Ovarian cancer causes more deaths each year among North American women than any other gynecologic cancer. The etiology is poorly understood. Although highly penetrant mutations in BRCA1 and BRCA2 are known to significantly increase ovarian cancer risk, such mutations are rare in the population and collectively they account for only 12-15% of cases. Recent evidence suggests that subtle (non-truncating) but more common genetic variants (i.e. single nucleotide polymorphisms with greater than 5% population frequency) confer more moderate increased risks of cancer and are likely to be involved in a significant proportion of cases. However, most studies conducted to date have tended to rely extensively on candidate gene approaches. Because current understanding of the pathobiology of ovarian cancer is limited, selection of appropriate candidates is challenging and efforts to date have proven largely unsuccessful. Our hypothesis is that ovarian cancer susceptibility genes exist but that the most fruitful strategy for their identification is a genome-wide analysis. Recent methodological and technical developments make this possible and feasible. Our approach will be to combine the resources and expertise of four large case control studies of ovarian cancer that have collected genomic DMA and relevant risk factors on participants. Phase I entails the use of 366,722 haplotype-tagging (ht) SNPs to screen the entire genome for potential loci of interest using 367 cases with a family history of ovarian cancer and 479 matched controls. Phase II seeks to validate and refine these results among 303 population-based cases and 303 matched controls using the 13,000 SNPs most strongly associated with risk. In Phase III we will assess the reproducibility and generalizability of our results among 3072 cases and 3072 matched controls, using the top 7309 SNPs from Phase II. Success in this endeavor will not only allow identification of women at risk for ovarian cancer, but will elucidate genes involved in the pathogenesis of this deadly malignancy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA114343-05
Application #
8025998
Study Section
Special Emphasis Panel (ZRG1-HOP-W (02))
Program Officer
Gillanders, Elizabeth
Project Start
2007-03-15
Project End
2014-02-28
Budget Start
2011-03-01
Budget End
2014-02-28
Support Year
5
Fiscal Year
2011
Total Cost
$1,078,602
Indirect Cost
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
(2016) Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus. Nat Commun 7:12675
French, Juliet D; Johnatty, Sharon E; Lu, Yi et al. (2016) Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer. Oncotarget 7:6353-68
(2016) No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer. Gynecol Oncol 141:386-401
Cuellar-Partida, Gabriel; Lu, Yi; Dixon, Suzanne C et al. (2016) Assessing the genetic architecture of epithelial ovarian cancer histological subtypes. Hum Genet 135:741-56
Lee, Alice W; Templeman, Claire; Stram, Douglas A et al. (2016) Evidence of a genetic link between endometriosis and ovarian cancer. Fertil Steril 105:35-43.e1-10
Richards, Edward J; Zhang, Gu; Li, Zhu-Peng et al. (2015) Long non-coding RNAs (LncRNA) regulated by transforming growth factor (TGF) β: LncRNA-hit-mediated TGFβ-induced epithelial to mesenchymal transition in mammary epithelia. J Biol Chem 290:6857-67
Jim, Heather S L; Lin, Hui-Yi; Tyrer, Jonathan P et al. (2015) Common Genetic Variation in Circadian Rhythm Genes and Risk of Epithelial Ovarian Cancer (EOC). J Genet Genome Res 2:
Richards, Edward J; Permuth-Wey, Jennifer; Li, Yajuan et al. (2015) A functional variant in HOXA11-AS, a novel long non-coding RNA, inhibits the oncogenic phenotype of epithelial ovarian cancer. Oncotarget 6:34745-57
Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan et al. (2015) Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk. Cancer Epidemiol Biomarkers Prev 24:1574-84
Lu, Yi; Cuellar-Partida, Gabriel; Painter, Jodie N et al. (2015) Shared genetics underlying epidemiological association between endometriosis and ovarian cancer. Hum Mol Genet 24:5955-64

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