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Diffuse large B-cell lymphoma (DLBCL) is a very heterogenous disease that has historically been divided into two subtypes driven by distinct molecular mechanisms. The activated B-cell (ABC) subtype of DLBCL has the worst overall survival and is characterized by activation of the NF-κB signaling pathway. Although many genetic alterations have been identified in DLBCL, there remain cases with few or no known genetic drivers. This suggests that there are still novel drivers of DLBCL yet to be discovered. In this thesis I aimed to leverage whole genome sequencing data to identify novel regions of the genome that were recurrently mutated, with a specific focus on non-coding regions. Through this analysis we identified numerous novel putative driver mutations within the non-coding genome. One of the most highly recurrently mutated regions was in the 3′ untranslated region (UTR) of the NFKBIZ gene. Amplifications of this gene have been previously discovered in ABC DLBCL and this gene is known to activate NF-κB signaling. Therefore, we hypothesized that these 3′ UTR mutations were acting as drivers in DLBCL. The remaining portion of this thesis is focused on the functional characterization of NFKBIZ 3′ UTR mutations and how they drive DLBCL and contribute to treatment resistance. To this end, I induced NFKBIZ 3′ UTR mutations into DLBCL cell lines and determined that they cause both elevated mRNA and protein expression. These mutations conferred a selective growth advantage to DLBCL cell lines both in vitro and in vivo and overexpression of NFKBIZ in primary germinal center B-cells also provided cells a growth advantage. Lastly, I found that NFKBIZ-mutant cell lines were more resistant to a selection of targeted therapeutics (ibrutinib, idelalisib and masitinib). Taken together, this thesis highlights the importance of surveying the entire cancer genome, including non-coding regions, when searching for novel drivers. I demonstrated that mutations in the 3′ UTR of a gene can act as driver mutations conferring cell growth advantages and treatment resistance. This work also implicates NFKBIZ 3′ UTR mutations as potentially useful biomarkers for predicting treatment response and informing on the most effective treatment options for patients.
