Barriers and Facilitators to Adoption of Genomic Services for Colorectal Care within the Veterans Health Administration.

We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC), but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines.

Characterizing Genetic Drivers of Lymphoma through High-Throughput Sequencing

The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution.

In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome.

In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma.

In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study.

In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.

Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.