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Clinical Implications of inter-tumour, intra-tumour, and tumour microenvironment heterogeneity in B-cell lymphomas

University of British Columbia

B-cell lymphomas are lymphoid neoplasms derived from mature B lymphocytes at various stages of B-cell development. Advances in sequencing have contributed to decoding the genomic landscapes underlying many subtypes of B-cell lymphomas. However, it remains unclear why some B-cell lymphoma patients suffer from disease progression. A major factor contributing to disease progression is tumour heterogeneity, a consequence of branched evolutionary processes, and microenvironment heterogeneity leading to variation in the composition and properties of non-malignant cells infiltrating and surrounding the cancer. A thorough characterization of these forms of diversity in B-cell lymphomas and their association with disease progression has not been undertaken. As such, the overarching hypothesis of this thesis is that uncharacterized inter-tumour, intra-tumour, and tumour microenvironment heterogeneity impacts disease progression in B-cell lymphomas. In particular, this thesis is focused on studying these types of heterogeneity in three subtypes of B-cell lymphomas and their implications on disease progression. First, I explored inter-tumour heterogeneity in primary specimens of diffuse large B-cell lymphoma patients. I identified novel RCOR1 deletions and their corresponding transcriptional signature in a subset of patients that stratified patients into good and poor outcome following first-line treatment. Secondly, I explored intra-tumour heterogeneity in histologically transformed and early progressed follicular lymphoma patients using serial samples of their primary and transformed/progressed specimens. Through the inference of clonal dynamic patterns, I revealed divergent evolution patterns and identified novel genes underlying these distinct clinical end points. Thirdly, I explored tumour microenvironment (TME) heterogeneity in classical Hodgkin lymphoma relapse patients through serial sampling of primary pretreatment and relapse specimens. I demonstrated how specific TME dynamic patterns can inform on treatment failure. Moreover, I derived a novel, clinically applicable prognostic model (RHL30), based on the TME composition at relapse that predicts response to second-line treatment. Collectively, the work in this thesis constitutes a step forward in our characterization of tumour and microenvironment heterogeneity in B-cell lymphomas and its association with disease progression. The results presented here will aid in the determination of precise therapeutic approaches for individual lymphoma patients.

Text

2018-03-31

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/61022

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/