Integrating Genomic and Biological Understandings of Disease to Improve Patient Outcome in Mature B Cell Lymphoma

All cancers begin as normal cells that have acquired genetic alterations allowing them to evade growth control mechanisms and proliferate uncontrollably. A better delineation of the genetic events that drive cancer and their biological consequences has the potential to enable the discovery of improved diagnostic and prognostic biomarkers and the identification of new therapeutic possibilities.Lymphomas comprise nearly 50 distinct malignancies arising from immune cells. These cancers are recognized by the current standard classification system organized by the World Health Organization. Outcomes for these collectively common diseases have not improved in several decades. These lymphomas are classified primarily based on lineage. There are three fundamental problems that must be addressed in order to better connect genetic alterations to new treatments in any genetically heterogeneous disease such as mature B cell lymphoma. First, the most common drivers of disease must be determined through a systematic genetic analysis of patient tumors. Second, we need to better understand the interplay between the biological context of lineage and these genetic alterations. Finally, we need to identify the specific biological aspects of the genetic alterations that can be systematically targeted with drugs. In this dissertation, I present my work addressing these critical questions with the overall goal of converting our genomic and biological understanding of disease into actionable improvements in patient outcome. First, I focus on defining and characterizing the common genetic drivers of ocular adnexa marginal zone lymphoma (OAMZL), a rare but sometimes deadly lymphoma that has not previously been genomically characterized systematically. In addition to finding alterations in genes previously implicated as drivers in other lymphomas, including TBL1XR1, CREBBP, and TNFAIP3, we identified CABIN1 as a novel tumor suppressor gene that is recurrently mutated and deleted. Experimental validation of CABIN1 as a driver in OAMZL indicates that its deletion can lead to uncontrolled cell-growth signaling in the B cell receptor and NFAT pathways that could be targeted with new drugs. This study thus provides an unbiased identification of genetically altered genes that may play a role in the development of OAMZL and serve as potential therapeutic targets in future drug development. Next, it is important to appreciate that genetic alterations driving cancer do not exert their effects in isolation. The lineage or normal cell of origin of the cancer provides critical context for understanding many aspects of cancer, including favored growth mechanisms and inherent gene activation patterns. Here, I describe how we utilized integrative genomic approaches to identify and characterize the normal cell of origin of diffuse large B cell lymphoma (DLBCL). We utilized a combination of single cell RNA sequencing to define all normal cell types that exist in lymphoid tissues and RNA sequencing on bulk lymphoma tumor samples to characterize the expression profiles of these tumors. We further developed a computational approach that allows us to identify the single cell population that most closely resembles RNA sequencing data from bulk tumors. Using this approach, we identified candidate normal immune cell populations that most closely resemble the bulk tumor sample for different DLBCL subtypes. This work provides important clues to the underlying biology of the specific normal cell types that shape the biological consequences of various genomic alterations in the corresponding cancers. Finally, the eventual goal of all basic cancer research is to translate our understanding of the genomic and biological underpinnings of cancer into clinical advances that improve overall patient survival. In the final section of this dissertation, I develop a framework to integrate different functional genomic approaches to identify novel therapeutic opportunities for DLBCL patients with poor outcomes. First, I describe how we identified a group of DLBCL patients that do not respond to current standard therapy. We then examined the spectrum of efficacy for 152 FDA-approved cancer drugs in preclinical models of DLBCL. Taken together, these data allowed us to identify a new combination therapy targeting the genomic features that are associated with low rates of response to standard therapy. Additional in vitro and in vivo experiments validated the efficacy of this proposed novel combination therapy. Overall, this dissertation contributes to our understanding of lymphoma genetics and presents a scientific framework for translating this understanding into clinical applications for improving patient outcomes. The methods and approaches described in this dissertation are broadly applicable to other types of cancer and could be used to improve clinical outcomes for other cancer patients.