Detecting adaptive regulatory evolution in cancer using copy number alterations and a generalized sign test
Abstract/Contents
- Abstract
- Gene expression changes accompany somatic mutations in cancer, often as their direct consequence. Whether such regulatory mutations increase in frequency reflects the cellular fitness of the associated expression changes. Identifying which regulatory mutations are present in human tumors, as well as their gene targets, is needed to improve our understanding of evolution in cancer and prioritize targets for treatment. After introducing the research question, I describe in Chapter 2 an approach for mapping genomic regions where copy number influences gene expression ("copy number expression quantitative trait loci"; cn-eQTLs) and report widespread associations. In Chapter 3, I introduce the cancer association toolkit software, casskit, written to enable large-scale cancer association studies. casskit wraps performant data science libraries and offers federated data structures and model components for commonly encountered cancer association tasks. In Chapter 4, I introduce the population sign test (PopST), a generalization of QTL-based sign tests for neutral evolution. PopST pools inference across independent evolutionary trajectories, while incorporating covariates and propagating uncertainty from QTL mapping. In chapter 5, I present results from applying PopST to cn-eQTLs mapped in a large, pan-cancer cohort of tumor samples to identify adaptive regulatory evolution. Across cancers, copy number alterations systematically reinforce expression changes in cancer genes and genes involved in proliferation. I highlight how PopST can detect subtype-specific selection and selection at the level of protein complexes, where I find coordinated up-regulation of spindle assembly checkpoint components. Finally, I conclude by discussing how regulatory evolution can provide a framework for interpreting cancerassociated genetic variants through their downstream effects on gene expression.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Silvers, Thomas Reed |
|---|---|
| Degree supervisor | Fraser, Hunter B |
| Degree supervisor | Jarosz, Daniel |
| Thesis advisor | Fraser, Hunter B |
| Thesis advisor | Jarosz, Daniel |
| Thesis advisor | Petrov, Dmitri Alex, 1969- |
| Degree committee member | Petrov, Dmitri Alex, 1969- |
| Associated with | Stanford University, Cancer Biology Program |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Thomas Silvers. |
|---|---|
| Note | Submitted to the Cancer Biology Program. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/mv649tg2937 |
Access conditions
- Copyright
- © 2022 by Thomas Reed Silvers
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