The cause of ovarian cancer is unclear. We have suggested that inflammation may be involved. Ovulation, endometriosis, and talc use all promote inflammation, and all increase the risk of ovarian cancer; tubal ligation and hysterectomy prevent the ovaries from being exposed to inflammants, and reduce risk. Furthermore, inflammation entails DNA damage and repair, oxidative stress, and elevations in prostaglandins and cytokines, all of which may be mutagenic. Building on our track record of success with conducting ovarian cancer case-control studies, we propose a population-based study to examine the role of inflammation in the risk for ovarian cancer. We will enroll 900 women with incident ovarian cancer (cases) from hospitals in Western Pennsylvania, Northern Ohio, and Western New York. One thousand eight hundred controls, ascertained via random digit dialing, will be frequency matched to cases on age, race, and residence. Using in-person standardized interviews and blood draws, we propose to: 1) evaluate whether non-steroidal anti-inflammatory drugs (NSAIDs) protect against ovarian cancer; 2) compare in cases and controls allelic variants in inflammatory and antinflammatory cytokines and growth factors including IL-1, TNF-a, IL-10, IGF-1 and TGF-b; 3) evaluate whether markers of past PID, i.e. higher antibody titers to chlamydia and its related heat shock protein (HSP)-60, relate to ovarian cancer; 4) in a secondary aim, explore whether allelic variants in the NSAID metabolizing enzymes CYP2C9 and UGT1A6 interact with NSAID use to reduce the risk of ovarian cancer. Exploring the relationships among inflammatory predisposition, inflammatory exposures, anti-inflammatory medications, and ovarian cancer represents a novel avenue of research. In particular, NSAID use may prove to be a potentially important chemopreventative for this often-fatal disease.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA095023-01A1
Application #
6611598
Study Section
Epidemiology and Disease Control Subcommittee 2 (EDC)
Program Officer
Arena, Jose Fernando
Project Start
2003-05-12
Project End
2008-04-30
Budget Start
2003-05-12
Budget End
2004-04-30
Support Year
1
Fiscal Year
2003
Total Cost
$516,671
Indirect Cost
Name
University of Pittsburgh
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Block, Matthew S; Vierkant, Robert A; Rambau, Peter F et al. (2018) MyD88 and TLR4 Expression in Epithelial Ovarian Cancer. Mayo Clin Proc 93:307-320
Harris, Holly R; Babic, Ana; Webb, Penelope M et al. (2018) Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev 27:174-182
Lu, Yingchang; Beeghly-Fadiel, Alicia; Wu, Lang et al. (2018) A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Res 78:5419-5430
Minlikeeva, Albina N; Moysich, Kirsten B; Mayor, Paul C et al. (2018) Anthropometric characteristics and ovarian cancer risk and survival. Cancer Causes Control 29:201-212
Peres, Lauren C; Risch, Harvey; Terry, Kathryn L et al. (2018) Racial/ethnic differences in the epidemiology of ovarian cancer: a pooled analysis of 12 case-control studies. Int J Epidemiol 47:460-472
Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun et al. (2018) Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence. Am J Epidemiol 187:366-377
Ong, Jue-Sheng; Hwang, Liang-Dar; Cuellar-Partida, Gabriel et al. (2018) Assessment of moderate coffee consumption and risk of epithelial ovarian cancer: a Mendelian randomization study. Int J Epidemiol 47:450-459
Glubb, Dylan M; Johnatty, Sharon E; Quinn, Michael C J et al. (2017) Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci. Oncotarget 8:64670-64684
Reid, Brett M; Permuth, Jennifer B; Chen, Y Ann et al. (2017) Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 26:116-125
Minlikeeva, Albina N; Freudenheim, Jo L; Eng, Kevin H et al. (2017) History of Comorbidities and Survival of Ovarian Cancer Patients, Results from the Ovarian Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev 26:1470-1473

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