive Abaji (2018) EWAS Discovery cohort: 237, ALL* Replication cohort: 405 Discovery: 130 (54.9%) Replication: 215 (53.1%) All white 1.5, not reported NCI-CTCAE 3.0 Discovery: 35 (grade 3–4) / 202 (grade 0) Replication: 13 (grade 3–4) / 392 controls 5527 Additive + Dominant Zgheib (2018) Candidate gene 133, ALL 76 (57.1%) All white 1.5-2.0, cases: 27.9, controls: 66.0 NCI-CTCAE 4.0 26 ( grade 2–3) / 107 (grade 0–1) 6 Recessive + Dominant Li (2019) GWAS Total: 1,131 POG cohort: 1068 ADVANCE Trial cohort: 63 491 (45.9%) All white 1.5, not reported NCI-CTCAE 4.0 & TNS–PV POG cohort: 135 (grade 2–4) / 933 controls ADVANCE Trial cohort: TNS–PV scores 4,749 Dominant + Additive Martin-Guerrero (2019) Candidate gene 152, ALL 86 (56.6%) Mainly white (Spanish) 1.5, 15.0–30.0 WHO criteria 46 (grade 1–4) / 103 (grade 0) 21 Dominant Kavcic (2020) Candidate gene 26, various types 13 (50%) All European 1.5, 10.2 (8-13.7) Not described Not described 6 Recessive Goodenough (2022) Candidate gene 990, ALL 502 (50.7%) 84.1% White, 10.5% Black, 5.4% Other 1.5 44.0 (±26.5) NCI-CTCAE 5.0 158 (grade 2–4) / 832 controls 1 Recessive Klumpers (2022) Candidate gene 104, various types 55 (52.9%) 98.1% Caucasians 1.9% Other 1.5, 25.9 (1.4–126.0) NCI-CTCAE 4.0 24 (grade 2–4) / 80 (grade 0–1) 47 Recessive + Dominant + Additive Mirjam (2022) Candidate gene 85, various types 48 (56%) 81% European 19% non-European 1.5, 13.91 (±9.23) NCI-CTCAE and ped-mTNS score CTCAE score: 40 grade 2–4) / 45 (grade 0–1) ped-mTNS score: 55 (≥5) / 11 (<5) 98 Additive Burgueño-Rodríguez (2023) Candidate gene 155, ALL 113 (56.5%) 69.2% European, 20.1% Native American, 10.7% African 1.5, not reported Spanish Society of Medical Oncology criteria 24 cases / 131 controls§ 10 Additive + Dominant + Recessive 37 2.4.3 Overview of Studied Genes The included studies analyzed genetic variants across a wide range of genes involved in vincristine pharmacokinetics and pharmacodynamics, neuropathy-related pathways, and other biological pathways. Eight genes were identified as part of vincristine pharmacokinetic pathways. These included three genes involved in vincristine transport –ABCB1, ABCC1, and ABCC2– and five genes related to vincristine metabolism: CYP3A4, CYP3A5, VDR, SLC22A14 and DPYD. Seven genes were implicated in vincristine's pharmacodynamics, including centrosome-related gene (CEP72), microtubule-related genes (MAPT, TUBB3), and actin-related genes (ACTG1, CAPG, SYNE2, and FGD4). In addition, seven genes were associated with neuropathy-related pathways. These included COCH, SLC5A7, TMEM215, NDRG1, GARS, FIG4, and SEPTIN9. Finally, nine genes were identified in other unrelated pathways to vincristine's direct pharmacology, including two mitochondrial genes (MRPL47, NDUFAF6) and seven other genes (MTNR1B, BAHD1, GLCCI1, LAMB3, LIPA, ATXN7L3B, and ETAA1). Vincristine transport across cell membranes is primarily mediated by ATP-binding cassette (ABC) transporter proteins, which play a crucial role in drug efflux and distribution. 206 ABCB1 (P-glycoprotein) is essential for the biliary excretion of vincristine and is expressed on the apical surface of hepatocytes. 206 Furthermore, ABCC1 (multidrug resistance protein 1, MRP1) exports vincristine from within cells into blood, particularly at the basolateral membrane of enterocytes and kidney epithelial cells, facilitating vincristine’s systemic clearance. 149, 207, 208 Similarly, overexpression of ABCC2 (MRP2), another ABC transporter, has been linked to increased in 38 vitro cellular resistance to vincristine. 209, 210 Vincristine metabolism is primarily mediated by the cytochrome P450 family 3 subfamily A member 5 (CYP3A5) enzyme, and to a lesser extent by CYP3A4, both of which catalyze the conversion of vincristine into its major amine metabolite (M1) and minor metabolites (M2 and M4). 122 Additionally, the vitamin D receptor (VDR) may indirectly affect vincristine metabolism by modulating the expression of CYP3A4 enzyme. 211 DPYD (dihydropyrimidine dehydrogenase) might influence metabolic pathways through enzymatic interactions, 206 though its exact role in vincristine metabolism is unclear. Vincristine exerts its cytostatic effect via binding to the β-subunit of tubulin and inhibiting the polymerization of microtubules, which are essential for cell division and intracellular transport, consequently causing mitotic arrest during metaphase. 212 During cell division, there is a well-known interaction between microtubules and the actin cytoskeleton; the latter contributes to mitotic spindle assembly and formation. 213 CEP72 encodes a protein critical for centrosome function and microtubule organization, 151 while microtubule-associated genes, such as MAPT (tau) and TUBB3 (class III β-tubulin), are vital for maintaining microtubule stability. 152 Additionally, genes encoding actin-related proteins, such as ACTG1 and CAPG, contribute to cytoskeletal remodeling and intracellular transport, and their disruption may exacerbate neuronal vulnerability to vincristine-induced damage. 150 SYNE2 and FGD4 are known to regulate cytoskeletal integrity and axonal transport. 202, 204 39 Several genes were involved in neuronal function and maintenance. COCH encodes cochlin, a protein that supports extracellular matrix organization and neuron survival, and its variants have been identified as protective against neuropathy. 205 SLC5A7 encodes a membrane choline transporter critical for acetylcholine synthesis in cholinergic neurons, and dysfunction of this gene predisposes individuals to neurotoxicity by impairing neuronal function. 148 TMEM215 and NDRG1 are associated with neurogenesis and axonal repair, and genetic variations in these genes may reduce neuronal resilience to vincristine. 151, 202 Variants in the GARS gene, which encodes glycyl-tRNA synthetase, can cause neuropathic pain by impairing axonal transport. 202 FIG4 and SEPTIN9 are involved in axonal development and vesicle trafficking, respectively, and their variations are associated with increased risk of vincristine-induced neuropathy. 202 Finally, genes involved in mitochondrial function and other pathways unrelated to vincristine’s direct pharmacological action have also been associated with neuropathy risk. MRPL47 and NDUFAF6 are essential for mitochondrial protein synthesis and respiratory chain assembly and contribute neuronal energy metabolism. 151, 204 Other genes: MTNR1B (melatonin receptor), BAHD1 (bromo adjacent homology domain-containing protein), GLCCI1 (glucocorticoid-induced transcript 1), LAMB3 (laminin subunit beta-3), LIPA (lipase A), and ATXN7L3B (ataxin-7-like protein 3B) may indirectly influence neuropathy risk through their roles in cellular signaling, inflammation, or oxidative stress. 148, 151, 204, 205 ETAA1, which encodes a DNA damage repair protein, has also been associated with increased neuropathy risk, likely through heightened neuronal vulnerability to DNA damage. 151 A brief summary of these genes and their associated biological pathways is provided in Figure 2.3. 40 Figure 2.3 Schematic overview of the function of genes associated with vincristine-induced peripheral neuropathy in pediatric cancer patients. Figure was created with BioRender.com. 41 2.4.4 Summary of Significant Genetic Variants Within the identified genes, several genetic variants were significantly associated with the risk of vincristine-induced peripheral neuropathy (Table 2.2). Seventeen genetic variants in three ATP-binding cassette transporter genes (ABCB1, ABCC1, ABCC2) were identified. Of these, 11 variants demonstrated a protective effect against vincristine neuropathy risk, whereas 7 variants were associated with an increased risk. The strongest protective associations were observed for rs3740066 and rs12826 in ABCC2, with odds ratio (OR) of 0.23 (95% confidence interval [CI]: 0.10-0.53) and 0.24 (95% CI: 0.10–0.54), respectively. Conversely, rs3784867 in ABCC1 exhibited the strongest risk association (OR=4.91, 95% CI: 1.99-12.10). Variants in genes associated with vincristine metabolism, including CYP3A5, DPYD and VDR, were also identified, with different variants within these genes being associated with either increased or reduced risks of developing vincristine peripheral neuropathy. Additionally, 10 variants in cytoskeleton-related genes and microRNAs (miRNAs) targeting these genes were associated with vincristine peripheral neuropathy. These included variants in MAPT, TUBB3, ACTG1, CAPG, CEP72, SYNE2 and FGD4. Most of these associations were identified through candidate gene studies, while only two variants in two genes (CEP72 and SYNE2) were discovered in GWAS/EWAS studies. Of the 10 variants, two variants were associated with microtubules-related genes (MAPT and TUBB3). MAPT variants were protective, while TUBB3 variants increased neuropathy risk. Two variants in CEP72 were associated with both risk and protection against peripheral neuropathy, depending on the specific allele. The CEP72 gene variant (rs924607) has been the most extensively studied variant in relation to vincristine-induced neuropathy (CTCAE grade 2-4). Diouf et al. reported a significant 42 association between homozygous TT risk genotype and increased neuropathy risk in both their discovery and replication cohorts. 151 While three independent replication studies confirmed this association, 148, 199, 200 three others failed to replicate these findings. 192, 198, 201 The remining six variants were located in actin-related genes (ACTG1, CAPG, SYNE2 and FGD4), two of which were associated with protection and four with increased risk. The strongest protective association was noted for rs3770102 in CAPG with an effect size of 0.1 although the uncertainty was high (95% CI: 0.01-0.8). One variant (rs1013940) in the hereditary neuropathy-associated gene (the solute carrier family 5 member 7 (SLC5A7)) was associated with a markedly increased risk of vincristine neuropathy (OR=8.60, 95% CI: 1.68–44.15), but the large CI underscores the need for further validation. Importantly, except for a variant in SYNE2, 204 all these associations were reported solely in discovery cohorts, with no replication studies performed for validation. Furthermore, these variants have not been reported as significantly associated with vincristine-induced neuropathy in any other GWAS or EWAS studies. GWAS or EWAS uncovered significant associations between vincristine-induced neuropathy and eight novel variants in genes not previously associated with neuropathy, vincristine mechanism of action or metabolism (Table 2.2). These included variants in COCH, ETAA1, MTNR1B, NDUFAF6 and TMEM215, which showed significant associations with vincristine peripheral neuropathy in both discovery and replication cohorts. In contrast, associations for variants in BAHD1, and MRPL4 were observed only in the discovery cohort and did not replicate in the independent validation cohort. Among these, the variants in BAHD1 and COCH conferred protection against neuropathy, with the strongest protective association observed for COCH 43 (OR=0.27, 95% CI: 0.16–0.50). 205 Conversely, variants in ETAA1, MRPL4, NDUFAF6, and TMEM215 were associated with an increased risk of neuropathy. The variant in ETAA1 demonstrated a particularly strong effect on neuropathy risk, especially in the replication cohort from Diouf et al., though with relatively wide confidence intervals (OR=10.4, 95% CI: 2.97–36.15). 151 Variants in NDUFAF6 and TMEM215 also showed large effect sizes with acceptable precision across both discovery and replication cohorts. 151 Finally, Diouf et al. reported a variant in MTNR1B as protective against neuropathy, with large effect sizes and high precision in both discovery (OR=0.23, 95% CI: 0.13–0.40) and replication cohorts (OR=0.24, 95% CI: 0.08–0.76). 151 However, these findings were not replicated in a study by Zgheib et al. 198 Gutierrez-Camino et al. identified two miRNA variants associated with vincristine-induced peripheral neuropathy. 197 One variant was associated with the axon-guidance pathway, while the other could not be associated with any known pathways related to vincristine's mechanism of action or neurotoxicity. 44 Gene Variant Type Allele (Ref/ Alt) Author (Year of publication) Cohort size Effect size (95% CI); p-value Impact on neuropathy risk (Genetic model) Cases, N Controls, N Candidate-gene studies ABCB1 rs4728709 UTR 5’ C/T Ceppi et al (2014) 64 (CTCAE grade 1-2) 218 (CTCAE grade 0) 0.3 (0.1–0.9); p=0.02 ↓ Risk (Dominant) rs10244266 Intronic T/G Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 2.60 (1.16–5.83); p=0.021 ↑ Risk (Dominant) rs10274587 intronic G/A Lopez-lopez et al (2016) 27 (WHO grade 1–2) 103 (WHO grade 0) 3.48 (1.36–8.86); p=0.009 ↑ Risk (Dominant) rs10268314 intronic T/C Lopez-lopez et al (2016) 27 (WHO grade 1–2) 103 (WHO grade 0) 3.19 (1.23–8.25); p=0.018 ↑ Risk (Dominant) rs9282564 missense T/C Burgueño-Rodríguez et al (2023) 24 cases§ 131 controls§ OR not reported; p=0.001 ↓ Risk (Dominant) ABCC1 rs3784867 intronic C/T Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 4.91 (1.99-12.10); p=5.34x10−5* ↑ Risk (Additive) rs11864374 intronic G/A Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.35 (0.15–0.79); p=0.008 ↓ Risk (Dominant) rs3743527 3’ UTR C/T Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.32 (0.13–0.79); p=0.008 ↓ Risk (Dominant) rs1967120 intronic T/C Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.37 (0.17–0.82); p=0.012 ↓ Risk (Dominant) rs17501331 intronic A/G Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 2.50 (1.10–5.68); p=0.029 ↑ Risk (Dominant) rs12923345 intronic T/C Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 2.39 (1.08–5.25); p=0.031 ↑ Risk (Dominant) rs11642957 intronic T/C Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.43 (0.19–0.98); p=0.047 ↓ Risk (Dominant) ABCC2 rs12826 3’ UTR G/A Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.24 (0.10–0.54); p=0.036 ↓ Risk (Dominant) rs2073337 intronic A/G Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.25 (0.11-0.59); p=0.001 ↓ Risk (Dominant) rs3740066 missense G/A Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.23 (0.10-0.53); p=0.036 ↓ Risk (Dominant) rs4148396 intronic C/T Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 0.36 (0.16–0.81); p=0.013 ↓ Risk (Dominant) rs11190298 3’ UTR G/A Lopez-lopez et al (2016) 46 (WHO grade 1–4) 103 (WHO grade 0) 2.44 (1.01–5.86); p=0.049 ↑ Risk (Recessive) CYP3A4 rs2740574 5’ UTR A/G Aplenc et al (2003) 28 (CCG grade 3-4) 505 (CCG 0-2) 0† (0-0.75); p=0.024 ↓ Risk (Dominant) CYP3A5 rs776746 intronic A/G Aplenc et al (2003) 28 (CCG grade 3-4) 505 (CCG 0-2) 0.13 (0.003-0.83); p=0.021 ↓ Risk (Recessive) Kishi et al (2007) 30 (CTCAE grade 2–4) 210 (CTCAE grade 0–1) 2.76 (1.34 -5.71); p=0.006 ↑ Risk (Recessive) Egbelakin et al (2011) 105 (CTCAE grade 1–4) 2 (CTCAE grade 0) OR not reported; p=0.030 ↑ Risk (Recessive) DPYD rs12144462 intronic G/A Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 0.25 (0.11-0.58); p=9.83x10−4* ↓ Risk (Additive) SLC5A7 rs1013940 missense A/G Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 8.60 (1.68-44.15); p=9.00x10−4* ↑ Risk (Additive) ACTG1 rs1135989 synonymous G/A Ceppi et al (2014) 38 cases (CTCAE grade 3-4) 218 controls (grade 0) 2.8 (1.3–6.3); p=0.008 ↑ Risk (Dominant) CAPG rs2229668 missense G/A Ceppi et al (2014) 38 cases (CTCAE grade 3-4) 218 controls (grade 0) 2.1 (1.1-3.7); p=0.02 ↑ Risk (Additive) rs377010 5’UTR C/A Ceppi et al (2014) 38 cases (CTCAE grade 3-4) 218 controls (grade 0) 0.1 (0.01-0.8); p=0.009 ↓ Risk (Additive) CEP72 rs924607 promoter region C/T Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 3.43 (1.15-10.3); p=0.02 ↑ Risk (Recessive) Kavcic et al (2020) Not described (Total of 26 patients) OR not reported (95% CI: 1.761-12.931); p=0.009 ↑ Risk (Recessive) Goodenough et al (2022) 158 (CTCAE grade 2–4) 32 (not defined) 2.47 (1.15–5.31); p=0.02* ↑ Risk (Recessive) rs71585289 intronic C/G Mirjam et al (2022) Total ped-mTNS (Linear regression) 0.84 (0.75–0.93); p<0.0001‡ ↓ Risk (Additive) MAPT rs11867549 intronic A/G Martin-Guerrero et al (2019) 18 (WHO grade 3–4) 103 (WHO grade 0) 0.21 (0.04–0.96); p=0.020 ↓ Risk (Dominant) MTNR1B rs12786200 intronic C/T Zgheib et al (2018) 26 (CTCAE grade 2–3) 107 (CTCAE grade 0–1) 0.59 (0.22–1.62); p=0.563 Not significant ETAA1 rs35777125 intronic G/A Mirjam et al (2022) 40 (CTCAE grade 2–4) 45 (CTCAE grade 0–1) 0.31 (0.16–0.57); p=0.0467 ↓ Risk (Additive) Total ped-mTNS (Linear regression) 0.91 (0.82–1.02); p=0.0007 ↓ Risk (Additive) LAMB3 rs2076356 synonymous C/A Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 2.41 (1.39-4.17); p=9.44x10−4 ↑ Risk (Additive) LIPA rs1051338 missense A/C Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 0.42 (0.25-0.71); p=8.08x10−4 ↓ Risk (Additive) SLC22A14 rs818818 missense T/C Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 4.65 (1.68-12.88); p=9.27x10−4 ↑ Risk (Additive) rs818816 intronic T/C Wright et al (2018) 167 (CTCAE grade 2–4) 56 (CTCAE grade 0) 4.65 (1.68-12.88); p=9.27x10−4 ↑ Risk (Additive) TUBB3: miR-202 rs12355840 intergenic T/C Martin-Guerrero et al (2019) 27 (WHO grade 1–2) 103 (WHO grade 0) 2.88 (1.07–7.72); p=0.032 ↑ Risk (Dominant) rs4395073; rs4558416 3’UTR CA Martin-Guerrero et al (2019) 27 (WHO grade 1–2) 103 (WHO grade 0) OR not reported; p=0.032 ↑ Risk (Dominant) TG Martin-Guerrero et al (2019) 27 (WHO grade 1–2) 103 (WHO grade 0) OR not reported; p=0.041 ↓ Risk (Dominant) VDR rs1544410 intronic G/A Kishi et al (2007) 30 (CTCAE grade 2–4) 210 (CTCAE grade 0–1) 2.16 (1.03-4.51); p=0.042 ↑ Risk (Dominant) miR-3117-3p rs12402181 intronic G/A Gutierezz-Gamino et al (2018) 39 (WHO grade 1–4) 116 (WHO grade 0) 0.16 (0.05–0.55); p=0.00042 ↓ Risk (Dominant) miR-4481 rs7896283 intronic T/C Gutierezz-Gamino et al (2018) 39 (WHO grade 1–4) 116 (WHO grade 0) 2.62 (1.15–5.95); p=0.0173 ↑ Risk (Dominant) miR-6076 rs35650931 intronic G/C Gutierezz-Gamino et al (2018) 39 (WHO grade 1–4) 116 (WHO grade 0) 0.22 (0.05–0.97); p=0.0175 ↓ Risk (Dominant) GARS rs1049402 missense G/C Mirjam et al (2022) 40 (CTCAE grade 2–4) 45 (CTCAE grade 0–1) 0.52 (0.28–0.99) p=0.0107 ↓ Risk (Additive) Total CTCAE (Linear regression) 0.71 (0.62–0.82); p=0.0013 ↓ Risk (Additive) 45 Table 2.2 Summary of statistically significant genetic associations with vincristine-induced peripheral neuropathy in the pediatric oncology population. §Defined according to the Spanish Society of Medical Oncology criteria based on presence of any of the following symptoms: progressive confusion, hallucinations, aphasia, speech disturbance, lethargy, drowsiness, seizures, ataxia, dysmetria, dysarthria, nystagmus, facial droop, loss of sensation in extremities, and paresthesia; †No cases with variant allele; ‡exact p-value is not reported; *remained significant after correction for multiple testing. Allelic model: assumes that the impact of each specific allele on the risk is independent; Additive model: assumes the effect of carrying one copy of the risk allele is exactly half of the effect of carrying two copies; Dominant model: assumes that carrying just one copy of the risk allele is sufficient to exert its full effect on the risk; Recessive model: assumes that the risk allele will only influence the phenotype if two copies are present (i.e., the individual is homozygous for the risk allele).NDRG1 rs2272653 intronic G/A Mirjam et al (2022) Total CTCAE (Linear regression) 0.84 (0.73–0.96); p<0.0001‡* ↓ Risk (Additive) FIG4 rs9885672 5’UTR T/C Mirjam et al (2022) Total ped-mTNS (Linear regression) 1.44 (1.30–1.59); p<0.0001‡* ↑ Risk (Additive) rs10659 3’UTR G/A Mirjam et al (2022) Total ped-mTNS (Linear regression) 1.53 (1.34–1.75); p<0.0001‡* ↑ Risk (Additive) FGD4 rs12823621 intronic G/A Mirjam et al (2022) Total ped-mTNS (Linear regression) 1.43 (1.27–1.60); p<0.0001‡* ↑ Risk (Additive) rs73083501 intronic C/T Mirjam et al (2022) Total ped-mTNS (Linear regression) 0.86 (0.76–0.97); p<0.0001‡* ↓ Risk (Additive) SEPTIN9 rs11650934 5’UTR C/G Mirjam et al (2022) Total ped-mTNS (Linear regression) 0.62 (0.54–0.71); p<0.0001‡* ↓ Risk (Additive) GWAS/EWAS studies ATXN7L3B rs7963521 none T/C Li et al (2019) – POG cohort 135 (CTCAE grade 2–4) 933 (not defined) 2.23 (1.49–3.35); p=1.02x10−4 ↑ Risk (Additive) Li et al (2019) – ADVANCE cohort Maximum neuropathy score (TNS–PV scores) 2.16 (0.53–3.70); p=6.57x10−3 ↑ Risk (Additive) BAHD1 rs3803357 missense C/A Abaji et al (2018) 35 (CTCAE grade 3–4) 202 (CTCAE grade 0) 0.3 (0.2–0.8); p=0.009 ↓ Risk (Dominant) CEP72 rs924607 promoter region C/T Diouf et al (2015) – St. Jude cohort 64 (CTCAE grade 2–4)) 158 (CTCAE grade 0–1) 2.43 (1.70-3.49); p=1.25x10−6 ↑ Risk (Allelic) Diouf et al (2015) – COG cohort 22 (CTCAE grade 2–4)) 74 (CTCAE grade 0–1) 4.1 (1.86-9.01); p=0.0004 ↑ Risk (Allelic) COCH rs1045644 missense T/G Li et al (2019) – POG cohort 135 (CTCAE grade 2–4) 933 (not defined) −1.28 (−1.86,−0.69); p=1.72x10−5 ↓ Risk (Dominant) Li et al (2019) – ADVANCE cohort Maximum neuropathy score (TNS–PV scores) −3.56 (−5.45,−1.67); p=3.80x10−4 ↓ Risk (Dominant) ETAA1 rs17032980 intergenic A/G Diouf et al (2015) – St. Jude cohort 64 (CTCAE grade 2–4)) 158 (CTCAE grade 0–1) 3.17 (1.95-5.17); p=3.67×10−6 ↑ Risk (Allelic) Diouf et al (2015) – COG cohort 22 (CTCAE grade 2–4)) 74 (CTCAE grade 0–1) 10.4 (2.97-36.15); p=0.0002 ↑ Risk (Allelic) GLCCI1 rs7792939 intronic A/G Li et al (2019) – ADVANCE cohort Maximum neuropathy score (TNS–PV scores) 2.83 (1.82-4.39); p=2.39x10−6* ↑ Risk (Additive) MRPL47 rs10513762 missense C/T Abaji et al (2018) 35 (CTCAE grade 3–4) 202 (CTCAE grade 0) 3.90 (1.5–10); p=0.004 ↑ Risk (Dominant) MTNR1B rs12786200 intronic C/T Diouf et al (2015) – St. Jude cohort 64 (CTCAE grade 2–4)) 158 (CTCAE grade 0–1) 0.23 (0.13- 0.40); p=1.58×10−7 ↓ Risk (Allelic) Diouf et al (2015) – COG cohort 22 (CTCAE grade 2–4)) 74 (CTCAE grade 0–1) 0.24 (0.08- 0.76); p=0.016 ↓ Risk (Allelic) NDUFAF6 rs7818688 intronic C/A Diouf et al (2015) – St. Jude cohort 64 (CTCAE grade 2–4)) 158 (CTCAE grade 0–1) 4.26 (2.45-7.42); p=3.05×10−7 ↑ Risk (Allelic) Diouf et al (2015) – COG cohort 22 (CTCAE grade 2–4)) 74 (CTCAE grade 0–1) 4.59 (1.35- 15.59); p=0.014 ↑ Risk (Allelic) SYNE2 rs2781377 nonsense G/A Abaji et al (2018) 35 (CTCAE grade 3–4) 202 (CTCAE grade 0) 2.7 (1.2–6.0); p=0.02 ↑ Risk (Additive) TMEM215 rs4463516 intronic C/G Diouf et al (2015) – St. Jude cohort 64 (CTCAE grade 2–4)) 158 (CTCAE grade 0–1) 2.89 (1.90- 4.39); p=6.83×10−7 ↑ Risk (Allelic ) Diouf et al (2015) – COG cohort 22 (CTCAE grade 2–4)) 74 (CTCAE grade 0–1) 4.94 (2.65- 14.79); p=0.004 ↑ Risk (Allelic) 46 2.5 Discussion The results from the present systematic review indicate that pharmacogenomic factors play an important role in the susceptibility to vincristine-induced peripheral neuropathy in patients with childhood cancers. Several genetic variations, primarily in genes implicated in vincristine pharmacokinetics, pharmacodynamics, and neuronal function, were identified. However, the overall evidence remains inconsistent, with limited replication across studies. Most of the identified associations were not confirmed in subsequent studies. This lack of consistent replication underscores the need for larger, well-powered investigations to explore and validate genetic associations and refine the understanding of vincristine-induced neuropathy risk. In this review, when genetic associations with vincristine neuropathy are referred to as “significant”, statistical significance is indicated rather than clinical significance. Although statistically significant associations may provide probability of genetic influences on vincristine peripheral neuropathy risk, the clinical relevance of these findings depends on several factors, including the effect size (i.e., magnitude of the variant effect [e.g., odds ratio]), allele frequency (i.e., how commonly the genetic variations occur in patient populations), and the incidence and severity of neuropathy symptoms. However, spurious associations may arise due to several factors, including population stratification (systematic genetic differences between subgroups), multiple testing without appropriate correction (increasing the risk of false positives), small sample sizes (leading to overestimation of effect sizes), and unaccounted confounding variables. Therefore, while associations that did not pass the stringent significance threshold may still be biologically relevant, statistical significance should always be interpreted in the context of the 47 study design. Replication in independent cohorts and functional validation studies are essential to establish the robustness and biological plausibility of observed associations. Regarding the effect size of the identified variants, several genetic variants exhibited clinically significant effect sizes (i.e., increase/decrease neuropathy risk by ≥ 3-fold) in at least one study. These include CEP72 rs924607 (OR=4.1, 95% CI: 1.86–9.01), 151 ABCB1 rs10274587 (OR=3.48, 95% CI: 1.36–8.86), 149 ABCC1 rs3784867 (OR=4.91, 95% CI: 1.99–12.10), 148 SLC5A7 rs1013940 (OR=8.6, 95% CI: 1.68–44.15), 148 NDUFAF6 rs7818688 (OR=4.26, 95% CI: 2.45–7.42), 151 ETAA1 rs17032980 (OR=3.17, 95% CI: 1.95–5.17), 151 MRPL47 rs10513762 (OR=3.3, 95% CI: 1.47–7.7), 204 and SLC22A14 rs818818 (OR=4.65, 95% CI: 1.68–12.88). 214 Protective variants were also reported, such as ABCC1 rs3743527 (OR=0.32, 95% CI: 0.13–0.79), ABCC2 rs3740066 (OR=0.23, 95% CI: 0.10–0.53), DPYD rs12144462 (OR=0.25, 95% CI: 0.11–0.58), CAPG rs377010 (OR=0.1, 95% CI: 0.01–0.8), MAPT rs11867549 (OR=0.21, 95% CI: 0.04–0.96), MTNR1B rs12786200 (OR=0.23, 95% CI: 0.13–0.40), and BAHD1 rs3803357 (OR=0.3, 95% CI: 0.2–0.8). However, most of these identified variants were not replicated in subsequent studies. Non-significant genetic associations identified across the included studies are summarized in Table A1. The association between rs924607 in CEP72 and vincristine peripheral neuropathy has been validated in several independent replication studies, though findings suggest the effect of CEP72 on peripheral neuropathy risk likely differs depending on treatment phase and genetic background. 151, 192 For instance, the association was not significant during the induction phase in a white Spanish cohort or during induction or continuation treatment in a white Arab population. 198 48 The variability in allele frequencies across populations likely contributes to observed differences in neuropathy risk among individuals of different ancestries. For instance, evidence suggests that Kenyan patients may be less susceptible to severe neuropathy compared to those of European ancestry. A study of Kenyan pediatric cancer patients reported that the incidence of clinically relevant neuropathy was 5% lower in Black children compared to European children, despite receiving higher vincristine doses (2.0 mg/m² vs. 1.5 mg/m² in Western countries) than did European children. 195 This difference could partially be attributed to the prevalence of the functional CYP3A5 variants (CYP3A5*3 and CYP3A*6) that lead to loss of CYP3A5 enzymatic activity, and are present in approximately 80% of individuals of European ancestry but are less frequent (~20–30%) among individuals of African ancestry. 215, 216 Consequently, Kenyan patients, more likely to express functional CYP3A5, may metabolize vincristine more efficiently than Caucasians (mostly CYP3A5 non-expressers), resulting in decreased systemic vincristine exposure and reduced neuropathy risk. 146 Ancestry was only accounted/adjusted for in two studies –Aplenc et al., 2003 and Diouf et al., 2015 – although the significant associations reported by Diouf et al. did not maintain statistical significance after adjusting for genetic ancestry and vincristine cumulative dose. Future studies should account for differences in genetic ancestry distributions between the case/control groups to limit the influence of population stratification and account for ancestry-specific effects arising from differences in allele frequencies. Table 2.3 provides an overview of allele frequencies for variants associated with a threefold change in vincristine neuropathy risk, stratified by different population, based on the Genomes Aggregation Database (gnomAD v4.1.0). 217 49 Effect allele frequencies across different ancestral populationsa,b Gene Variant (Effect allele) African/ African American Latino/ Admixed American Ashkenazi Jewish East Asian South Asian European Finnish Other ABCB1 rs4728709 (T) 0.3726 0.1136 0.06033 0.1392 0.06744 0.06728 0.07147 0.1486 rs10274587 (A) 0.1536 0.1094 0.1500 0.05995 0.1509 0.1258 0.04804 0.1249 rs10268314 (C) 0.1712 0.1114 0.1503 0.05920 0.1506 0.1256 0.04739 0.1282 rs9282564 (C) 0.01469 0.03260 0.02253 0.000156 0.02569 0.1072 0.1702 0.07474 ABCC1 rs3784867 (T) 0.3397 0.2949 0.2898 0.1524 0.3044 0.1946 0.1569 0.2879 rs3743527 (T) 0.1470 0.2143 0.2085 0.4388 0.4514 0.2112 0.2979 0.2003 ABCC2 rs12826 (A) 0.1874 0.3433 0.3558 0.2295 0.3229 0.3730 0.3379 0.3374 rs2073337 (G) 0.4365 0.3755 0.4036 0.2265 0.3825 0.3852 0.3622 0.3818 rs3740066 (A) 0.2578 0.3467 0.3475 0.2285 0.3274 0.3739 0.3412 0.3518 BAHD1 rs3803357 (A) 0.7681 0.6271 0.5913 0.8134 0.6375 0.4836 0.5771 0.5456 CEP72 rs924607 (T) 0.1148 0.3270 0.3640 0.3401 0.3867 0.4147 0.5180 0.3445 COCH rs1045644 (G) 0.2644 0.6356 0.5955 0.3356 0.3611 0.6397 0.6482 0.5636 CYP3A5 rs776746 (G) 0.2918 0.7855 0.9250 0.7373 0.7280 0.9329 0.9329 0.8591 DPYD rs12144462 (A) 0.02636 0.05286 0.1153 0.2174 0.09161 0.07659 0.05444 0.07700 ETAA1 rs17032980 (G) 0.4290 0.1762 0.2158 0.1798 0.2728 0.1215 0.1852 0.2177 rs35777125 (A) 0.01713 0.04718 0.1050 0.000335 0.05800 0.1019 0.08961 0.08916 MAPT rs11867549 (G) 0.04564 0.1276 0.1859 0.01913 0.1295 0.2575 0.3715 0.1515 MRPL47 rs10513762 (T) 0.09688 0.1530 0.06331 0.1236 0.1629 0.07405 0.08215 0.08321 MTNR1B rs12786200 (T) 0.2203 0.1851 0.1971 0.3872 0.1308 0.2234 0.2535 0.2194 NDUFAF6 rs7818688 (A) 0.1044 0.1215 0.1210 0.05922 0.1220 0.1455 0.1743 0.1307 SLC22A14 rs818818 (C) 0.8348 0.8179 0.8225 0.7555 0.8392 0.8833 0.8568 0.8577 rs818816 (C) 0.8358 0.8303 0.8112 0.7435 0.8331 0.8822 0.8551 0.8600 SLC5A7 rs1013940 (G) 0.02499 0.1864 0.05036 0.1270 0.02882 0.08562 0.1155 0.07519 TMEM215 rs4463516 (G) 0.5634 0.7739 0.7147 0.7664 0.7529 0.7339 0.8179 0.6853 Table 2.3 Ancestry-specific allele frequencies of variants associated with 3-fold increase/decrease of vincristine-induced peripheral neuropathy risk. aAccording to ancestral populations in Genome Aggregation Database (gnomAD v4.1.0); bcoloured according to allele frequencies (grey indicates frequencies <0.0100 and shades of blue indicate higher frequencies, with shades darkening with increased frequency categories [0.0100-0.1999, 0.2000-0.3999, 0.4000-0.5999, 0.6000-0.7999 and 0.8000-1.000]). The phenotypic heterogeneity among the included studies (i.e., variability in defining cases and controls) limits the direct comparison and interpretation of the results. This is further compounded by the inclusion of control groups contaminated with cases of mild neuropathy (i.e., neuropathy grade 0–1) in several studies (Table 2.1) which could potentially lead to an underestimation of true effect sizes. While the majority of the included studies (64.2%) used the NCI-CTCAE criteria to define peripheral neuropathy, other studies relied on alternative scales, such as the modified Balis scale, WHO scale, or other methods, to quantify vincristine peripheral 50 neuropathy. This lack of standardization undermines cross-study comparability and the consistency of findings. To help actualize the potential of pharmacogenomic research, future studies should adopt standardized methods for defining and reporting vincristine-induced peripheral neuropathy. Additionally, future studies are warranted to validate genetic findings in independent replication cohorts of pediatric populations and elucidate the biological mechanisms by which these variants contribute to neuropathy risk through functional studies. To determine the clinical implications of these variants, including their potential utility in personalizing vincristine dosing in pediatric patients, clinical trials designed to assess the impact of genotype-guided interventions on patient outcomes could provide evidence for their utility in predicting vincristine neuropathy or response to guide therapeutic decision-making. Of note, most of the conducted studies were candidate-gene studies, where only specific variants within pre-defined genes were selected for the analyses. Such studies are inherently susceptible to bias, including inadequate correction for multiple comparisons, limited sample sizes, and population stratification. Furthermore, while candidate-gene approach has been instrumental in identifying statistically significant variants, it overlooks the contributions of unrecognized genes or pathways involved in neuropathy risk, limiting the broader understanding of its genetic architecture. Pharmacogenomic studies provide a more comprehensive and unbiased approach by exploring the entire genome for genotype-phenotype associations. Studies that employ GWAS or EWAS analyses expanded knowledge by uncovering novel genotype-phenotype associations that were not previously described in relation to the risk of vincristine-induced peripheral neuropathy (Figure 2.4). 51 GWAS typically scan the entire genome for associations between common variants and phenotypic traits, covering both coding and non-coding regulatory regions. This broad coverage enables GWAS to identify variants that influence gene expression or splicing, many of which lie outside protein-coding regions. Most GWAS-identified hits tend to be common regulatory variants with small effect sizes, and statistical significance is typically defined by a genome-wide threshold of p < 5.0×10⁻⁸ due to the large number of tests conducted. In contrast, EWAS focuses exclusively on the protein-coding regions of the genome, representing ~2% of the entire genome. It can interrogate both common and rare functional variants—such as missense, nonsense, and splice site variants—that are more likely to have a direct effect on protein structure and function. EWAS can be particularly powerful for identifying rare coding variants through both single-variant testing and pooled rare variant burden analyses. Given the lower number of variants tested, the significance threshold for EWAS is typically less stringent (e.g., p < 2.5 × 10⁻⁶), but varies slightly depending on study design and variant inclusion criteria. The growing availability of high-throughput sequencing technologies is expected to further facilitate such genome-wide and exome-wide analyses by enabling rapid and cost-effective identification of genetic variants associated with vincristine-induced neuropathy across the genome. 52 Figure 2.4 Discovery of genetic variants associated with vincristine peripheral neuropathy risk. The figure represents the effect size vs allele frequency of the discovered variants within genes associated with vincristine peripheral neuropathy in pediatric cancer patients; §was independently replicated; VIPN=vincristine-induced peripheral neuropathy. As pharmacogenomic studies inherently require large sample sizes to detect significant effects, larger and adequately powered studies are needed to investigate these associations as well as associations with other minor alleles in the studied genes. Half of the included studies had a study population of fewer than 150 patients and were thus limited by a relatively small sample size and low statistical power to detect meaningful associations. Small sample sizes also increase the likelihood of false-positive findings, especially in studies testing multiple genetic variants. Approximately half of the reported significant associations either failed to pass stringent significance thresholds (i.e., adjusting the significance threshold with Bonferroni or False Discovery Rate correction), or did not apply corrections for multiple testing. 53 Given the complexity inherent in vincristine-induced peripheral neuropathy, a promising approach to assess the influence of pharmacogenomics on the risk of vincristine neuropathy is the development of polygenic risk scores. Unlike single-gene traits, vincristine-induced neuropathy is influenced by a multitude of factors, including genetic variations with low to moderate effect sizes, as well as clinical and demographic factors. While individual genetic variants with low to moderate effect sizes may have limited predictive power, combining their effects into risk scores may enhance risk stratification and help identify patients at highest risk of peripheral neuropathy when treated with vincristine therapy. 2.6 Conclusion This review highlights selected genetic variations related to vincristine pharmacokinetics (e.g., ABCB1, ABCC1, ABCC2, CYP3A4), vincristine pharmacodynamics (e.g., ACTG1, CAPG, CEP72, MAPT, SYNE2, TUBB3), and neuronal-related pathways (e.g., SLC5A7, COCH, TMEM215) found to be associated with vincristine-induced peripheral neuropathy risk in patients with pediatric cancers. These include variants in: ABCB1, ABCC1, ABCC2, CYP3A4, VDR, ACTG1, CAPG, CEP72, MAPT, SYNE2, TUBB3, SLC5A7, BAHD1, COCH, ETAA1, MRPL4, MTNR1B, NDUFAF6 and TMEM215 – All of which highlight the complexity of vincristine neuropathy susceptibility and the interplay of genetic, clinical, and demographic factors. To actualize the potential of pharmacogenomic testing, future research should prioritize standardized neuropathy assessment and pursue validation/replication in independent cohorts. When translating pharmacogenomic findings, identified genetic factors (e.g., genes involved in 54 vincristine pharmacokinetics/pharmacodynamics) should be carefully considered in conjunction with other factors that may impact neuropathy risk such as demographic (e.g., age and sex) and clinical (e.g., concomitantly administered medications) factors to better inform vincristine therapy. Ultimately, the goal should be to develop an individualized protocol based on a patients’ genotype, taking all risk and protective genes into account, and subsequently give patients a dose that limits the risk of vincristine peripheral neuropathy while maintaining highest possible therapeutic efficacy. Dose reductions or treatment withdrawal, or for some patients even standardized dose capping, would no longer be necessary. 55 Chapter 3: Genomic Variations Associated with Risk and Protection Against Vincristine-induced peripheral neuropathy in Pediatric Cancer Patients 3.1 Introduction Vincristine is one of the most widely used chemotherapeutic agents for the treatment of pediatric cancers, including leukemia, lymphoma, neuroblastoma, rhabdomyosarcoma, Wilm’s tumor and brain tumours. 72, 177, 178 Despite its high efficacy, up to 78% of patients receiving vincristine develop clinically significant vincristine-induced peripheral neuropathy. 81, 106, 179 The symptoms are characterized by progressive sensory, motor and autonomic nerve dysfunctions (e.g., paresthesia, impaired motor skills, loss of deep tendon reflexes, and altered gait). Such symptoms are one of the main reasons for interruption or discontinuation of vincristine treatment, which can lead to an overall loss of therapeutic efficacy, an increased relapse risk, and consequently affects patients’ survival and quality of life during and after cancer therapy. 74, 218 The risk of developing vincristine-induced peripheral neuropathy is influenced by several factors including patient-related and treatment-related factors. Age, sex and ancestry represent the three patient-related factors that are known to impact the risk of vincristine neuropathy, while treatment-related risk factors include vincristine cumulative dose and concomitant use of medications such as nifedipine, clarithromycin and anti-fungal azoles (e.g., fluconazole, ketoconazole, posaconazole, itraconazole, and voriconazole). 52, 116-118, 120, 219, 220 56 In addition, several genetic variations have been associated with the risk of vincristine-induced neuropathy (as discussed in Chapter 2). Since the first pharmacogenetic study of vincristine-induced neuropathy by Aplenc et al. demonstrating the role of genetic variants in CYP3A4 and CYP3A5 in 2003, 123 additional studies have implicated genetic variations in genes encoding components of vincristine pharmacokinetics: metabolism (e.g., CYP3A4, CYP3A5, and DPYD), 123, 124, 148 distribution (e.g., ABCC1, ABCC2), 148, 149 and elimination (e.g., ABCB1 and ABCC2); 149, 150 as well as vincristine pharmacodynamics: vincristine cellular targets (e.g., CEP72, CAPG, and MAPT) 150-152 and neuropathy-related pathways (e.g., SLC5A7, and TMEM215). 148 Currently available drug treatment of neuropathy results in modest improvements at best. 52 Nonetheless, emerging pharmacogenomic findings offer opportunities for further study of personalized or adaptive dosing strategies (e.g., treatment regimens with higher or lower dose intensity) and/or closer monitoring and proactive management (e.g., addition of pre-emptive physiotherapy in patients at high risk) to alleviate or prevent vincristine-induced peripheral neuropathy, which can adversely affect patients’ quality of life and longevity due to dose reduction or treatment omission despite the improved survival rate of cancers. 74, 218 This study aimed to investigate genomic risk factors of vincristine-induced peripheral neuropathy in a large cohort of pediatric patients with cancer using a genome-wide approach. 3.2 Methods 3.2.1 Patient Recruitment and Characterization A total of 2,043 patients who received vincristine chemotherapy were consecutively recruited and enrolled between 2005 and 2018 from ten pediatric academic health centres within the 57 Canadian Pharmacogenomics Network for Drug Safety (CPNDS) in Canada. This included sites in Vancouver (BC Children’s Hospital), Montreal (CHU Sainte-Justine Hospital), Toronto (The Hospital for Sick Children), Winnipeg (Children’s Hospital at the Health Sciences Centre), London (Children’s Hospital at London Health Sciences Centre), Ottawa (Children's Hospital of Eastern Ontario), Calgary (Alberta Children's Hospital), Halifax (IWK Children’s Hospital), Edmonton (Stollery Children's Hospital), and Saskatoon (Jim Pattison Children's Hospital). Written informed consent and/or assent were obtained from all patients or their parents/legal guardians/substitute decision-maker before enrolling in the study. The study was conducted in accordance with the Declaration of Helsinki and received ethical approval from the University of British Columbia Children's and Women's Research Ethics Board (reference number: H04-70358). The trial is publicly accessible through ClinicalTrials.gov under the registry name “National Active Surveillance Network and Pharmacogenomics of Adverse Drug Reactions in Children”, registration number NCT00414115, registered on December 21, 2006. Relevant clinical and demographic data were collected from medical charts and electronic medical records and were characterized for the entire cohort. These included data on patient age at cancer diagnosis, sex, cancer diagnosis, tumour risk and relapse, start/end date of vincristine treatment, chemotherapy protocol, date of first notation of neuropathy, vincristine total cumulative dose received and cumulative dose to the time of toxicity in cases (mg/m2), and concomitant medications used that potentially impact vincristine metabolism and elimination (i.e., nifedipine, clarithromycin, phenytoin). Concomitant treatment with anti-fungal azoles was also recorded, including treatment with fluconazole, itraconazole, ketoconazole, posaconazole or 58 voriconazole, which are strong CYP3A4 inhibitors and increase the risk of neuropathy when administered concomitantly with vincristine at therapeutic doses. 128 Vincristine-induced peripheral neuropathy was assessed and graded according to the CTCAE version 5.0. Vincristine neuropathy reactions were defined by neurological symptoms clinically characterized by numbness and paresthesia, loss of sensation/tendon reflexes, alterations of fine gait and motor skills, or uncontrolled pain and paralysis that may lead to death. Cases of vincristine-neuropathy (CTCAE grade ≥ 2, n=669) and controls (n=683) were matched by vincristine cumulative dose and genetic ancestry (top 4 principal components [PCs]) using propensity score matching (R package [MatchIt], data included: case/control status, treatment duration, vincristine dose, PC1, PC2, PC3, and PC4) to reduce case-control selection bias (Figure 3.1), 221 resulting in 550 cases matched with 550 controls. The CONSORT diagram provides detailed descriptions of all patients and exclusions (Figure 3.2). 59 Figure 3.1 Propensity score matching of cases and controls using vincristine cumulative dose and genetic ancestry. The matching was conducted based on vincristine cumulative dose and genetic ancestry (using the top four principal components) to reduce the heterogeneous vincristine exposure among cases and controls. Power calculations were performed prior to matching to ensure sufficient statistical power for downstream analyses. 60 Figure 3.2 CONSORT flow diagram of CPNDS-recruited pediatric patients with Vincristine-induced peripheral neuropathy. 61 3.2.2 Genotyping and Quality Control DNA extraction and genotyping were performed on the collected biological samples (blood or saliva). Genotype data were obtained through the Illumina Infinium® (Illumina, San Diego, CA, USA) Global Screening Array (GSA v2.0) with a custom multi-disease add-on panel. Using the 1000 Genomes Phase 3 samples as a reference, genotype phasing and imputation were conducted with SHAPEIT2 (v2.0) 222 and IMPUTE2 (v2.3.2) 223 to include variants that were not directly genotyped, and imputed single nucleotide polymorphisms (SNPs) with missingness >0.05, call threshold <0.9, and info score <0.5 were removed. A total of 488,268 directly genotyped SNPs remained after the quality control (QC) steps. 10,239,025 variants were analyzed following imputation, and 6,476,118 SNPs remained available for the genomic analysis after QC filtering. PLINK v1.9 was used for quality control filtering and variant calling through BC Platforms. 224 Initial quality control was completed through Genome Studio to remove failed assays identified by visual inspection of raw genotype data. At the sample level, individuals were screened for call rate (>95%) and genetic sex using PLINK v1.9 in BC Platforms. Samples with sex discrepancies that were not resolved by re-checking the patient chart, re-genotyping or re-collection were excluded. Identity-by-descent (IBD) check was performed using PLINK v1.9 in BC Platforms GWAS pipeline to identify relatedness between the samples. Highly genetically related samples (closer than cousins; PI cut-off ≥0.125) were checked for genetic quality, and the samples with the lowest call rate were removed. At the SNP level, further quality control was performed to filter SNPs based on variant missingness (<0.05), deviation from Hardy-Weinberg Equilibrium (HWE; Fisher's exact test p <1x10-6), and minor allele frequency (MAF) <0.01 using PLINK (v1.9). Genetic ancestry was calculated using principal component analysis (PCA) of patient 62 genotypes via the EIGENSTRAT method, in conjunction with genome-wide genotyping data from the 1000 Genomes Phase 3 reference population, after Genotype Harmonizer strand alignment. 225 PCA was conducted and visualized using RStudio and related packages (i.e., AssocTests, ggplot2, and plyr) and the top 4 principal components (Figure A1) were accounted for in the genome-wide analysis to control for any potential population stratification. 3.2.3 Statistical Analyses Analyses of the clinical and demographic characteristics were performed using R and related packages (i.e., plyr, reshape2, dplyr, broom, and finalfit) with Wilcoxon–Mann–Whitney test for testing continuous variables and Fisher exact test for categorical variables. Table 3.1 summarizes and reviews all the clinical and demographic characteristics analyzed in the current cohort (additional characteristics related to tumor types are listed in Table A2). I performed a matched case-control genome-wide analysis using an allelic genetic model (PLINK v1.9 in BC Platforms). The genome-wide significance level was established at p=5.0x10-8 for a priori power calculations for different allele frequencies and different odds ratios. Power to detect significant associations was calculated for minor allele frequencies (MAF) of 0.01-0.5 and ORs of 2.0-5.0. The assumptions were cohort size of 1,100 (1:1 case/control ratio), MAF between 0.01 to 0.05, ORs of 2, 2.5, 3, 3.5, 4, 4.5 or 5, and a significant p-value of 5.0x10-8 for the genome-wide analysis. I sought to identify potentially causal/driver variants by testing linkage disequilibrium (LD) between the top GWAS hits and previously identified SNPs within the 1000 Genomes reference cohort (considering all cohorts together [i.e., African, American, European, East Asian, and South Asian] and non-Finnish European alone) embedded in LDLink (https://ldlink.nci.nih.gov/).226 Additionally, I used the Genotype-Tissue Expression database 63 (GTEx consortium v8.0; embeded in FUMA: https://fuma.ctglab.nl/) to test the effects of the identified variants on gene expression. 227 To examine whether specific pathways are involved according to the GWAS results, pathway enrichment analysis (gene-set enrichment) was performed using the GWAS-nominated genes for cellular components, biological processes, and molecular functions through the publicly available online tool WebGestalt (http://www.webgestalt.org/).228 An enrichment score was computed to indicate the extent to which the genes identified through GWAS are overexpressed in various functional pathways. Statistical significance was determined using a permutation test (Fisher's exact test), and adjustment for multiple testing (number of pathways examined) was applied according to Bonferroni correction. 3.3 Results 3.3.1 Patient Characteristics The median age at diagnosis of the cases was 5.48 years (interquartile range [IQR]: 3.37-10.3), 50.5% (n=278) of whom were males. The median age for the controls was 4.95 years (IQR: 2.80-9.35), 51.8% (n=285) were males. Cases and controls received a median cumulative dose of 48 mg/m2 (IQR: 27.0-65.0) and 45 mg/m2 (IQR: 18.0-64.5), respectively. Table 3.1 summarizes the clinical and demographic characteristics of the current cohort, and Figure 3.2 (CONSORT diagram) provides a comprehensive overview of included patients. 64 Table 3.1 Clinical and demographic characteristics of the CPNDS pediatric patients. IQR=interquartile range; PC=principal component *:fluconazole, itraconazole, ketoconazole, posaconazole, and voriconazole. Patient characteristics Cases Neuropathy grade ≥ 2 (N=550) Controls No neuropathy (N=550) Overall (N=1100) p-value Sex Female (%) 272 (49.5%) 265 (48.2%) 537 (48.8%) 0.46 Male (%) 278 (50.5%) 285 (51.8%) 563 (51.2%) Age at diagnosis Years, median (IQR) 5.48 (3.37-10.3) 4.95 (2.80-9.35) 5.24 (3.06-9.92) 0.003 Vincristine total cumulative dose mg/m2, median (IQR) 48.0 (27.0-65.0) 45.0 (18.0-64.5) 47.0 (23.5-65.0) 0.11 Concomitant medications (%) Antifungal azoles* 68 (12.36%) 67 (12.2%) 135 (12.27%) 1.0 Clarithromycin 11 (2.0%) 42 (7.6%) 53 (4.81%) 0.0001 Nifedipine 50 (9.0%) 35 (6.4%) 85 (7.72%) 0.11 Phenytoin 8 (1.5%) 6 (1.1%) 14 (1.3%) 0.78 PC1 African from non-African, median (IQR) 0.00938 (0.00826 –0.00966) 0.00933 (0.00726 – 0.00967) 0.00936 (0.00778 – 0.00966) 0.32 PC2 East Asian from non-East Asian, median (IQR) 0.0118 (0.0106 – 0.0121) 0.0117 (0.00964-0.0121) 0.0117 (0.0101 – 0.0121) 0.10 PC3 Admixed American from non-Admixed American, median (IQR) 0.00483 (0.00407 – 0.00559) 0.00483 (0.00409-0.00576) 0.00483 (0.00408 – 0.00565) 0.11 PC4 South Asian from non-South Asian, median (IQR) -0.00459 (-0.00577 – -0.00240) -0.00456 (-0.00591--0.00253) -0.00458 (-0.00586 – -0.00248) 0.61 65 3.3.2 Cohort Exclusions Exclusions were made based on clinical criteria to ensure high quality and homogeneity of the cohort. These include samples exhibiting discrepancies in sex assignment (n=3) or displaying high genetic relatedness beyond first-degree relatives (n=7) after medical chart confirmation of sex or repeat genotyping failed to resolve discrepancies. Individuals whose DNA samples were collected post-bone marrow transplant (n=24) were excluded due to potential alterations in genetic background post-transplantation. Patients with mild neuropathy (CTCAE grade 1; n=155) were excluded because these cases are mildly affected and do not require medical intervention and may not progress to a more severe grade. All cases underwent expert review to ensure accurate classification according to CTCAE criteria, with those that were ambiguous excluded (n=59). Additional exclusions included non-pediatric patients (age at cancer diagnosis >18 years old; n=8), those lacking clinical charts with data on vincristine dosing or details about potential neuropathy (n=19), patients who did not receive vincristine (n=2), and duplicate entries (n=8). Cases where neuropathy reaction was unclear if due to vincristine (n=59), patients with pre-existing neurological conditions prior to vincristine administration (n=27), and cases with unclear vincristine dosing/timing in relation to neuropathy onset (n=23) were also excluded. 3.3.3 Multivariable Analysis and Confounding Variables The multivariable analysis accounted for key confounding variables, specifically the genetic ancestry and vincristine cumulative dose. Of the other variables analyzed, age and concomitant clarithromycin use were statistically significantly different between the case and control groups. 66 Concomitant clarithromycin was more frequently given in controls (7.6%) than in cases (2.0%), and the median age at diagnosis was higher in cases (5.48 years, IQR: 3.37-10.3) than in controls (4.95 years, IQR: 2.80-9.35). Given clarithromycin's effect as a potent CYP450 3A4 inhibitor, increasing vincristine plasma concentrations, the more frequent use in controls suggests it is unlikely to impact vincristine peripheral neuropathy risk. Table A3 details the timing and overlap of concomitant medications with neuropathy onset. The observed age difference (6 months and 10 days) between cases and controls is also unlikely to be clinically significant in terms of substantially increasing vincristine neuropathy risk. Additionally, sensitivity analysis accounting for potential confounding by age confirmed that the results remained consistent (Table A4), providing further assurance of validity of the findings. The multivariate analysis therefore focused on clinically relevant confounding variables: vincristine exposure (cumulative dose) and genetic ancestry (top 4 principal components). 3.3.4 Time to Neuropathy I investigated the time to first documentation of vincristine-induced peripheral neuropathy (CTCAE grade ≥2) in the 550 cases to understand the timing of vincristine neuropathy in relation to vincristine treatment. To calculate treatment duration to the first neuropathy reaction, I used the date of first dose of vincristine and the date neuropathy was first documented in the medical record. Three-hundred and thirty-one cases (60.18%) reported symptoms of peripheral neuropathy (CTCAE grade ≥2) within the first month of chemotherapy, while 525 (95.45%) had developed neuropathy symptoms by 14 months and 550 (100%) by 55 months (illustrated in Figure 3.3). Controls were followed up for an average duration of 12.5 years (standard deviation 67 [SD] ±5.93), confirming the absence of vincristine-induced neuropathy symptoms, having received on average 28 doses of vincristine (SD ±17). Figure 3.3 Cumulative incidence of vincristine-induced peripheral neuropathy cases over time. Cumulative incidence of cases (n=550) who developed vincristine-induced peripheral neuropathy (CTCAE grade ≥2) over time, indicating that 95% of the cases declared neuropathy symptoms within the first 14 months after the start of vincristine therapy (red dashed line). 68 3.3.5 Genome-Wide Analysis To identify genetic risk loci associated with the risk of vincristine-induced neuropathy (CTCAE grade ≥2), I performed a genome-wide analysis of vincristine-induced peripheral neuropathy cases and controls matched by vincristine dose and genetic ancestry (top 4 PCs, allelic model). The GWAS identified 13 significant associations (p<5.0x10-8), including variants within or near the genes SPDYA, METLL8, PDE4D, FBN2, ZFAND3, NFIB, PAPPA, LRRTM3, VTI1A, NRG3, ARHGAP5, ACTN1 and MCM3AP (Figure 3.4). Individual LocusZoom plots can be found in Figure A2. Of the 13 statistically significant GWAS loci, only one SNP was positively associated with the occurrence of vincristine-induced neuropathy, and the other 12 were all negatively associated (i.e., protective). SNP (rs1815857) in MCM3AP increased the risk of vincristine-induced neuropathy by more than 6-fold (OR=6.25, 95% CI: 2.91-12.11, p=3.13x10-8) while 12 other SNPs showed a protective effect against neuropathy risk. (Table 3.2). FBN2 rs12656510 is found in LD with a missense variant rs32209 (c.6931A>G; p.Met2311Val) in the same gene (R2=0.72, D'=0.85) with a combined annotation depletion dependent (CADD) score of 21.2 (top 1% of deleterious variants in the genome), and MCM3AP rs1815857 is in LD (R2=0.90, D'=0.96) with an intronic variant rs17177067 within the same gene (CADD=11.2; top 10% of pathogenic variants across the genome). In addition, 9 of the 13 identified genes are widely expressed across the nervous system, including 4 genes (NFIB, ACTN1, ZFAND3, and MCM3AP) that are very highly expressed in the tibial nerve (Figure A3). 69 Figure 3.4 Manhattan plot of the vincristine-induced peripheral neuropathy GWAS summary statistics. Manhattan plot highlighting the GWAS-nominated loci associated with the risk of vincristine-induced neuropathy. Each point represents the log p-value at each genomic position from Chromosome 1 to Chromosome 22. The genome-wide significance threshold was set at 5x10-8 (black dashed line). 70 Variant Chr Position (GRCh37/hg19) Annotation Nearest Gene(s) EA EAF cases EAF controls Global EAF (GnomAD v3.1.2) Odds Ratio (95% CI) p-value rs12474420 2 29068092 intronic SPDYA T 1.6% 6.2% 2.6% 0.25 (0.14-0.43) 4.40x10-8 rs79802223 2 172161437 intergenic METTL8 G 0.9% 5.0% 2.5% 0.17 (0.09-0.35) 2.46x10-8 rs12658429 5 58532218 intronic PDE4D C 1.5% 6.1% 3.0% 0.24 (0.14-0.42) 4.14x10-8 rs12656510 5 127751056 intronic FBN2 T 3.8% 9.7% 6.7% 0.36 (0.25-0.53) 4.06x10-8 rs200858088 6 37981515 5’UTR ZFAND3 C 0.3% 4.5% 1.6% 0.07 (0.02-0.21) 2.53x10-10 rs10961381 9 14117145 intronic NFIB G 0.2% 3.6% 1.1% 0.07 (0.02-0.24) 2.50x10-8 rs12235805 9 118440926 intergenic PAPPA A 1.2% 5.5% 2.9% 0.20 (0.11-0.30) 3.04x10-8 rs10997459 10 68730118 intronic LRRTM3 G 0.6% 4.2% 2.5% 0.14 (0.06-0.32) 4.84x10-8 rs12253008 10 84153036 intronic NRG3 T 0.7% 4.5% 3.2% 0.15 (0.07-0.33) 3.19x10-8 rs17129858 10 114313869 intronic VTI1A T 2.2% 7.7% 3.6% 0.27 (0.17-0.43) 4.10x10-9 rs8006511 14 32449334 intergenic ARHGAP5 G 33.5% 45.3% 42.5% 0.60 (0.51-0.72) 2.90x10-8 rs2268979 14 69415962 intronic ACTN1 T 8.3% 16.2% 10.4% 0.46 (0.35-0.61) 2.19x10-8 rs1815857 21 47700847 intronic MCM3AP T 99.1% 95.1% 97.4% 6.25 (2.91- 12.11) 3.13x10-8 Table 3.2 SNPs associated with vincristine-induced peripheral neuropathy. Summary of the top independent SNPs associated with vincristine peripheral neuropathy risk. Abbreviations: Chr=chromosome; GRCh37=genome reference consortium human build 37; EA=effect allele; EAF=effect allele frequency; GnomAD=the genome aggregation database; CI=confidence interval. 71 3.3.6 Pathway Analysis The nominated cellular components include glutamatergic synapse (p=0.0004), synapse (p=0.001), and voltage-gated calcium channel complex (p=0.02). Biological processes include sensory nerve development (p=0.001), cell communication by electrical coupling (p=0.02) and regulation of cellular component movement by cytoskeleton (p=0.02), and molecular functions include protein kinase activator activity (p=0.001), ion channel binding (p=0.002) and structural constituent of post-synapse (p=0.005) (Figure 3.5a and Table 3.3). All p-values were Bonferroni corrected for multiple testing (number of tested pathways). 72 Figure 3.5 Vincristine neuropathy pathways associated with genes nominated by GWAS. a) Vincristine-induced peripheral neuropathy GWAS pathways nominated by gene-set enrichment analysis using WebGestalt (http://www.webgestalt.org/) in cellular components, biological processes, and molecular functions. 85 The bars represent the Bonferroni corrected p-values, and the red dashed line indicates significance threshold of p=0.05. b) Key GWAS-significant loci across different pathophysiology, where a significant overlap is observed between the gene-sets involved in different pathways, suggesting that an interaction between these pathways contributes to the overall risk of vincristine peripheral neuropathy. 73 Gene-Set Pathway description p-value* Enrichment ratio Pathway type GO:0098978 glutamatergic synapse 0.00040589 18.850 cell composition GO:0045202 synapse 0.0010410 7.6226 cell composition GO:0001527 microfibril 0.0045391 219.91 cell composition GO:0005891 voltage-gated calcium channel complex 0.019391 51.142 cell composition GO:0031201 SNARE complex 0.036715 26.806 cell composition GO:0021740 principal sensory nucleus of trigeminal nerve development 0.0013197 757.55 biological processes GO:0060689 cell differentiation 0.0019789 505.03 biological processes GO:0051271 negative regulation of cellular component movement 0.020064 8.9453 biological processes GO:0010644 cell communication by electrical coupling 0.020610 48.081 biological processes GO:0032147 activation of protein kinase activity 0.022639 8.3880 biological processes GO:0030900 forebrain development 0.030242 7.1801 biological processes GO:0030295 protein kinase activator activity 0.0011566 38.860 molecular functions GO:0044325 ion channel binding 0.0028432 24.643 molecular functions GO:0030297 transmembrane receptor protein tyrosine kinase activator activity 0.0046105 216.51 molecular functions GO:0099186 structural constituent of post-synapse 0.0059242 168.39 molecular functions Table 3.3 Summary of the vincristine-induced peripheral neuropathy GWAS-nominated pathway analysis gene-sets. *Bonferroni corrected p-values. 74 3.4 Discussion In this largest genome-wide analysis of vincristine-induced peripheral neuropathy, I identified 13 significant vincristine peripheral neuropathy-associated loci, including 12 variants that strongly protect against peripheral neuropathy by 40-93% and one variant that increases the odds of developing peripheral neuropathy by 6-fold (Table 3.2). The pathway analysis showed specificity for the involvement of four key pathways: nerve structure and development (genes involved: ACTN1, LRRTM3, NRG3, VTI1A, NFIB, FBN2, and MCM3AP), nerve myelination (MCM3AP and ZFAND3), neuronal transmission (PDE4D, ACTN1, NRG3, VTI1A, SPDYA, and MCM3AP), and cytoskeleton/microfibril function (ACTN1, NRG3, FBN2, and ARHGAP5) pathways; all are required for the stability and normal function of the peripheral nervous system. Notably, the identified genetic variations within all the identified genes, except for MCM3AP, exhibit a protective effect against the development and progression of neuropathy, potentially modulating biological processes that contribute to the overall integrity of nerve structure and function. The identified vincristine peripheral neuropathy genes involved in nerve structure pathway (ACTN1, LRRTM3, NRG3, VTI1A, NFIB and FBN2) are known to play critical roles in the development and maintenance of neuronal networks. Specifically, ACTN1, LRRTM3, and NRG3 are implicated in synapse formation and synaptic plasticity, 229-234 suggesting their involvement in regulating neuronal connectivity and communication. VTI1A is primarily associated with trans-Golgi network in the neuron body and is known to play a key role in neuronal development. 235, 236 NFIB is a transcription factor that regulates neurogenesis of the pontine neurons, 237-239 which manage sensory and pain signals. 240 Haploinsufficiency of NFIB in 75 humans is found to result in neurodevelopmental deficits and neuronal malformations. 241 FBN2 is a key component of the extracellular matrix of peripheral nerve, 242 and rare pathogenic missense variants (c.5009T>G; p.Phe1670Cys) in FBN2 were found to cause early-onset peripheral neuropathy. 243 Variants in all these genes confer significant protection against neuropathy, reducing the risk by 54-93%. In addition, genes identified in the nerve myelination pathway involve ZFAND3 and MCM3AP. MCM3AP encodes for germinal center associated nuclear protein (GANP), which is a major regulator of gene expression in developing motor neurons. 244 MCM3AP biallelic variants that affect protein function cause nerve demyelination and autosomal recessive forms of childhood-onset peripheral neuropathy (Charcot-Marie-Tooth disease; CMT). 245-247 While MCM3AP-related neuropathy is primarily axonal and predominantly motor, sensory impairments such as altered pain or reduced sensory nerve action potentials are also present in some affected individuals. 248 ZFAND3 plays a role in preventing CMT potentially through its role in facilitating the degradation and clearance of aberrant stress granules (SGs) that are responsible for increasing stress vulnerability of peripheral motor nerves. 249, 250 Such aberrant SGs are implicated with CMT risk and their disruption was found to alleviate motor weaknesses in CMT mice. 251 ZFAND3 has also been identified through previous GWAS studies to be associated (OR=1.51; CI 95%: 0.54-4.22) with an increased risk of Type 2 Diabetes (T2D) neuropathy, 252, 253 and variants in ZFAND3 T2D locus (rs58692659 and rs9470794) discovered in patients of East Asian ancestry are in high LD with the top SNP in the current GWAS (rs200858088; R2=0.952, D'=0.975, and R2=0.985, D'=1.0, respectively). The identified variant in ZFAND3 (rs200858088) decreased vincristine neuropathy reaction risk by 93% (OR=0.07; CI 95%: 0.02- 76 0.21) while MCM3AP rs1815857 increased the risk of peripheral neuropathy (OR=6.25; CI 95%: 2.91-12.11). Vincristine peripheral neuropathy-related genes involved in neuronal transmission pathway were PDE4D, ACTN1, NRG3, LRRTM3 and VTI1A, which are notably linked with various aspects of neuronal signaling and synaptic transmission. PDE4D is an enzyme that modulates cyclic adenosine monophosphate (cAMP) levels in neurons, 254, 255 and it plays a role in intracellular cascades involved in post-synaptic signaling. 256 Inhibition of PDE4 has shown promising results in reversing neuropathic pain in mice, 257 and is considered as therapeutic target for improving neurological symptoms of neurodegenerative disorders such as Parkinson’s disease and Huntington disease. 258 ACTN1 regulates post-synaptic growth and neuronal plasticity through its interaction and activation of calcium/calmodulin-dependent protein kinase II (CaMKII). 232-234 NRG3 and LRRTM3 promote excitatory synapse formation and synaptic plasticity of the peripheral nerves through their regulation of ErbB signaling and neurexin binding, respectively. 229-231, 259 NRG3 is a paralog of NRG1, which reduces pain hypersensitivity and inhibits neuropathic pain, 260, 261 and ablation of NRG3 results in reduced excitatory synapse numbers on GABAergic interneurons (involved in mediating pain), altered short-term plasticity and disinhibition of the hippocampal network. 262 VTI1A has been implicated in synaptic vesicle trafficking and neurotransmitter release, and its absence leads to impairments in neuronal development and communication. 235, 236, 263 The presence of protective variants in these genes may influence crucial processes such as synaptic vesicle trafficking, neurotransmitter release, and synaptic membrane dynamics, ultimately contributing to efficient neuronal transmission. 77 In addition to the previously discussed pathways, defects in cytoskeleton and microfibril architectures have also been implicated in peripheral neuropathies. 264, 265 This study identified ACTN1, NRG3, FBN2, and ARHGAP5 that are involved in maintaining cytoskeletal integrity and regulating cellular processes related to microfibril function. Such processes are essential for ensuring neuronal morphology and stability and axonal transport.27 FBN2 encodes for microfibril, 242 while ACTN1, NRG3, and ARHGAP5 are associated with actin cytoskeleton organization and dynamics. 266-268 ACTN1 encodes for alpha-actinin and plays a critical role in axonal growth and guidance. 269 ARHGAP5 is involved in the regulation of Rho GTPases, which are key regulators of cytoskeletal remodeling and cellular motility processes within the peripheral nervous system. 268 Variations within these genes have shown a 40-86% protection against peripheral neuropathy risk, which suggests their contribution in maintaining neuronal structural stability and cellular motility, and thereby decreasing the sensitivity of the peripheral nervous system to vincristine-neurotoxicity. Of note, a significant overlap exists in the contributing genes within each pathophysiology (Figure 3.5b), suggesting a potential interplay between these pathways underlies protection against susceptibility of vincristine-induced peripheral neuropathy. Based on these results, I hypothesize that vincristine neuropathy risk is influenced by a complex interaction involving multiple neuropathy-related pathophysiology mechanisms (Figure 3.6). 78 Figure 3.6 Vincristine-induced peripheral neuropathy-related pathophysiology. Schematic overview of the key GWAS-significant loci across different vincristine peripheral neuropathy-related pathophysiology; a) VTI1A regulates neuronal development, Golgi secretion, and extracellular transport of neurons86, 87; NRG3 plays a role in intracellular signal transduction and nervous system development88; Actin provides structural support for neurons and regulates neuronal shape89; b) MCM3AP is implicated in axonal and demyelinating CMT neuropathy39, 40; ZFAND proteins regulate the clearance of aberrant stress granules (SGs) via the ubiquitin/proteasome system preventing stress vulnerability in motoneurons and CMT caused by aberrant-SGs 43, 45, 90, 91; Neuregulin interacts with ErbB to promote myelination of peripheral axons and motor axon maturation92, 93, 94, 95, 96; c) Actin filaments regulate axon growth, guidance and active axonal transport89, 97; ARHGAP5 mediates cytoskeleton changes and promote actin polymerization through regulating Rho GTPases62; FBN2 provides mechanical and functional support to peripheral nerves and is implicated in early-onset neuropathies37, 98, 99, 100, 101; d) VTI1A regulates the fusion of synaptic vesicles with the presynaptic membrane via interacting with t-SNAREs complex proteins57, 86, 102; Actinin regulates neurotransmitter release from presynaptic terminals and modulates synaptic plasticity via activating CaMKII in post-synapse neurons97, 103, 104, 105; NRG3 promotes excitatory synapse formation and plasticity, and modulates synaptic transmission through activating ErbB424, 25, 88; LRRTM3 induces synapse development and differentiation through interacting with pre-synapse neurexins. 23, 106, 107, 108 Figure was created with BioRender.com and Adobe Illustrator® Creative Cloud. 79 Several trials sought to determine whether medications such as amitriptyline, Org 2766, gabapentin, vitamin B6 and glutamine can be used to treat or prevent vincristine-induced peripheral neuropathy. 153, 154, 156-159, 162-164 Out of these, only gabapentin has been found to improve neuropathy symptoms in pediatric patients. 159, 163 However, these trials suffered from limitations such as small sample, insufficient power, a high drop-out rate, and inconsistencies in primary outcomes, limiting comparability of results. In addition, these trials were performed in a variety of treatment settings with various chemotherapy regimens, including different combinations of other neurotoxic medications (e.g., vinblastine, platinum derivatives, taxanes), making the interpretation and extrapolation of the results a major challenge. As a result, despite the widespread interest and numerous clinical trials aiming to treat peripheral neuropathy, no clear standard has been determined or can be recommended at the current time. These findings present potential actionable genomic markers, encompassing variants in multiple genes associated with significant alterations in vincristine peripheral neuropathy risk, including MCM3AP (rs1815857) with a 6-fold increased risk, and protective variants such as FBN2 (rs12656510), ZFAND3 (rs200858088), SPDYA (rs12474420), METLL8 (rs79802223), PDE4D (rs12658429), NFIB (rs10961381), PAPPA (rs12235805), LRRTM3 (rs10997459), VTI1A (rs17129858), NRG3 (rs12253008), ARHGAP5 (rs8006511), and ACTN1 (rs2268979). These genomic markers can be potentially leveraged to identify patients’ risk of developing peripheral neuropathy prior to treatment start and tailor therapeutic strategies (i.e., vincristine doses) accordingly. Specifically, patients carrying the high-risk variant in MCM3AP (rs1815857) may warrant closer monitoring and proactive management (i.e., addition of pre-emptive physiotherapy) to mitigate the increased risk. Conversely, individuals with protective variants, 80 such as those identified in NRG3 (rs12253008) and ACTN1 (rs2268979) – most overlapping genes in the pathophysiology of neuropathy, may derive benefit from tolerating standard-dose vincristine regimens, preserving the efficacy of their chemotherapy treatment. Of note, while the current GWAS study identified 13 genetic variants strongly associated with vincristine-induced peripheral neuropathy risk (Table 3.2), the analysis did not replicate previously identified variants, namely the promoter variation (rs924607) in the centrosomal Protein 72 (CEP72) gene, which was first identified by Diouf et al. 2015, where an association was observed in cases of neuropathy grade 2–4 during the continuation phase of chemotherapy treatment. 151 This significant association was evident only in patients after prolonged vincristine treatment (20–40 doses over 1–2 years) and was not replicated by the same research group (Diouf et al 2016) and other studies when investigated neuropathy risk during the induction phase. 192, 270 This suggests the effect of CEP72 is particularly relevant to longer-term therapy. In the current study, time-to-neuropathy analysis showed that 60.2% of vincristine-induced neuropathy cases reported symptoms early (i.e., within the first month of chemotherapy), and 90% developed neuropathy prior the completion of seven months of cancer treatment. This difference in neuropathy onset can explain the non-significant association of CEP72 rs924607 observed in our study and suggests potential etiological differences in neuropathy between induction and continuation phases of treatment. The lack of replication of previously identified genetic markers highlights the complexity of vincristine-induced neuropathy and underscores the critical importance of defining the phenotypes rigorously in genomic studies when moving forward with results validation. 81 While these findings may provide valuable insights into the genomic associations with vincristine-induced peripheral neuropathy risk, the identified genetic variants in this study should be validated in an independent cohort of children to establish the generalizability and robustness of the findings. Given the rarity of pediatric cancer, securing a sufficiently large independent cohort for replication is challenging. However, validation of the current findings is a critical next step in this work and is now being planned. Functional studies using cellular (e.g., neurons derived from human-induced pluripotent stem cells) or animal (e.g., mice, zebrafish, Caenorhabditis elegans) models are likely to be useful for better understanding the mechanism by which the identified variants are involved in the pathophysiology of vincristine neuropathy. Validation of these findings will be a critical step forward in our efforts to mitigating the burden incurred by this severe reaction on children battling cancer, their families, and caregivers. 82 Chapter 4: Validation of Genome-Wide Association Analysis Results 4.1 Introduction Vincristine-induced peripheral neuropathy is a common and highly debilitating toxicity from vincristine chemotherapy, often leading to dose reductions or treatment discontinuation, which may impact patients quality of life and overall survival. 74, 218 The risk of vincristine peripheral neuropathy is influenced by several factors, including clinical (e.g., vincristine cumulative dose, concomitant medications, dose intensity), demographic (e.g., biological sex, age at cancer diagnosis, ancestry) and genetic factors. 52 The increasing evidence highlighting the role of genetic variation as a key contributor in vincristine neuropathy susceptibility emphasizes the importance of pharmacogenomic studies in this field. I previously conducted a large GWAS study involving 1,100 pediatric cancer patients matched for vincristine cumulative dose and genetic ancestry. 271 In this study, I identified 13 genomic variants significantly associated with risk and protection of vincristine-induced peripheral neuropathy. Among these, one variant (rs1815857) in the MCM3AP gene, was associated with an increased risk of neuropathy, and 12 protective variants were identified in the genes SPDYA (rs12474420), METTL8 (rs79802223), PDE4D (rs12658429), FBN2 (rs12656510), ZFAND3 (rs200858088), NFIB (rs10961381), PAPPA (rs12235805), LRRTM3 (rs10997459), NRG3 (rs12253008), VTI1A (rs17129858), ARHGAP5 (rs8006511) and ACTN1 (rs2268979). These findings highlighted the genetic complexity of peripheral neuropathy and provided insights into potential mechanisms underlying both susceptibility and protection. 83 Because of these promising findings, replication in an independent cohort is required to validate the associations and ensure their generalizability and robustness. Replication is considered the gold standard in scientific discovery272 as it helps ensure that the observed genotype-phenotype associations in GWAS are not artifacts resulting from chance findings, population stratification, or other uncontrolled biases. Therefore, in this study, I sought to validate the 13 previously identified genetic variants in an independent cohort of pediatric cancer patients treated with vincristine. 4.2 Methods 4.2.1 Patients and Clinical Assessment A total of 525 patients with childhood cancers (age at diagnosis ≤18 years) who received vincristine as part of their chemotherapy were recruited from ten pediatric hospitals across Canada, including sites in Vancouver, Montreal, Toronto, Winnipeg, London, Ottawa, Calgary, Halifax, Edmonton and Saskatoon. Of note, this cohort, termed “replication cohort”, is completely independent from the previously published discovery cohort (Chapter 3). The patients in this cohort were more recently characterized and graded, and there were no shared individuals or genetic relationships between individuals from the two cohorts, as determined by identity-by-descent analysis (i.e., closer than cousins; the PI cut-off ≥0.125). This independence was needed to ensure that the results of the replication cohort are not influenced by overlapping genetic factors with the discovery cohort. Prior to participation, written informed consent and/or assent was obtained from all replication cohort participants or their parents/legal guardians. Patients’ biological samples (blood/saliva) 84 were collected and relevant clinical and demographic data were systematically obtained using the CPNDS active surveillance methodology. 273 Data included patients age, biological sex, cancer diagnosis, vincristine dose, treatment protocol and duration, the date of first declaration of vincristine neuropathy symptoms and concomitantly administered medications. Vincristine-induced peripheral neuropathy was assessed according to the CTCAE v5.0 criteria, with neuropathy defined by symptoms as mild numbness and paresthesia, loss of sensation/tendon reflexes, alterations of fine gait and motor skills, or uncontrolled pain and paralysis, which in severe cases could potentially lead to death. Similar to the discovery cohort, cases (CTCAE grade ≥ 2) and controls in the replication cohort were matched by vincristine dose and genetic ancestry (represented by the top 4 PCs). Matching was performed using propensity score matching through the R package [MatchIt], which included case/control status, treatment duration, vincristine dose, and PCs 1–4 as covariates, resulting in 181 cases matched with 181 controls. The CONSORT diagram (Figure 4.1) provides a comprehensive overview of the study population, detailing patient characteristics and exclusions in the replication cohort. 85 Figure 4.1 CONSORT flow diagram of CPNDS-recruited pediatric patients with vincristine-induced peripheral neuropathy. 86 4.2.2 Statistical and Genetic Analyses Statistical analyses of clinical and demographic characteristics in the replication were cohort performed using Rstudio and related packages (i.e., plyr, reshape2, dplyr, broom) with the Wilcoxon–Mann–Whitney test for testing continuous variables and Chi-square test (Fisher exact test when cell count less than 5) for categorical variables. Table 4.1 summarizes and reviews all the clinical and demographic characteristics analyzed in the current cohort (additional characteristics related to tumor types are listed in Table A5). To replicate and interpret the genetic associations identified in the discovery GWAS, I performed a matched case-control analysis using PLINK v1.9 in BC Platforms. 224 This analysis focused on the 13 genetic variants that surpassed the genome-wide significance threshold (p<5.0x10-8) in the discovery cohort. To correct for multiple testing (n=13), a significance threshold of p<0.0038 was set for the replication analysis. Additionally, I performed a meta-analysis to combine the results from the discovery and replication cohorts. This analysis employed the inverse variance-weighted fixed-effect model using the software METAL, integrated within the BC Platforms (https://genome.sph.umich.edu/wiki/METAL_Documentation).274 The meta-analysis allowed for a direct comparison of effect sizes, directionality of the effects, and statistical significance for the tested variants across the discovery and replication cohorts. 87 4.3 Results 4.3.1 Patient Characteristics The patient demographic and clinical characteristics of the study participants are summarized in Table 1.4. After matching cases and controls based on vincristine dose and genetic ancestry, no statistically significant differences were observed between the two groups. Cases were more often male compared to controls, though the difference was not statistically significant. The median age at diagnosis was similar between cases and controls, with cases having a median age of 5.56 years and controls 4.86 years. Additionally, no significant differences were observed in the use of concomitant medications, including antifungal azoles, clarithromycin, nifedipine, and phenytoin (Table 4.1). Among the cases, the majority (77.4%) were classified as CTCAE grade 2 (n=140), while the remaining cases (22.6%) were classified as by grade 3 neuropathy, both of which are within the range previously reported in the literature. 106 There were no neuropathy cases with grades 4 or 5. Patients were predominantly of European genetic ancestry (63.81%), followed by American (11.32%), South Asian (9.95%) and East Asian (6.63%) (Table A5). 88 Table 4.1 Clinical and demographic characteristics of the replication cohort of CPNDS. IQR=interquartile range; PC=principal component; *:fluconazole, itraconazole, ketoconazole, posaconazole, and voriconazole.Patient characteristics Cases Neuropathy grade ≥ 2 (N=181) Controls No neuropathy (N=181) Overall (N=362) p-value Sex Female (%) 65 (35.9%) 82 (45.3%) 147 (40.6%) 0.09 Male (%) 116 (64.1%) 99 (54.7%) 215 (59.4%) Age at diagnosis Years, median (IQR) 5.56 (3.24-9.96) 4.86 (2.65-11.2) 5.39 (3.00-10.6) 0.78 Vincristine cumulative dose mg/m2, median (IQR) 8.00 (3.00-14.0) 7.00 (5.00-14.4) 7.50 ( 4.50-14.3) 0.33 Concomitant medications (%) Antifungal azoles* 18 (9.94%) 18 (9.94%) 36 (9.94%) 1.0 Clarithromycin 5 (2.76%) 1 (3.31%) 6 (1.65%) 0.21 Nifedipine 15 (8.29%) 8 (7.73%) 23 (6.35%) 0.19 Phenytoin 0 (0.0%) 0 (0.0%) 0 (0.0%) 1.0 PC1 African from non-African, median (IQR) 0.00705 (0.00652 – 0.00736) 0.00711 (0.00662 – 0.00775) 0.00709 (0.00652 – 0.00750) 0.07 PC2 East Asian from non-East Asian, median (IQR) -0.0131 (-0.0135 – -0.00803) -0.0130 (-0.0136 – -0.00285) -0.0130 (-0.0136 – -0.00475) 0.11 PC3 Admixed American from non-Admixed American, median (IQR) -0.00548 (-0.00625 – -0.00378) -0.00534 (-0.00653 – -0.00428) -0.00544 (-0.00629 – -0.00398) 0.37 PC4 South Asian from non-South Asian, median (IQR) -0.00456 (-0.00604 – -0.00134) -0.00405 (-0.00619 – 0.000542) -0.00433 (-0.00611 – -0.000172) 0.39 89 4.3.2 Replication of Genetic Associations with Vincristine Peripheral Neuropathy Of the 13 variants evaluated, two genetic variants identified as significantly associated with vincristine-induced peripheral neuropathy in the discovery cohort were replicated in the independent replication cohort (Bonferroni corrected p-value < 0.0038) (Table 4.2). These included the variants rs17129858 in (VTI1A, OR: 0.29, 95% CI: 0.14–0.61) and rs2268979 in (ACTN1, OR: 0.51, 95% CI: 0.32–0.81). Notably, the directionality of these associations was consistent with that observed in the discovery cohort. In a meta-analysis of the original discovery cohort and the current replication cohort, 11 variants remained genome-wide significant (p<5.0x10-8). The variants rs200858088 in ZFAND3 and rs17129858 in VTI1A were among the most strongly associated loci, with meta-analysis p-values of 1.59×10⁻¹¹ and 1.03×10⁻¹¹, respectively. Other replicated variants, such as rs8006511 in ARHGAP5 (meta p=1.77×10⁻⁹) and rs2268979 in ACTN1 (meta p=3.12×10⁻¹⁰), exhibited highly consistent protection from neuropathy (Table 4.2). Overall, the consistency of effect sizes and the highly significant meta-analysis p-values highlight the potential biological relevance of these variants and their utility in understanding the genetic architecture of vincristine-induced neuropathy risk. 90 Table 4.2. Variants associated with vincristine-induced neuropathy risk in discovery and independent replication cohorts. Abbreviations: Chr=Chromosome; EA=Effect allele; OR=Odds ratio; CI= Confidence interval; significant p-values are highlighted in bold. *Statistical significance was set at p-value<0.0038 for independent replication cohort analysis after adjusting for multiple variants testing (n=13). Variant Chr Gene EA Discovery cohort (GWAS) n=1100 (Mufti et al 2024) 271 Replication cohort (validation analysis) n=362 Meta analysis EA% Cases Controls OR (95% CI) p-value EA% Cases Controls OR (95% CI) p-value* p-value rs12474420 2 SPDYA T 1.6% 6.2% 0.25 (0.14-0.43) 4.40x10-8 2.7% 6.4% 0.40 (0.17-0.93) 0.029 5.46x10-9 rs79802223 2 METTL8 G 0.9% 5.0% 0.17 (0.09-0.35) 2.46x10-8 2.7% 5.1% 0.52 (0.21-1.25) 0.140 2.55 x10-8 rs12658429 5 PDE4D C 1.5% 6.1% 0.24 (0.14-0.42) 4.14x10-8 6.8% 9.0% 0.74 (0.40-1.37 0.343 1.7x10-7 rs12656510 5 FBN2 T 3.8% 9.7% 0.36 (0.25-0.53) 4.06x10-8 6.8% 13.9% 0.45 (0.26-0.80) 0.005 7.94x10-10 rs200858088 6 ZFAND3 C 0.3% 4.5% 0.07 (0.02-0.21) 2.53x10-10 2.0% 6.1% 0.31 (0.12-0.81) 0.011 1.59x10-11 rs10961381 9 NFIB G 0.2% 3.6% 0.07 (0.02-0.24) 2.50x10-8 1.3% 2.3% 0.57 (0.16-1.98) 0.373 1.31x10-7 rs12235805 9 PAPPA A 1.2% 5.5% 0.20 (0.30-0.11) 3.04x10-8 3.7% 7.7% 0.64 (0.46-0.89) 0.041 5.91 x10-9 rs10997459 10 LRRTM3 G 0.6% 4.2% 0.14 (0.06-0.32) 4.84x10-8 1.0% 3.6% 0.26 (0.07-0.96) 0.031 6.48 x10-9 rs12253008 10 NRG3 T 0.7% 4.5% 0.15 (0.07-0.33) 3.19x10-8 1.6% 5.6% 0.28 (0.10-0.77) 0.009 1.10 x10-9 rs17129858 10 VTI1A T 2.2% 7.7% 0.27 (0.17-0.43) 4.10x10-9 3.3% 10.4% 0.29 (0.14-0.61) 0.0006 1.03x10-11 rs8006511 14 ARHGAP5 G 33.5% 45.3% 0.60 (0.51-0.72) 2.90x10-8 38.9% 49.4% 0.65 (0.32-0.81) 0.005 1.77x10-9 rs2268979 14 ACTN1 T 8.3% 16.2% 0.46 (0.35-0.61) 2.19x10-8 11.6% 20.4% 0.51 (0.32-0.81) 0.0038 3.12x10-10 rs1815857 21 MCM3AP T 99.1% 95.1% 6.25 (2.91-12.11) 3.13x10-8 98% 95.9% 2.05 (0.76-5.55) 0.146 3.35x10-8 91 4.3.3 Phenotypic Sub-Analysis of the Replicated Gene variants To further examine the role of replicated genetic variants, a deeper phenotypic analysis was performed to determine whether the genotypes within the studied genes were associated with specific neuropathy subtypes (sensory vs. motor neuropathy) in the replication cohort. Clinical data pertaining to sensory and motor neuropathy symptoms were analyzed and tested using Fisher’s exact test for their association with the replicated genetic variants. Of the examined variants, this analysis revealed two significant associations with specific neuropathy subtypes. The G-allele of ARHGAP5 rs8006511 was significantly associated with protection from sensory neuropathy symptoms (p=0.0245), and the T-allele of ACTN1 rs2268979 was significantly associated with a reduced risk of motor neuropathy (p=0.0326) (Figure 4.2a and b). These findings suggest that the protective effects of the variants in ARHGAP5 and ACTN1 may be subtype-specific, with distinct roles in sensory and motor neuropathy, respectively. Figure 4.2 Distribution of patients with different neuropathy subtype (motor or sensory). a) stratified by ARHGAP5 (rs8006511) genotypes, and b) ACTN1 genotypes (rs2268979). 92 4.3.4 Risk Stratification Using Replicated Genetic Variants In order to increase the discrimination ability of the combined-effect genetic model for predicting vincristine-induced peripheral neuropathy, two key genetic variants in ACTG1 and NRG3 – identified as the most overlapping genes in the pathways identified through pathway enrichment analysis (as discussed in Chapter 3; Figure 3.5b) – were incorporated to stratify patients by genetic risk. To maximize statistical power, patients in both the discovery and replications cohorts were combined and stratified into distinct genetic risk groups to better assess the variation in neuropathy incidence over time. Patients were categorized into three groups according to their genetic risk profile. Those who did not carry a protective variant were categorized as high-risk group, while individuals carrying any of the protective variants were categorized as intermediate-risk group, and those carriers of protective variants in both NRG3 and ACTN1 were designated as low-risk group due to their presumed enhanced protection. Patients in the high-risk group exhibited the steepest increase in cumulative neuropathy incidence, with over 50% developing grade ≥ 2 neuropathy within the first six months of chemotherapy. Intermediate-risk patients, who carried at least one protective variant, showed a slower progression of neuropathy, with a lower cumulative neuropathy incidence compared to the high-risk group, particularly after the first month of their chemotherapy (Kaplan-Meier plot; Figure 4.3). Notably, the low-risk group, defined by the presence of both NRG3 and ACTN1 protective variants, showed the most remarkable reduction in peripheral neuropathy incidence, with a significant 2.78-fold lower cumulative incidence of grade ≥ 2 neuropathy over time as compared with the high- and intermediate-risk group (hazard ratio [HR]=0.36, 95% CI: 0.124–0.602; p<0.001) (Figure 4.3). 93 Figure 4.3 Kaplan-Meier plot of the cumulative incidence of vincristine-induced peripheral neuropathy over a 24-month follow-up period. The cumulative incidence is stratified by genetic risk groups based on replicated protective variants. 94 4.4 Discussion In this study, I conducted a replication analysis in an independent cohort of pediatric cancer patients to validate and expand upon the findings of genetic variants associated with vincristine peripheral neuropathy. The analysis replicated two genetic variants highly associated with vincristine-induced neuropathy. Specifically, VTI1A (rs17129858) and ACTN1 (rs2268979) displayed statistically significant associations with reduced neuropathy risk. The meta-analysis further strengthened these results, with 11 variants maintaining genome-wide significance, emphasizing their potential biological relevance to the pathophysiology of vincristine peripheral neuropathy. A subsequent phenotypic analysis suggests that distinct genetic pathways may influence different neuropathy subtypes, which may provide guidance for the anticipation of the susceptibility to developing specific neuropathy symptoms. The risk stratification model incorporating variants in NRG3 and ACTN1 further demonstrates the clinical utility of genetic markers in understanding the patient’s risk for developing vincristine neuropathy as well as providing an opportunity for tailored interventions. For instance, clinicians can implement proactive measures, such as closer monitoring or dose adjustments, to reduce the likelihood of severe neuropathy. Conversely, low risk patients (i.e., carriers of protective alleles) may tolerate standard vincristine dosing without requiring dose capping at 2 mg due to toxicity concerns, thereby preserving vincristine efficacy. Additionally, the discovery of protective variants provides a compelling rationale for the development of pharmacological strategies aimed at mimicking their protective effects in genetically susceptible individuals. Thus, the discovery of these protective alleles could serve as 95 a foundation for the development of targeted therapies (i.e., neuroprotective agents) designed to enhance or mimic the molecular mechanisms that underlie resilience to vincristine-induced nerve damage. Specifically, the discovery that certain alleles (e.g., in NRG3 and ACTN1) are associated with a combined 3-fold reduction in neuropathy risk suggests that the molecular pathways influenced by these genes may serve as viable therapeutic targets. Therefore, beyond their value as predictive biomarkers, these variants could help guide the development of neuroprotective agents that replicate the protective mechanisms observed in resilient patients to mitigate vincristine-induced neuropathy in pediatric cancer patients. Importantly, the allele frequencies and principal component distributions were comparable between the replication and discovery cohorts, suggesting they unlikely to account for the lack of replication observed for the remaining variants in SPDYA (rs12474420), METTL8 (rs79802223), PDE4D (rs12658429), FBN2 (rs12656510), ZFAND3 (rs200858088), NFIB (rs10961381), PAPPA (rs12235805), LRRTM3 (rs10997459), NRG3 (rs12253008), VTI1A (rs17129858), ARHGAP5 (rs8006511), ACTN1 (rs2268979) and MCM3AP (rs1815857). Rather, the smaller sample size of the replication cohort (n=362 vs. n=1,100 in the discovery cohort) likely reduced the statistical power, particularly for detecting variants with smaller effect sizes. As such, studies with larger replication cohorts would be better powered to detect statistically significant associations within the studied genes that did not reach p<0.0038 significance threshold in the current study, thereby determining whether their lack of replication in the current study was due to limited power rather than true absence of effect. 96 Although follow up analyses were conducted in the combined cohort, the sample size for specific sub-analyses remained relatively small, limiting the statistical power to detect weaker associations and to explore associations with specific sensory/motor neuropathy symptoms (e.g., jaw pain, leg pain, extremity weakness, loss of tendon reflexes). Notably, the identification of protective genetic variants represents a significant opportunity to advance our understanding of neuropathy and neuropathic pain. These replicated variants show strong potential as predictive biomarkers and could be considered for clinical implementation. Moreover, mechanistic studies (i.e., animal or cellular studies) will be helpful to provide additional line of evidence and elucidate the biological pathways through which these variants exert their protective effects. In particular, investigating the functional roles of NRG3 and ACTN1 in neural repair and regeneration may provide insights into their contributions to neuropathy protection, and could potentially help inspire new treatment strategies to mitigate neuropathy and neuropathic pain. In conclusion, this study validates the important contributions of two genetic variants that are strongly associated with vincristine peripheral neuropathy and highlights their potential for risk stratification and personalized treatment strategies in pediatric cancer patients in the future. Specifically, these findings might enable assessment of neuropathy risk prior to initiating vincristine therapy, allowing for individualized strategies such as tailored dosing, closer monitoring, or pre-emptive physiotherapy treatment to minimize neuropathy symptoms in high-risk patients (i.e., non-carriers of protective variants). Conversely, patients with protective genetic variants may better tolerate standard vincristine dosing, maximizing its therapeutic efficacy without an increased neuropathy risk. The replication of key findings across independent cohorts strengthens the evidence base for these associations, while the risk 97 stratification model offers a practical framework for integrating genetic insights into clinical decision-making. Further research investigating the biological mechanisms of these variants may help further elucidate the specific roles of these genes in protection against vincristine peripheral neuropathy risk and provide innovation for new prevention/management strategies of vincristine peripheral neuropathy, ultimately improving outcomes for pediatric oncology patients. To determine if these findings are relevant to adult population, a dedicated study in adults is needed. The detection and diagnosis as well as incidence and severity of vincristine-induced peripheral neuropathy may differ between pediatric and adult populations due to differences in physiology, comorbidities, and the use of concomitant medications. The incidence of neuropathy in pediatric patients can be as high as 78%,106 whereas in adults, it ranges from 30-50%.275, 276 Such difference in the incidence potentially suggests that different genetic and biological factors may influence neuropathy risk between children and adults. While predictive pharmacogenetic biomarkers remain constant across the lifespan, their expression and impact can differ significantly between children and adults. In addition, the dynamic developmental changes such as drug-metabolizing enzymes and organ function over time necessitate dedicated research to optimize drug therapy in children and adult populations. Unlike adults, children typically have fewer comorbidities and take fewer concomitant medications, which can mask genetic predictors of ADRs. This highlights the necessity for independent pharmacogenomic studies in children and adults to identify genetic predictors of vincristine-induced neuropathy. 98 Chapter 5: Targeted CEP72 Gene Variant (rs924607) Analysis 5.1 Introduction The promoter variation in the CEP72 gene is one of the most replicated genetic markers for identifying children at high risk of developing vincristine-induced peripheral neuropathy. A GWAS conducted by Diouf et al in 2015 identified a specific variation in the promoter region (rs924607) of the CEP72 gene as being significantly associated (OR=2.43, 95% CI: 1.70-3.49) with an increased incidence of vincristine-induced peripheral neuropathy in pediatric ALL patients. This study found that patients carrying the high-risk genotype (TT) exhibited significantly higher risk of vincristine neuropathy compared to those with CT or CC genotypes. Carriers of TT genotype were particularly susceptible during long-term vincristine therapy, which typically involved 20–40 doses over a treatment duration of 1–2 years. Interestingly, the association between CEP72 rs924607 and vincristine-induced neuropathy was not consistently replicated in subsequent studies. Diouf et al (2016) failed to replicate the association (unpublished data; p=0.40), 270 and other studies similarly did not find a significant association when neuropathy risk was examined during the induction phase of treatment. 192 These results suggest that the effect of CEP72 may be more relevant in long-term therapy, highlighting the potential differences in the underlying etiology of neuropathy during the induction and continuation phases of treatment. In other word, neuropathy risk driven by CEP72 may be time-dependent, which is specifically relevant in patients undergoing prolonged vincristine therapy. Confirmation of this hypothesis in independent cohorts remains necessary. 99 Neither of our discovery cohort nor replication cohort showed a significant association for CEP72 rs924607 with vincristine peripheral neuropathy risk. In our full cohort, 60.1% of the patients who developed peripheral neuropathy (CTCAE grade ≥2) reported symptoms within the first month of chemotherapy (corresponding to the induction phase), and 87.5% of these cases experienced peripheral neuropathy before completing 6 months of vincristine therapy, which may explain the lack of significant association between CEP72 rs924607 and neuropathy risk in the discovery/replication analyses. Given the evidence from previous reports suggesting that the CEP72 promoter variant may only influence neuropathy risk during long-term therapy, I conducted a focused analysis to investigate whether CEP72 rs924607 variant was associated with the risk of peripheral neuropathy after long-term vincristine therapy in our cohort. A subgroup of cases who developed neuropathy after six months of vincristine therapy was selected, along with a control group of patients who received vincristine for at least six months without developing neuropathy. 5.2 Methods 5.2.1 Patient Inclusion/Exclusion Criteria Vincristine-induced neuropathy was assessed using the CTCAEv5.0 criteria, which classifies neuropathy severity into the following grades: no signs of neuropathy, mild neuropathy (grade 1), moderate (grade 2), severe (grade 3), and life-threatening (grade 4). No cases of neuropathy-related deaths (grade 5) were reported in the cohort. I sought the time of first declaration of neuropathy symptoms and calculated the vincristine cumulative dose to neuropathy onset in all the cases. Cases who developed significant vincristine-induced neuropathy (CTCAE grade ≥ 2) 100 after receiving vincristine treatment for a minimum of six months were included in the analysis, along with controls who received vincristine therapy for at least six months without experiencing neuropathy symptoms. 5.2.2 Analysis of Clinical and Demographic Data Potential associations between clinical characteristics and the occurrence of vincristine peripheral neuropathy were analysed using Wilcoxon–Mann–Whitney test (for continuous variables) and Chi-square test (or Fisher's exact test when cell counts were less than five) for categorical variables. Since the subsequent genetic association test did not employ a matched case‐control analysis, clinical and demographic factors that differed significantly between cases and controls were included as covariates to account for potential confounding in the genetic association analysis. 5.2.3 Genetic and Statistical Analysis Genotyping of CEP72 rs924607 was performed on all patients using Illumina Infinium® Global Screening Array GSAv2. A recessive genetic model was applied to evaluate the association between the CEP72 rs924607 (TT genotype) and the risk of vincristine neuropathy, which is the model reported by the discovery study to initially identify this variant. 151 The multivariate logistic regression analysis was conducted with PLINK v1.9 embedded in BC platform and was adjusted for age at cancer diagnosis, concomitant antifungal Azoles, vincristine cumulative dose and genetic ancestry (PCs 1–4), and p-value of <0.05 was considered statistically significant, indicating a meaningful association between the CEP72 variant and vincristine neuropathy risk. 101 5.2.4 Meta-Analysis A follow-up meta-analysis was performed including the results on the association of CEP72 rs924607 and peripheral neuropathy from this study, alongside results from 7 previous studies/cohorts that investigated this association in pediatric patients with cancers (Table 4.3). For each study, the reported sample size, case-control definition and distribution, OR and 95% CI, and results from multivariate logistic regression analyses (CC/CT genotype vs. TT genotype) were extracted and used as input. The meta-analysis was performed with R, employing Stouffer's method to combine p-values across studies. The choice between a fixed-effect or random-effect model was based on the observed degree of heterogeneity (I2), which translates into the proportion of total variation contributed by variation between included studies. 102 Table 5.1 Summary of studies investigated CEP72 (rs924607) for the risk of vincristine-induced neuropathy in pediatric cancer patients. Study (year) Cohort N of cases/ total Neuropathy assessment / case/control definitions Sex (% male) Patients’ ancestry Association between CEP72 rs924607 and vincristine neuropathy p-value OR (95% CI) Diouf et al – St Jude cohort (2015) 151 Children 64/222 CTCAE v1.0 0–1 vs. 2–4 42.3 Mainly European 1.25x10−6 2.43 (1.70–3.49) Diouf et al – COG cohort (2015) 151 22/99 59.6 0.0004 4.1 (1.86-9.01) Gutierrez-Camino et al (2016) 192 Children 36/142 CTCAE v1.0 0–1 vs. 2–4 57.0 All European (Spanish) 0.5 0.65 (0.17–2.43) Zgheib NK et al (2018) 198 Children 26/133 CTCAE v4.0 0–1 vs. 2–4 57.1 Arab 0.953 1.0 (0.3–4.3) Wright et al (2019) 148 Children 167/224 CTCAE v4.0 0 vs. 2–4 50.8 Mainly European 0.02 3.43 (1.15–10.3) Kavcic et al (2020) 199 Children/ Adolescents 9/25 Not reported 50.0 All Middle European 0.009 2.2 (1.76–12.93) Goodenough et al (2022) 200 Children 158/990 CTCAE v5.0 not reported vs. 2–4 52.9 Mainly European 0.02 2.47 (1.15–5.31) Marangoni-Iglecias et al (2024) 277 Children 8/86 CTCAE v5.0 0 vs. 1–4 52.0 All Caucasian 0.883 Not reported Current study Children 27/319 CTCAE v4.0 0 vs. 2–4 53.3 Mainly European 0.012 3.46 (1.14–10.45) 103 5.3 Results 5.3.1 Patient Characteristics After applying the inclusion criteria, a total of 319 patients with childhood cancers who received vincristine for at least 6 months were included in this analysis, including 27 cases (CTCAE grade ≥2) and 292 controls. Table 5.2 summarizes the clinical and demographic characteristics of the study population. The majority of the neuropathy cases (81.48%) were defined as grade 2 (n=22), with a smaller number (18.52%) classified as grade 3 (n=5). No cases of grade 4 or 5 neuropathy were observed. Patients with mild neuropathy (grade 1) were excluded because these individuals exhibit only clinical or diagnostic observations, and they do not require medical intervention. The median number of vincristine doses received was 33 (SD: ±8.84) for cases and 63 (SD: ±11.91) for controls, corresponding to cumulative vincristine doses of 49.5 mg/m2 (SD: ±13.26) and 63 mg/m2 (SD: ±117.86), in cases and controls respectively. Age at cancer diagnosis was statistically significantly associated with the occurrence of neuropathy. Cases were also more likely to have received concomitant azoles compared to controls. To account for potential confounding effects on the genetic association analysis, all significantly associated demographic and clinical variables: age at cancer diagnosis, vincristine cumulative dose, and azole antifungals use were included as covariates in regression analysis along with genetic ancestry. 104 Table 5.2 Clinical and demographic characteristics of the CPNDS pediatric patients. IQR=interquartile range; PC=principal component; avincristine cumulative dose to toxicity in cases and total cumulative dose in control; bfluconazole, itraconazole, ketoconazole, posaconazole or voriconazole. Patient characteristics Cases Neuropathy grade ≥ 2 (N=27) Controls No neuropathy (N=292) p-value Sex Female (%) 10 (37%) 139 (48%) 0.32 Male (%) 17 (63%) 153 (52%) Age at diagnosis Years, median (IQR) 3.43 (2.21-5.41) 4.59 (2.91-7.85) 0.03 Vincristine cumulative dosea mg/m2, median (IQR) 49.5 (46.5-56.5) 63.0 (51.0-73.5) 0.0001 Concomitant medications (%) Antifungal azolesb 8 (30%) 42 (14%) 0.05 Clarithromycin 1 (4%) 33 (11%) 0.33 Nifedipine 4 (15%) 20 (7%) 0.13 Phenytoin 1 (4%) 5 (2%) 0.41 PC1 African from non-African, median (IQR) 0.00821 (0.00589 – 0.00960) 0.00924 (0.00620 –0.00963) 0.67 PC2 East Asian from non-East Asian, median (IQR) 0.0112 (-0.00356 –0.0119) 0.0117 (0.00508 – 0.0121) 0.17 PC3 Admixed American from non-Admixed American, median (IQR) 0.00471 (-0.00449 –0.0027549) 0.00488 (0.00400 –0.00581) 0.08 PC4 South Asian from non-South Asian, median (IQR) -0.00502 (-0.00589 – -0.00177) -0.00442 (-0.00566 – -0.00249) 0.55 105 5.3.2 Replication of Genetic CEP72 rs924607 Association with Vincristine Neuropathy The CEP72 rs924607 TT genotype was significantly associated with an increased risk of neuropathy in children receiving long-term vincristine therapy (p=0.012; OR=3.457 [95% CI%: 1.143-10.45]). One hundred and twenty-three patients (38%) were homozygous for the major allele (CC), 152 patients (48%) were heterozygous (CT) and 46 (14%) were homozygous for the minor allele (TT). The frequency of the TT genotype was notably higher among neuropathy cases (26%) compared to controls (13%) (Figure 5.1a). These findings were further confirmed by a meta‐analysis of the current study data combined with results from 7 previously published CEP72 studies (Figure 5.1b; Total n cohorts=8; combined Z-score=6.90; OR=2.45 [95% CI: 1.89–3.17]; p=5.15×10-12; heterogeneity: I2=12.31%). 106 Figure 5.1 CEP72 association with vincristine-induced peripheral neuropathy. a) Recessive genotype frequencies for CEP72 rs924607 differed significantly between vincristine-induced peripheral neuropathy cases and controls (p=0.012). The TT risk genotype occurred in 26% of cases (CTCAE grade ≥2) and 13% of controls; b) Meta-analysis (random effects model) of eight cohorts investigating the association between CEP72 rs924607 and risk for development of vincristine-induced peripheral neuropathy, resulting in a statistically significant effect of TT genotype on risk of development of peripheral neuropathy. The turquois summary diamond indicates meta‐analysis results including all studies. 107 5.4 Discussion This analysis confirms that the TT genotype of the CEP72 rs924607 polymorphism in the promoter region is associated with an increased risk of neuropathy in patients with pediatric cancers who received vincristine for at least 6 months. These findings suggest that the risk conferred by CEP72 rs924607 is likely treatment phase-specific, emphasizing its relevance during prolonged vincristine treatment. The results of this analysis validate the importance of CEP72 as a pharmacogenetic biomarker the prediction of such a serious adverse reaction caused by an essential chemotherapeutic agent. CEP72 rs924607 is a promising predictive marker of vincristine neuropathy given its potential role in the mechanism of action of vincristine. These results, supported by a meta‐analysis of published CEP72 studies, 151, 192, 198-200, 214, 277 provide validation of this association with neuropathy risk in pediatric patients on vincristine for at least six months. In particular, the replication of CEP72 in diverse pediatric cohorts confirms the generalizability of this pharmacogenomic marker, though the failure of previous replication attempts as well as the current discovery/replication cohorts’ analyses brings to light the importance of phenotypic considerations (i.e., neuropathy assessment, case/control definitions, timing of neuropathy) in pharmacogenomic studies of vincristine peripheral neuropathy. 192, 205, 271, 277 Given the current level of evidence for the CEP72 risk genotype, optimizing therapeutic personalized interventions rs924607 TT patients such as increased clinical monitoring, dose adjustments or targeted rehabilitation (e.g., earlier initiation of physiotherapy) could potentially be beneficial to prevent development of long-term impairments and improve quality of life in 108 survivors. This is especially important for the growing childhood cancer survivor population as peripheral neuropathy in long-term survivors is associated with poor mobility and reduced walking endurance. 278 Since children with homozygous (TT) genotypes are suggested to be more sensitive to vincristine, 151 these data support the need to test interventions that employ vincristine dose-reduction among children with high‐risk genotypes, provided these adjustments maintain efficacy and survival outcomes. Such adaptations would align with the growing emphasis on personalized medicine, optimizing therapeutic benefits while minimizing toxicity. The results of an ongoing clinical trial (ClinicalTrials.gov: NCT03117751) investigating the influence of vincristine dose and duration reductions in patients with ALL and acute lymphoblastic lymphoma carrying CEP72 rs924607 TT will also be highly informative in guiding such clinical practices in the future. This randomized trial aims to determine whether the incidence and/or severity of acute vincristine-induced peripheral neuropathy can be reduced by decreasing the dosage of vincristine in patients with CEP72 TT genotype without compromising vincristine treatment efficacy, or by shortening the duration of vincristine therapy in standard/high-risk patients with the CEP72 rs924607 CC or CT genotype. If successful, these findings could transform the prevention of vincristine-induced neuropathy, offering a new paradigm for personalized treatment in pediatric oncology. 109 Chapter 6: General Discussion and Conclusions Over the past few decades, the survival rates of children diagnosed with cancer have significantly improved from 58% during the mid-1970s to 85% during 2012 through 2018. 279, 280 This progress has shifted the focus of pediatric oncology research from solely improving survival outcomes to also reducing treatment-induced toxicities, therefore, the need to mitigate ADRs has become increasingly apparent. Vincristine is a cornerstone chemotherapy that currently plays an indispensable role in the treatment of pediatric cancers. In the United States alone, over half of all children with cancer who receive chemotherapy are given a treatment regimen that includes vincristine. 144, 145 Given that vincristine is first-line therapy for many cancer types and the significant improvement of the 5-years survival rates of patients with childhood cancers, 279, 280 simply discontinuing vincristine chemotherapy might not be a viable solution. Instead, there is a need to better predict which patients are at risk of developing toxicity in order to improve the safety of vincristine therapy, particularly for young children whose lives are just beginning. The problem of vincristine-induced neuropathy has been extensively studied and despite this, the underlying mechanisms of neuropathy remain incompletely understood. There is also an ongoing need to discover and implement screening strategies to identify patients who are highly susceptible to this life-threatening ADR. Studies have reported that up to 78% of children receiving vincristine experience clinically significant peripheral neuropathy during treatment, 106, 179 with more recent studies suggesting that 82% of neuropathy cases were newly identified approximately seven years after diagnosis, which is well after the cessation of vincristine treatment. 281 110 Currently, there are no established predictive tools to identify patients who are more susceptible to vincristine neuropathy, and there is a lack of effective medications or interventions to prevent or mitigate this serious reaction. An improved understanding of the contribution of genetic variations to the risk of vincristine-induced neuropathy would make it possible to identify patients who are at higher and lower risk of this adverse drug reaction. Using the largest genetic cohort of pediatric oncology patients treated with vincristine and assessed for vincristine-induced peripheral neuropathy to date, this dissertation aimed to 1) identify and evaluate, through an updated systematic review, genetic variants that have been associated with vincristine-induced peripheral neuropathy in the existing literature, 2) uncover novel genomic factors using a genome-wide approach to add to the current understanding of the genetic and mechanistic basis of vincristine peripheral neuropathy, and 3) replicate and further explore the identified pharmacogenetic variants associated with vincristine peripheral neuropathy in pediatric cancer patients to better understand the underlying pathophysiology of this ADR. 6.1 Summary of key findings Chapter 1 highlighted vincristine peripheral neuropathy as one of the major ADRs in pediatric oncology patients. It also discussed the current knowledge of the mechanism of action of vincristine and its clinical use, the types of vincristine-induced neuropathies, what is currently known about the pathophysiology of vincristine peripheral neuropathy and the clinically available diagnostic tools and measurements. This chapter also presented the current evidence on known treatment-related and patient-related risk factors and current treatment/prevention. Finally, it presented the scope of genetics in predicting and preventing vincristine-induced peripheral neuropathy. 111 In Chapter 2, a systematic review was conducted to summarize and evaluate the genetic variants that have been reported in the literature to be associated with vincristine peripheral neuropathy. This is the most recent systematic review of the pharmacogenomics of vincristine-induced peripheral neuropathy in pediatric oncology patients. The review identified 28 genetic studies that investigated a total of 34 genes and miRNAs. Of the identified genetic variants, the CEP72 gene variant (rs924607) has been the most extensively studied and was significantly associated with risk for vincristine neuropathy with various tumour types (Table 2.2). This chapter mainly discussed the proposed biological roles of the identified genes in vincristine-induced peripheral neuropathy (Figure 3.1). In Chapter 3, I sought to uncover actionable genomic associations by performing the largest GWAS analysis of vincristine peripheral neuropathy in pediatric cancer patients to date. I discovered 13 genomic variants that are significantly associated with neuropathy risk and protection. Among these, a variant in MCM3AP gene substantially increased the risk of neuropathy by 6-fold while variants in 12 genes (SPDYA, METTL8, PDE4D, ZFAND3, NFIB, ZFAND3, FBN2, PAPPA, LRRTM3, NRG3, VIT1A, ARHGAP5 and ACTN1) exerted significant protection from neuropathy risk by 40-93%. Conducting pathway enrichment analyses to understand the biological processes implicated in these associations, I identified four key pathways related to nerve development, nerve myelination, cytoskeleton/microfibril function, and neuronal transmission pathways; providing new insights into the mechanistic underpinnings of vincristine peripheral neuropathy. 112 I additionally examined the current knowledge of the biological function of these genes to generate supporting hypotheses about their prospective role in the development of vincristine neuropathy (Figure 3.6). LRRTM3, for example, appears to play a protective role through its involvement in synaptic stability and neuronal plasticity. ARHGAP5 regulates cytoskeleton dynamics and integrity. VTI1A is involved in vesicular trafficking, including the transport of neurotransmitters within neurons. FBN2 encodes fibrillin-2, a key structural component of elastic fibers in connective tissues, and ZFAND3 is involved in protein degradation processes, particularly through the ubiquitin-proteasome system. Genes such as NRG3 and ACTN1 were identified as central players in pathways related to axonal guidance, cytoskeletal dynamics, and neurotransmission – processes that are critical for maintaining neuronal function. These pathways provide potential targets for therapeutic intervention, as they represent critical processes that can be modulated to prevent or mitigate neuropathy. This chapter emphasized the importance of integrating genomic data with functional pathways to identify actionable targets. By linking genetic findings to specific biological processes, this work has paved the way for a more nuanced understanding of pathophysiology of vincristine peripheral neuropathy. Highlighted in Figure 3.6 is a summary of how these identified genes could be integrated into the current knowledge base regarding potential effect on modulating susceptibility to peripheral neuropathy. Chapter 4 extended from the work performed in Chapter 3 by pursuing a follow-up validation analysis in an independent replication cohort. This study replicated two of the genetic associations with vincristine peripheral neuropathy. Interestingly, the replicated variants exerted protection against peripheral neuropathy with up to 93% reduction in the overall risk. A time-to- 113 event analysis was performed using the first notation of neuropathy symptoms and stratified by genetic data to determine when neurotoxicity occurred. These data showed that the genes NRG3 and ACTN1 and their associated pathways emerged as key players in mitigating/protecting against vincristine peripheral neuropathy, highlighting the potential utility of incorporating genetic variants in risk stratification. Finally, Chapter 5 analyzed the CEP72 promoter variant (rs924607) as a candidate gene variant associated with vincristine peripheral neuropathy in pediatric patients. Although previous studies provided mixed evidence regarding its role, these new findings demonstrated that the TT genotype of rs924607 was significantly associated (OR=3.46, 95% CI:1.14-10.45; p=0.012) with increased neuropathy risk in a subset of children who received long-term vincristine therapy. Importantly, this association appeared to be treatment phase-specific, with its impact most pronounced during the continuation phase of chemotherapy. A meta-analysis was also conducted and confirmed the robustness of the CEP72 association across multiple studies, reinforcing its potential as a predictive biomarker. Furthermore, the analysis highlighted the challenges of phenotypic heterogeneity in pharmacogenomic research and underscored the importance of precise clinical characterization. Collectively, the findings show that multiple genetic factors contribute to the overall underlying genetic susceptibility to vincristine peripheral neuropathy and underscore the complexity of the pathways involved. The development of vincristine-induced peripheral neuropathy is clearly influenced by multiple intricate interactions, including genetic and non-genetic factors, necessitating a multigenic and integrative approach for future risk stratification of individual patients. Future research efforts should focus on developing risk 114 prediction models that combine the effects of multiple genetic variants with patient clinical characteristics to provide a comprehensive risk assessment. 6.2 Strength and Significance A strength of this dissertation is the use of deeply characterized patient cohorts with extensive clinical data collected and assessed by CPNDS clinicians and researchers. This level of characterization is highly important factor for the success of pharmacogenomic GWASs. 282 Using the available clinical data, discovery and replication cohorts in Chapters 3-4 were separated into cases and controls based on established grading criteria in order to limit phenotype heterogeneity within each group. 105 These cohorts were also comprised of control patients with similar cancer types treated with the same chemotherapy (i.e., vincristine) as the cases with comparable doses, as opposed to population controls, to enable better comparisons between cases and controls that minimize effects due to disease or drug status. In addition, the extensive phenotyping in this study enabled the detection of genetic variants with strong effect sizes that have passed the genome-wide significance threshold. Another strength of this dissertation is the follow-up analyses that extended beyond the GWAS to identify the mechanisms underlying the phenotype, rather than just reporting the associated variants. The gene set analyses in Chapter 3 implicated several pathways related to normal nerve development and function. These results expand our knowledge about the genetic factors that contribute to the overall susceptibility of vincristine-induced peripheral neuropathy. Finally, in Chapter 4 and 5, I performed follow-up replication analyses to validate the findings, as well as to further explore previously reported genes (i.e., CEP72), providing a further layer of evidence for the identified associations. Overall, the results discussed in this work provide additional insights into the mechanisms of peripheral 115 neuropathy that can help guide future pharmacogenomic and functional studies to further understand the mechanisms and pathways involved in this ADR. The significance of the findings of this work lies in their potential clinical applications. First, they offer a pathway to precision medicine by enabling the risk stratification of patients based on their genetic risk of vincristine-induced neuropathy. Second, the identification of protective variants highlights opportunities to leverage these genetic mechanisms to develop therapeutic strategies aimed at enhancing neuronal resilience during chemotherapy. The development of neuropathy preventive strategies based on the risk pathways that are important in patients will improve the safety and efficacy of vincristine-chemotherapy for the treatment of cancer in patients. For example, this may differentiate who would benefit more from closer monitoring for early diagnosis and treatment. Similarly, the use of early preventative therapies may prevent the progression of neuropathy into more severe forms and could thus maximize a patient’s daily life function and independence. This could include pre-emptive physiotherapy, pharmacological interventions, and/or increased monitoring to mitigate peripheral neuropathy symptoms or prevent their occurrence. Early interventions with physiotherapy and occupational therapy may prevent irreversible joint contractures resulting from severe motor neuropathy. 283, 284 There are currently no guidelines on pharmacogenetic testing recommendations for vincristine in pediatric patients and dosing recommendations for vincristine are largely based upon tradition with few dose studies since the 1960s. 285 Consequently, the current dosing recommendations for vincristine have come into question, 138 including reports of lower vincristine exposure contributing to cancer relapse and reduced cancer survival rates in children. 139, 286 Due to the 116 lack of universally shared strategies currently used for vincristine-neuropathy prediction and prevention, patients who are not susceptible to vincristine-induced neuropathy may receive sub-therapeutic doses of vincristine due to an empirical upper cap on the dose (2 mg) while others may experience severe neuropathy at the same dose. Today, pharmacogenetic testing for drug toxicity biomarkers is becoming more widely available and increasingly cost-effective, and rapid testing methods are being developed and implemented. Predictive genetic testing represents a promising avenue for translation. Thus, the significance of the work performed in this dissertation provides results that offer opportunities for modifying treatment plans tailored for each individual patient based on the patient’s risk profile. For example, patients at the highest risk of developing neuropathy could be recommended for vincristine dose reductions or treatment protocols with lower dose intensities. Ultimately, alterations in vincristine therapy need to be balanced between the risk of vincristine neuropathy and survival outcomes (maximize cancer cell killing and minimize toxicity) and will require clinical testing to determine treatment with an optimized risk-benefit ratio for different predicted risk groups. Overall, these results have the potential to change the dosing recommendations of vincristine in cancer therapy and move decision-makers and clinicians with one step closer to personalizing vincristine therapy, which could reduce healthcare costs associated with this ADR and drastically improve overall patient quality of life. 6.3 Limitations Although this research work includes largest genome-wide study conducted for this drug reaction in children, the work performed in this thesis is not without limitations. First, the current study was underpowered to detect associations for rare genetic variants (i.e., MAF <1%) with ORs 117 below 2.0, and therefore, the analysis focused on common genetic variant. Given the importance of rare variations for the overall genetic susceptibility in pharmacogenomics traits, 214 studies with larger cohort sizes would be helpful to discover less frequent genetic variations that could explain the risk of severe neuropathy cases. Furthermore, this study had limited power to conduct secondary analyses, particularly when patients were divided into subgroups based on neuropathy types to investigate associations with specific sensory or motor neuropathy symptoms, such as jaw pain, leg pain, extremity weakness, or loss of tendon reflexes, or to study associations with more severe neuropathy phenotypes (i.e., neuropathy grades 3 or 4). These analyses were therefore not conducted. Another limitation of this study was the lack of mechanistic studies to directly validate the functional impact of identified genetic variants, which leaves gaps in our understanding of how these variants influence vincristine neuropathy risk at the molecular level. This limitation was partially mitigated through the pathway analysis, which provided insights into the potential biological mechanisms and pathways influenced by the identified genes, offering basis for future functional validation studies. Additionally, the dose and duration of vincristine treatment must also be considered. Although any neuropathy reaction of grade ≥ 2 to vincristine was considered a case regardless of the treatment intensity, a threshold based on drug dose and duration must be defined to ensure that patient controls have had enough exposure to vincristine to potentially experience a notable neuropathy. That being said, the date of the first documentation of neuropathy does not necessarily reflect the actual onset time of the reaction as symptoms might occur days or weeks before being documented. Therefore, the phenotyping process in the current 118 cohort included a thorough review of patient records to identify any documented descriptions of neuropathy symptoms reported by the patient prior to the formal diagnosis. 6.4 Future Directions Future work from this thesis may take several forms. First, it would be helpful to expand these results by using animal (e.g., C57Bl/6 mice, zebrafish, or Caenorhabditis elegans) or cellular (e.g., iCell sensory neurons derived from human iPSCs) model systems to further investigate and elucidate the complex biological mechanisms through which the identified genetic variants contribute to the development of vincristine peripheral neuropathy. In particular, animal studies could provide insights into dose-response relationships and temporal dynamics of neuropathy development, while cellular models could uncover molecular interactions and downstream signaling pathways influenced by genetic variants. Future functional studies could explore the roles of genes such as ACTN1 and NRG3 on neuronal function and response to vincristine through using knock-out or knock-in models (Actn1−/− and Nrg3−/−), introducing the specific variants I have identified, or employing human-derived cell models from individuals who carry these variants and their isogenic controls. Using these models (e.g., C57Bl/6 mice) will allow for assessing how variants in these two genes can affect specific mechanisms and better understand how the excess or reduced activity of their respective proteins could contribute to the pathogenesis of peripheral neuropathy. For instance, functional evaluation of ARHGAP5 by its knockout in mice was found to cause several defects in neuronal development, including defects in axon guidance and fasciculation. 268 Conventional and conditional knockout of LRRTM3 mice displayed specific decrease in excitatory synapse density 119 and excitatory synaptic transmission. 229, 287 VTI1A knockdown results in reduced spontaneous synaptic vesicles fusion and impairs spontaneous high-frequency glutamate release, which exerts neuropathic effects. 288-290 While these systems allow for controlled experiments and direct assessment of gene function, they do not fully recapitulate the complexity of human responses to chemotherapy. Therefore, findings from model systems must be interpreted cautiously and validated in clinical or ex vivo human settings to determine their relevance to patient outcomes. Work in patient-derived iPSCs has shown promise in providing direct insight into the effects that known genetic variants have on these cells when treated with vincristine, 151 which could be used to assess the functional relevance of the identified genetic findings from Chapters 3 and 4. Furthermore, integrating these systems into cancer models could help evaluate the balance between the development of vincristine neuropathy and treatment efficacy/survival rates, as well as determining the effects of these variants on the neuron, axon, and myelin during stages of damage and recovery from vincristine-induced neurodegeneration. Such models might also enable testing potential neuroprotective agents targeting the identified pathways. For instance, functional evaluation experiments of PDE4D gene, although was not replicated in the validation cohort analysis, showed that its inhibition can reverse neuropathic pain in mice, 257 which makes it a promising therapeutic target for improving nociceptive symptoms associated with vincristine neuropathy. Finally, it will be beneficial for future studies to use high‐throughput sequencing approaches to delineate extreme cases of vincristine-induced neuropathy in future studies, given the importance of rare variation for pharmacogenomic traits. 214 In particular, re-sequencing the discovered 120 genes will facilitate the identification of additional genetic variants – both common and rare – that could be associated with peripheral neuropathy risk, whether it is an indirect association (in LD with the identified variants), or directly (other variants within same genes may be independently associated with vincristine neuropathy). At the same time, this analysis will provide genotype information and fine mapping of the functional variants within the discovered genes, such as ACTN1, NRG3, and ARHGAP5. In the current research, I performed targeted genotyping for specific genetic variants, complimented with imputation, but did not examine the full range of potential genetic variants. Performing whole-genome sequencing on our cohort will potentially facilitate future identification of other genes involved in vincristine neuropathy risk. Overall, future research should prioritize replicating and functionally validating the genetic findings from this thesis while leveraging diverse populations and advanced genomic technologies to expand the understanding and the clinical translation of pharmacogenomics in vincristine-induced peripheral neuropathy. 6.5 Final Remarks For many years, ADRs from the treatment of cancer were regarded as the price to pay for the survival from an otherwise fatal disease. In the era of personalized medicine, these views are beginning to change. Pharmacogenomics has been singled out as one of the most promising areas in precision health and provides a new hope for safer cancer therapy. 291 It is well understood that individual genetic variability in drug response plays an important role in a patient’s risk of experiencing severe ADRs, and thus the goal of pharmacogenetic testing in pediatric oncology is for children and families to no longer have to choose between survival and toxicity. 292 121 One of the advantages of association studies is that they can serve as a corner stone for future studies. The type of work discussed in this thesis may ultimately help to reveal genetic markers that will advance our ability to more accurately predict disease development and to tailor personalized treatments for each individual patient. The main goal of such treatments in cancer patients receiving vincristine would be to mitigate, or preferably prevent, the development of peripheral neuropathy. This would reduce the huge burden incurred on patients, their caregivers and the entire society, decrease healthcare expenses and time consumed for treatments, improve the efficacy of vincristine therapy and decrease adverse effects. While all these goals could still be far out of our reach, the current work provides an additional step in this direction. In conclusion, this thesis highlights the complex role of genetic factors in influencing the risk of vincristine peripheral neuropathy in pediatric cancer patients. By identifying and validating key genetic variants and pathways, this work provides a foundation for the development of targeted interventions aimed at reducing the burden of neuropathy. Future research efforts should focus on bridging the gap between genetic discovery and clinical application, ensuring that the benefits of precision medicine are realized for all children undergoing cancer treatment. The findings presented here not only contribute to the scientific understanding of vincristine-induced neuropathy but also provide a roadmap for translating these discoveries into tangible benefits for patients and families affected by childhood cancer. The work described in this dissertation further advances the understanding of the genetic involvement and potential mechanisms associated with vincristine peripheral neuropathy. After 122 reviewing and evaluating genetic associations identified in the literature, I determined that genetic variants in NRG3 and ACTN1 along with CEP72 had strong evidence to be recommended for predictive pharmacogenetic testing. 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Gene Variant Author (Year of publication) ABCB1 rs1045642 Plasschaert et al (2004) Ceppi et al (2014) Zgheib et al (2018) rs1128503 Ceppi et al (2014) Zgheib et al (2018) rs2032582 Plasschaert et al (2004) Ceppi et al (2014) ABCC2 rs717620 Zgheib et al (2018) ACTG1 rs1139405 Ceppi et al (2014) rs7406609 Ceppi et al (2014) CAPG rs6886 Ceppi et al (2014) CEP72 rs924607 Gutierrez-Camino et al (2016) Zgheib et al (2018) Klumpers et al (2022) CYP1A1 rs4646903 Abo-Bakr et al (2017) CYP3A4 rs2740574 Guilhaumou et al (2011) Kishi et al (2007) GSTP1 rs1695 Kishi et al (2007) Abo-Bakr et al (2017) MAP4 rs11268924 Ceppi et al (2014) rs1137524 Ceppi et al (2014) rs1875103 Ceppi et al (2014) rs11711953 Ceppi et al (2014) MTHFR rs1801133 Kishi et al (2007) rs1801131 Kishi et al (2007) SLC19A1 rs1051266 Kishi et al (2007) TUBB rs6070697 Ceppi et al (2014) rs10485828 Ceppi et al (2014) VDR rs2228570 Kishi et al (2007) XRCC1 rs1799782 Abo-Bakr et al (2017) 158 Figure A1. Top 4 principal components (PCs) representing the distribution of patients compared to samples from the 1000 Genomes Project using PCs 1-4. Abbreviations: PC=Principal Component; AFR=African; AMR=American; EAS=East Asian; EUR=European; SAS=South Asian; VPN=Vincristine peripheral neuropathy. 159 Patient characteristics Full cohort (N=1100) Age (years at cancer diagnosis, median [IQR]) 5.24 (3.06-9.92) Sex Male (%) 563 (51.2%) Female (%) 537 (48.8%) Tumour Type, count (%) Acute lymphoblastic leukemia 660 (60.00%) Wilm’s Tumor 86 (7.82%) Hodgkin Lymphoma 82 (7.45%) Medulloblastoma 49 (4.45%) Rhabdomyosarcoma 48 (4.36%) Ewing’s Sarcoma 42 (3.82%) Non-Hodgkin Lymphoma 39 (3.55%) Hepatoblastoma 19 (1.73%) Burkitt Lymphoma 16 (1.45%) Sarcoma 10 (0.91%) Primitive Neuroectodermal Tumor 9 (0.82%) Pinealoblastoma 7 (0.64%) Astrocytoma 6 (0.55%) Neuroblastoma 5 (0.45%) Glioma 3 (0.27%) Peripheral Neuroectodermal Tumour 2 (0.18%) Pleuropulmonary Blastoma 2 (0.18%) Other tumour types 15 (1.37%) Genetic ancestry, count (%) European 763 (69.36%) Mixed Ancestry 188 (17.10%) American 71 (6.45%) East Asian 44 (4.00%) African 18 (1.64%) South Asian 16 (1.45%) Table A2. Patients clinical and treatment characteristics in discovery cohort. Abbreviations: IQR=Inter-quartile range. 160 Table A3. Timing and overlap of concomitant therapy with the onset of vincristine-induced peripheral neuropathy. aOnly concomitant therapy given before the onset of vincristine-induced neuropathy was considered; bAntifungal Azoles = fluconazole, ketoconazole, posaconazole, itraconazole and voriconazole. a) ZFAND3 locus b) VTI1A locus Concomitant medication Cases received concomitant medication, N (%)a Case who declared neuropathy symptoms while receiving concomitant therapy, N (%) Cases who declared neuropathy symptoms after completion of concomitant therapy, N (%) Neuropathy reaction occurred during or within 3 months after completion of concomitant therapy, N (%) ≤3 months after the end of concomitant therapy >3 months after the end of concomitant therapy Antifungal Azolesb 87 (15.8%) 34 (6.1%) 34 (6.1%) 19 (3.4%) 68 (12.3%) Nifedipine 66 (12.0%) 27 (4.9%) 23 (4.1%) 16 (2.9%) 50 (9.0%) Clarithromycin 20 (3.6%) 2 (0.3%) 9 (1.6%) 9 (1.6%) 11 (2.0%) Phenytoin 8 (1.4%) 4 (0.7%) 4 (0.7%) 0 (0.0%) 8 (1.4%) 161 c) ACTN1 locus d) NFIB locus e) ARCHGAP5 locus f) MCM3AP locus g) NRG3 locus h) FBN2 locus 162 i) PDE4D locus j) SPDYA locus k) LRRTM3/CTNNA3 locus Figure A2. LocusZoom regional Manhattan plots for the GWAS-nominated vincristine neuropathy-associated risk loci. LocusZoom regional Manhattan plots for GWAS nominated vincristine-induced peripheral neuropathy risk loci. The points represent the SNPs plotted with respect to their genomic region (x axis). The left y axis represents the corresponding log-adjusted p-values from the GWAS analysis, while the blue line (right y axis) depicts the recombination rate at the corresponding regionPlots were generated using LocusZoom (http://locuszoom.org/). 163 Figure A3. Summary of gene expression of GWAS-nominated genes across different tissues. Summary of the expression (eQTL) representation of the top GWAS genes based on GTEX v8.0 (visualized with FUMA: https://fuma.ctglab.nl/). 164 Variant Gene Effect Allele OR (95% CI) p-value rs12474420 SPDYA T 0.26 (0.15-0.44) 1.10x10-7 rs79802223 METTL8 G 0.18 (0.09-0.36) 3.78x10-8 rs12658429 PDE4D C 0.25 (0.14-0.43) 6.11x10-8 rs12656510 FBN2 T 0.37 (0.25-0.53) 5.39x10-8 rs200858088 ZFAND3 C 0.08 (0.03-0.23) 1.14x10-9 rs10961381 NFIB G 0.07 (0.02-0.24) 2.40x10-8 rs12235805 PAPPA A 0.21 (0.12-0.40) 4.58x10-8 rs17129858 VTI1A T 0.28 (0.18-0.45) 9.05x10-9 rs12253008 NRG3 T 0.16 (0.07-0.33) 3.01x10-8 rs10997459 LRRTM3 G 0.14 (0.07-0.32) 4.59x10-8 rs8006511 ARHGAP5 G 0.60 (0.50-0.72) 1.69x10-8 rs2268979 ACTN1 T 0.49 (0.38-0.65) 3.31x10-7 rs1815857 MCM3AP T 5.58 (2.85- 12.5) 4.85x10-8 Table A4. Sensitivity analysis for potential confounding by age in the discovery cohort. Abbreviations: OR=odds ratio. 165 Patient characteristics Full cohort (n=362) Age (years at cancer diagnosis, median [IQR]) 5.39 (3.00-10.6) Sex Male (%) 215 (59.4%) Female (%) 147 (40.6%) Tumour Type, count (%) Acute lymphoblastic leukemia 159 (43.9%) Hodgkin lymphoma 46 (12.7%) Neuroblastoma 26 (7.2%) Burkitt lymphoma 25 (6.9%) Wilm's Tumor 18 (4.9%) Ewing’s sarcoma 16 (4.4%) Rhabdomyosarcoma 13 (3.6%) Hepatoblastoma 11 (3.0%) Non-Hodgkin lymphoma 9 (2.5%) Lymphoblastic lymphoma 8 (2.2%) Medulloblastoma 7 (1.9%) Astrocytoma 4 (1.1%) Anaplastic Ependymoma 2 (0.6%) Retinoblastoma 2 (0.6%) Osteosarcoma 2 (0.6%) Retinoblastoma 2 (0.6%) Other tumour types 12 (3.3%) Genetic ancestry, count (%) European 231 (63.81%) American 41 (11.32%) South Asian 36 (9.95%) East Asian 25 (6.63%) Mixed Ancestry 20 (5.53%) African 10 (2.76%) Table A5. Patients clinical and treatment characteristics in replication cohort. Abbreviations: IQR=Inter-quartile range.
Thesis/Dissertation
eng
Medical Genetics
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Carleton, Bruce C.
Ross, Colin J.
Pharmacogenomic study of vincristine-induced peripheral neuropathy in patients with pediatric cancers
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