4.5 Article

MicroRNA Processing and Binding Site Polymorphisms Are Not Replicated in the Ovarian Cancer Association Consortium

Journal

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
Volume 20, Issue 8, Pages 1793-1797

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-11-0397

Keywords

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Funding

  1. Mayo Foundation
  2. American Cancer Society [CRTG-00-196-01-CCE]
  3. Advanced Cancer Detection Center
  4. Department of Defense [DAMD-17-98-1-8659]
  5. Canadian Cancer Society
  6. NIH [R01-CA-63682, R01-CA-63678]
  7. National Cancer Institute [P30-CA-15083]
  8. NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics
  9. Center for Cancer Research
  10. Cancer Research UK
  11. Eve Appeal
  12. OAK Foundation
  13. Department of Health
  14. [R01-CA-114343]
  15. [R01-CA114343-S1]
  16. [R01-CA-122443]
  17. [P50-CA-136393]
  18. [R01-CA-76016]
  19. [R01-CA-106414]
  20. [CA-54419]
  21. [P50 CA105009]
  22. MRC [G0801875] Funding Source: UKRI
  23. Cancer Research UK
  24. The Francis Crick Institute [10124] Funding Source: researchfish
  25. Medical Research Council [G0801875] Funding Source: researchfish

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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: Common variants in these evaluated genes do not seem to be strongly associated with EOC risk. 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. Cancer Epidemiol Biomarkers Prev; 20(8); 1793-7. (C)2011 AACR.

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