MicroRNA processing and binding site polymorphisms are not replicated in the Ovarian Cancer Association Consortium

Jennifer Permuth-Wey, Zhihua Chen, Ya Yu Tsai, Hui Yi Lin, Y. Ann Chen, Jill Barnholtz-Sloan, Michael J. Birrer, Stephen J. Chanock, Daniel W. Cramer, Julie M. Cunningham, David Fenstermacher, Brooke L. Fridley, Montserrat Garcia-Closas, Simon A. Gayther, Aleksandra Gentry-Maharaj, Jesus Gonzalez-Bosquet, Edwin Iversen, Heather Jim, John McLaughlin, Usha MenonSteven A. Narod, Catherine M. Phelan, Susan J. Ramus, Harvey Risch, Honglin Song, Rebecca Sutphen, Kathryn L. Terry, Jonathan Tyrer, Robert A. Vierkant, Nicolas Wentzensen, Johnathan M. Lancaster, Jin Q. Cheng, Andrew Berchuck, Paul D.P. Pharoah, Joellen M. Schildkraut, Ellen L. Goode, Thomas A. Sellers

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Background: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies. Methods: We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset. Results: After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk. Conclusions: Commonvariants in these evaluated genesdonotseemto be strongly associatedwithEOCrisk. Impact: This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.

Original languageEnglish (US)
Pages (from-to)1793-1797
Number of pages5
JournalCancer Epidemiology Biomarkers and Prevention
Issue number8
StatePublished - Aug 2011

ASJC Scopus subject areas

  • General Medicine


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