Tumor Biology

, Volume 35, Issue 6, pp 5797–5804 | Cite as

The effect of RAD51 135 G>C and XRCC2 G>A (rs3218536) polymorphisms on ovarian cancer risk among Caucasians: a meta-analysis

  • Shujing Shi
  • Lingyan Qin
  • Mengqiu Tian
  • Mao Xie
  • Xiaoxue Li
  • Chenglin Qi
  • Xiang Yi
Research Article


Genetic polymorphisms of RAD51 135 G>C and XRCC2 G>A (rs3218536) have been reported to change the risk of ovarian cancer, but the results are controversial. To get a more precise result, a meta-analysis was performed. A comprehensive literature search in PubMed, Excerpta Medica Database, and China National Knowledge Infrastructure was carried out to get case–control studies published up to November 2013. The pooled odds ratio (OR) and its corresponding 95 % confidence interval (CI) were conducted to estimate the effect of RAD51 135 G>C and XRCC2 G>A (rs3218536) polymorphisms on ovarian cancer risk. A total of 13 independent case–control studies with 5,927 cases and 10,303 controls were included in this meta-analysis. There was no significant association between RAD51 135 G>C polymorphism and risk of ovarian cancer. However, the result of total studies indicated the XRCC2 G>A (rs3218536) polymorphism could reduce the risk of ovarian cancer (heterozygote model AG vs. GG: OR = 0.877, 95 % CI = 0.770–0.999, P = 0.048; dominant model AA/AG vs. GG: OR = 0.864, 95 % CI = 0.763–0.979, P = 0.022). The result was still significant after Hardy–Weinberg equilibrium-violating studies were excluded (allele contrast A vs. G: OR = 0.836, 95 % CI = 0.74–0.943, P = 0.004; homozygote model AA vs. GG: OR = 0.562, 95 % CI = 0.317–0.994, P = 0.048; heterozygote model AG vs. GG: OR = 0.859, 95 % CI = 0.753–0.98, P = 0.023; dominant model AA/AG vs. GG: OR = 0.842, 95 % CI = 0.74–0.958, P = 0.009). In the stratified analysis by ethnicity, significantly reduced risk was observed among Caucasians in dominant model (AA/AG vs. GG: OR = 0.867, 95 % CI = 0.764–0.984, P = 0.027). No significant association was found between the RAD51 135G>C polymorphism and the risk of ovarian cancer. Interestingly, XRCC2 G>A (rs3218536) polymorphism might reduce the risk of ovarian cancer. Larger-scale and well-designed studies are needed to further clarify the association.


RAD51 XRCC2 Polymorphism Ovarian cancer Meta-analysis 



We would like to thank the students who give us help.

Conflicts of interest



  1. 1.
    Romero I, Bast Jr RC. Minireview: human ovarian cancer: biology, current management, and paths to personalizing therapy. Endocrinology. 2012;153(4):1593–602.PubMedCentralCrossRefPubMedGoogle Scholar
  2. 2.
    Brekelmans CT. Risk factors and risk reduction of breast and ovarian cancer. Curr Opin Obstet Gynecol. 2003;15(1):63–8.CrossRefPubMedGoogle Scholar
  3. 3.
    Murdoch WJ, Martinchick JF. Oxidative damage to DNA of ovarian surface epithelial cells affected by ovulation: carcinogenic implication and chemoprevention. Exp Biol Med (Maywood). 2004;229(6):546–52.Google Scholar
  4. 4.
    Fathalla MF. Incessant ovulation—a factor in ovarian neoplasia? Lancet. 1971;2(7716):163.CrossRefPubMedGoogle Scholar
  5. 5.
    Godwin AK et al. Spontaneous transformation of rat ovarian surface epithelial cells: association with cytogenetic changes and implications of repeated ovulation in the etiology of ovarian cancer. J Natl Cancer Inst. 1992;84(8):592–601.CrossRefPubMedGoogle Scholar
  6. 6.
    Scully C, Field JK, Tanzawa H. Genetic aberrations in oral or head and neck squamous cell carcinoma 2: chromosomal aberrations. Oral Oncol. 2000;36(4):311–27.CrossRefPubMedGoogle Scholar
  7. 7.
    Thacker J. A surfeit of RAD51-like genes? Trends Genet. 1999;15(5):166–8.CrossRefPubMedGoogle Scholar
  8. 8.
    Thacker J. The RAD51 gene family, genetic instability and cancer. Cancer Lett. 2005;219(2):125–35.CrossRefPubMedGoogle Scholar
  9. 9.
    Tambini CE et al. The importance of XRCC2 in RAD51-related DNA damage repair. DNA Repair (Amst). 2010;9(5):517–25.CrossRefGoogle Scholar
  10. 10.
    Baumann P, West SC. Role of the human RAD51 protein in homologous recombination and double-stranded-break repair. Trends Biochem Sci. 1998;23(7):247–51.CrossRefPubMedGoogle Scholar
  11. 11.
    Shinohara A et al. Cloning of human, mouse and fission yeast recombination genes homologous to RAD51 and recA. Nat Genet. 1993;4(3):239–43.CrossRefPubMedGoogle Scholar
  12. 12.
    Hasselbach L et al. Characterisation of the promoter region of the human DNA-repair gene Rad51. Eur J Gynaecol Oncol. 2005;26(6):589–98.PubMedGoogle Scholar
  13. 13.
    Thacker J, Zdzienicka MZ. The XRCC genes: expanding roles in DNA double-strand break repair. DNA Repair (Amst). 2004;3(8–9):1081–90.CrossRefGoogle Scholar
  14. 14.
    Lin WY et al. A role for XRCC2 gene polymorphisms in breast cancer risk and survival. J Med Genet. 2011;48(7):477–84.PubMedCentralCrossRefPubMedGoogle Scholar
  15. 15.
    Perez LO et al. XRCC2 R188H (rs3218536), XRCC3 T241M (rs861539) and R243H (rs77381814) single nucleotide polymorphisms in cervical cancer risk. Pathol Oncol Res. 2013;19(3):553–8.CrossRefPubMedGoogle Scholar
  16. 16.
    Benhamou S et al. DNA repair gene XRCC2 and XRCC3 polymorphisms and susceptibility to cancers of the upper aerodigestive tract. Int J Cancer. 2004;112(5):901–4.CrossRefPubMedGoogle Scholar
  17. 17.
    Jiao L et al. XRCC2 and XRCC3 gene polymorphism and risk of pancreatic cancer. Am J Gastroenterol. 2008;103(2):360–7.PubMedCentralCrossRefPubMedGoogle Scholar
  18. 18.
    Auranen A et al. Polymorphisms in DNA repair genes and epithelial ovarian cancer risk. Int J Cancer. 2005;117(4):611–8.CrossRefPubMedGoogle Scholar
  19. 19.
    Jakubowska A et al. The RAD51 135 G>C polymorphism modifies breast cancer and ovarian cancer risk in Polish BRCA1 mutation carriers. Cancer Epidemiol Biomarkers Prev. 2007;16(2):270–5.CrossRefPubMedGoogle Scholar
  20. 20.
    Webb PM et al. Double-strand break repair gene polymorphisms and risk of breast or ovarian cancer. Cancer Epidemiol Biomarkers Prev. 2005;14(2):319–23.CrossRefPubMedGoogle Scholar
  21. 21.
    Beesley J et al. Association between single-nucleotide polymorphisms in hormone metabolism and DNA repair genes and epithelial ovarian cancer: results from two Australian studies and an additional validation set. Cancer Epidemiol Biomarkers Prev. 2007;16(12):2557–65.PubMedCentralCrossRefPubMedGoogle Scholar
  22. 22.
    Mohamed FZ et al. Role of DNA repair and cell cycle control genes in ovarian cancer susceptibility. Mol Biol Rep. 2013;40(5):3757–68.CrossRefPubMedGoogle Scholar
  23. 23.
    Jakubowska A et al. BRCA1-associated breast and ovarian cancer risks in Poland: no association with commonly studied polymorphisms. Breast Cancer Res Treat. 2010;119(1):201–11.CrossRefPubMedGoogle Scholar
  24. 24.
    Wang WW et al. A single nucleotide polymorphism in the 5′ untranslated region of RAD51 and risk of cancer among BRCA1/2 mutation carriers. Cancer Epidemiol Biomarkers Prev. 2001;10(9):955–60.PubMedGoogle Scholar
  25. 25.
    Levy-Lahad E et al. A single nucleotide polymorphism in the RAD51 gene modifies cancer risk in BRCA2 but not BRCA1 carriers. Proc Natl Acad Sci U S A. 2001;98(6):3232–6.PubMedCentralCrossRefPubMedGoogle Scholar
  26. 26.
    Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.CrossRefPubMedGoogle Scholar
  27. 27.
    Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst. 1959;22(4):719–48.PubMedGoogle Scholar
  28. 28.
    DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.CrossRefPubMedGoogle Scholar
  29. 29.
    Galbraith RF. A note on graphical presentation of estimated odds ratios from several clinical trials. Stat Med. 1988;7(8):889–94.CrossRefPubMedGoogle Scholar
  30. 30.
    Attia J, Thakkinstian A, D'Este C. Meta-analyses of molecular association studies: methodologic lessons for genetic epidemiology. J Clin Epidemiol. 2003;56(4):297–303.CrossRefPubMedGoogle Scholar
  31. 31.
    Stuck AE, Rubenstein LZ, Wieland D. Bias in meta-analysis detected by a simple, graphical test. Asymmetry detected in funnel plot was probably due to true heterogeneity. BMJ. 1998;316(7129):469. author reply 470-1.PubMedCentralCrossRefPubMedGoogle Scholar
  32. 32.
    Egger M et al. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.PubMedCentralCrossRefPubMedGoogle Scholar
  33. 33.
    Romanowicz-Makowska H et al. A single nucleotide polymorphism in the 5′ untranslated region of RAD51 and ovarian cancer risk in Polish women. Eur J Gynaecol Oncol. 2012;33(4):406–10.PubMedGoogle Scholar
  34. 34.
    Khanna KK, Jackson SP. DNA double-strand breaks: signaling, repair and the cancer connection. Nat Genet. 2001;27(3):247–54.CrossRefPubMedGoogle Scholar
  35. 35.
    Garcia-Closas M et al. Genetic variation in the nucleotide excision repair pathway and bladder cancer risk. Cancer Epidemiol Biomarkers Prev. 2006;15(3):536–42.CrossRefPubMedGoogle Scholar
  36. 36.
    Trikalinos TA et al. Impact of violations and deviations in Hardy-Weinberg equilibrium on postulated gene-disease associations. Am J Epidemiol. 2006;163(4):300–9.CrossRefPubMedGoogle Scholar

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2014

Authors and Affiliations

  • Shujing Shi
    • 1
  • Lingyan Qin
    • 2
  • Mengqiu Tian
    • 1
  • Mao Xie
    • 1
  • Xiaoxue Li
    • 1
  • Chenglin Qi
    • 1
  • Xiang Yi
    • 1
  1. 1.Department of Otolaryngology-Head and Neck SurgeryFirst Affiliated Hospital of Guangxi Medical UniversityNanningPeople’s Republic of China
  2. 2.Department of Clinical LaboratoryFirst Affiliated Hospital of Guangxi Medical UniversityNanningPeople’s Republic of China

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