Prostate cancer (PCa) has the highest incidence of any cancer in North America, yet little is known about the risk factors or underlying molecular defects that cause the disease. One emerging hypothesis suggests that chronic inflammation in the prostate plays a role in the development and progression of PCa. Inflammation may foster the development of cancer because: 1) cells at the site of inflammation are exposed to free radicals and other genotoxic compounds that directly damage DNA; 2) inflammation is associated with increased cellular proliferation, enhancing the probability that cells may acquire new mutations; and 3) inflammatory cells release cytokines that inhibit apoptosis, allowing DNA-damaged cells to survive and proliferate. Ultimately, inflammation may augment PCa risk by disrupting the normal balance between proliferation and apoptosis. To investigate the role of inflammation in relation to PCa, we propose to evaluate the risk associated with variant alleles of inflammatory pathway-related genes. Specifically, we propose an association study of PCa in relation to single nucleotide polymorphisms (SNPs) and haplotypes in the following genes: 1) IL-6 cytokine, its receptor, and genes of the downstream signaling pathways of Jak/STAT and PI3K/Akt; 2) CXCL12/SDF-1 cytokine and its receptor, CXCR4; and, 3) Cox-2 TNF-a, NF-?B, IL-8 and IL-10. The proposed population-based case-control study will involve genotyping 1,457 histologically confirmed PCa cases identified through the Puget Sound SEER registry and 1,352 age frequency-matched controls with no prior history of PCa. Study participants were 40-74 years old in1993-1996 or 2002-2005 when they were recruited for one of two prior studies that involved similar in-person interviews and blood draws. Information on demographic factors, medical history, PCa screening history (PSA and DRE), family cancer history, lifetime smoking and alcohol consumption, and lifetime sexual history was recorded. DNA samples (n=2,809) will be genotyped at NHGRI using the Applied Biosystems SNPlex(tm) system. Unconditional logistic regression analysis will be used to estimate odds ratios and 95% confidence intervals associated with the above genetic polymorphisms. Clinical data (e.g., Gleason score, stage of disease, diagnostic PSA level) will be used to assess whether PCa-genotype associations differ according to disease aggressiveness. Results from this study may provide novel information on how the inflammatory pathway may affect risk of PCa and may provide insights leading to new prevention strategies. This year alone, a third of all cancers diagnosed in men will be prostate adenocarcinoma, leading to 218,890 new cases. Results from the proposed study may provide insight into the underlying biology of this complex disease and suggest useful avenues for future prevention studies, such as strategies aimed at decreasing inflammation. Because this study is population-based, it will be possible to estimate the impact of any genetic alleles found to be related to prostate cancer risk in the population. The greatest potential impact of this study would result from identification of genetic alleles able to detect men at higher risk of developing clinically aggressive prostate cancer, who might benefit most from increased surveillance or more aggressive treatment. ? ? ?
