<p> Cancer encompasses a broad range of complex malignancies characterized by diverse sites of origin, genetic landscapes, and disease progressions. This diversity dictates the manner in which these cancer cases are clinically managed, as well as the overall prognosis. Despite these differences, most cancers exhibit universal hallmarks that contribute to tumor growth and cell survival. As such, these hallmarks are the focus of many research efforts and represent high priority targets for anticancer therapy. While some novel treatment regimens targeting these features have provided good outcomes, effective therapeutics for aggressive cancers are still needed. </p><p> To that end, I used patient- derived xenografts (PDX) of colorectal cancer (CRC) and an established cell line of advanced prostate cancer (CaP) to target oncogenic drivers, specifically mTOR and MEK, and altered metabolism for decreased tumor cell growth. My work defined genomic landscapes in CRC for which molecularly targeted agents (against MEK alone and in combination with mTOR) were most effective. My research also revealed the glycolytic nature of CaP which, when inhibited, upregulated autophagy. Combined inhibition of glycolysis and autophagy reduced CaP cell viability, thereby supporting autophagy’s role in cell survival during times of metabolic stress. </p><p> Chapter 1 provides an introduction on the hallmarks and history of cancer to frame the work described in Chapters 2 and 3. Chapter 2 presents the development of clinically relevant PDX models of CRC, and their sensitivity to targeted therapies. Chapter 3 describes the metabolic characteristics of CaP and the effects of inhibiting glycolysis. Chapter 4 contains unpublished data that interrogates the role of autophagy in CaP. Finally, chapter 5 presents conclusions from this work and future research directions.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10274924 |
| Date | 15 July 2017 |
| Creators | Burgenske, Danielle Marguerite |
| Publisher | Van Andel Research Institute |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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