Prostate cancer, one of the most common cancers among men, can be relatively harmless or extremely aggressive. The most widely used biomarker for the disease, the PSA test, is not independently diagnostic or prognostic of prostate cancer. One of the main challenges of prostate cancer research is to find reliable and effective prognostic biomarkers that will predict cancer recurrence following surgery, in order to identify clinically significant prostate cancer and improve management of the disease. In recent years, microRNAs (miRNAs) have been identified as master regulators of cellular processes, and dysregulated miRNAs have been associated with cancer development and progression. The intent of my PhD research program was to uncover novel miRNAs that contribute to prostate cancer pathogenesis in order to assess their potential as predictors of clinical progression. By analyzing a large cohort of primary prostate cancer samples, we have discovered that microRNA-221 (miR-221) is associated with metastasis and biochemical recurrence in prostate cancer, and is downregulated in TMPRSS2:ERG fusion gene- positive tumors. In addition, we have determined that microRNA-182 (miR-182) is overexpressed in prostate cancer and is associated with increased metastasis and clinical progression by targeting a tumors suppressor Forkhead box O1 (FOXO1). Overall, this work introduces novel candidate miRNA genes and downstream targets that are aberrantly expressed in more aggressive prostate cancer, and presents a potentially significant role for miRNAs as prognostic biomarkers that are associated with clinical progression, and perhaps aids in defining how miRNAs might one day serve as anti-cancer therapeutic agents.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OTU.1807/34019 |
Date | 12 December 2012 |
Creators | Gordanpour, Aida |
Contributors | Seth, Arun |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | en_ca |
Detected Language | English |
Type | Thesis |
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