Despite decades of effort, the mechanistic underpinnings of many cancers remain unsolved It has increasingly become appreciated that cancers can be more readily classified by their transcriptional identities rather than by genomics alone. A fuller understanding of the mechanistic connections between the aberrant genomics leading to the transcriptional dysregulation of tumors is key to both improving our knowledge of cancer biology as well as developing more precise and effective therapeutics. This thesis explores the development and application of a network based multi-omic master regulator framework designed to elucidate these pathways.
In Chapter 2 we apply this analysis across 20 tumor types from the Cancer Genome Atlas and in doing so identify 407 key master regulators responsible for canalizing a high percentage of the driver genetics present across these samples. Further evaluation of these key regulators revealed a highly modular structure, indicating that the regulators work in coordinated groups to implement a variety of key cancer hallmarks. Genetic and pharmacological validation assays confirmed the predicted interactions and biological phenotypes.
Chapter 3 focuses on the application of this analytical framework specifically on gastroesophageal tumors. Using a more fine-grained approach we find 15 distinct subtypes across a cohort of these heterogenous tumors. These subtypes align well with previously identified features of these cancers but also reveal novel genomic associations and key master regulators that can serve as potential avenues for therapeutic treatment.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-q71y-cp03 |
| Date | January 2021 |
| Creators | Jones, Sunny |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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