<p> Genome sequencing technology has enabled the identification of genetic variants that are linked with cancer phenotypes, whether these are somatically acquired mutations or common inherited single nucleotide polymorphisms (SNPs). Whereas coding variants have been reported to disrupt protein function to promote cancer, most variants map to noncoding regions, with no known function. Recently, much effort has gone into annotating the human noncoding genome, enabling the characterization of the functional basis of noncoding SNPs. As an example of functional impact, breast cancer (BrCa) risk-associated SNPs can alter transcription factor binding at distal enhancers. </p><p> Identifying the targets of risk SNPs remains a challenge. One reason for this is the complex three-dimensional structure of the genome. Local chromatin openness correlates with chromatin activity, and sites of chromatin that are open concurrently across multiple cell types indicates a functional relationship between them. We mapped BrCa risk-associated SNPs to regions of open chromatin to predict the most likely functional risk SNPs. Then, we predicted their targets by identifying the gene promoters whose openness correlated with these risk regions. Further, we validated a gene which is a novel therapeutic target and relevant in breast cancer biology. </p><p> In addition to SNPs, noncoding somatic mutations are also predicted to play a role in cancer. In 2012, driver mutations were reported in the telomerase gene promoter, hinting at the relevance of mutations in regulatory elements. This is particularly true when considering oncogenes whose elevated expression in certain cancers is not attributable to coding mutations or copy number amplification. We reveal the enrichment and functional nature of somatic mutations mapping to enhancers that regulate the estrogen receptor gene, which is known to drive over two-thirds of breast cancer. </p><p> Attributing function to noncoding SNPs and mutations associated with cancer risk and progression is a growing necessity in this era of whole-genome cancer biology. This thesis demonstrates a methodology to identify the functional consequence and gene targets of significantly mutated or risk variant-bearing enhancer sets to narrow the gap between known and unknown risk factors in BrCa.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10144817 |
| Date | 18 August 2016 |
| Creators | Desai, Kinjal |
| Publisher | Dartmouth College |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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