Abstract
Uveal Melanoma (UM) is a highly aggressive and frequently fatal cancer of the eye. While only 2-4% of patients will have detectable metastasis at diagnosis, up to 50% of patients later develop metastatic disease to the liver even after treatment of the primary tumor. UM can be separated into two sub-groups, low risk class 1 and high risk class 2, based on gene expression profiling. Class 1 tumors obtain a mutation in either EIF1AX or SF3B1, while class 2 tumors acquire bi-allelic loss of BAP1 and loss of heterozygosity of chromosome 3. Molecular mechanisms that aid in this directed evolution of UM down a distinct trajectory remain undetermined. Multi-omic approaches at various points of the disease are needed to advance precision medicine, in order to gain a complete picture of the molecular framework of these tumors. Here we describe how the genomic landscape of UM is, on one hand, influenced by genetic ancestry and, on the other hand, drives tumor evolution along one of three trajectories that determine patient outcome.
This work presents the results of three studies investigating the impact of genetic ancestry on UM, genomic evolution in the metastatic setting, and non-coding RNA transcriptome’s association with early evolutionary trajectories in UM. The findings suggest that an underlying ancestral genetic structure may influence which prognostically significant evolutionary trajectory an individual’s tumor may follow. However, once in the metastatic setting, there is a pattern of undirected evolution allowing for novel driver mutations to arise. Tumor specific alterations in the non-coding transcriptome may allow for the development of new prognostic biomarkers in UM. This dissertation provides an arc of novel genetic and genomic findings in UM that provide new insights into UM evolution, from the patients’ underlying genetic ancestry to the late stages of tumor evolution. The dissertation concludes with a synthesis of these findings into the larger body of knowledge regarding UM, and how this work suggests future directions and how it may aid in patient management and prognosis.