Cancer is a set of complex genetic diseases driven by diverse genomic alterations. The genomic study of cancer has enabled the discovery of novel, targetable events in almost all cancer types and in turn, has led to the development of new, targeted cancer therapies benefiting patients; however, the recent explosion of genomic datasets has also resulted in huge lists of new oncogenic factors of unknown biological relevance, and uncertainty over how best to use the data appropriately to influence patient care. Some of the most pressing questions surround the use of statistical methods to identify actionable genomic alterations in cancer and the identification of driving oncogenes in the context of the genomic evolution of cancer cells, undergone before, during, and after prolonged treatment regimens.
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/11181067 |
| Date | 18 October 2013 |
| Creators | Liao, Rachel Grace |
| Contributors | Meyerson, Matthew Langer |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Rights | open |
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