Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.
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BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.
Polymorphism, Single Nucleotide
Tumor Suppressor Protein p53
Published Version (Please cite this version)10.1371/journal.pone.0010061
Publication InfoBentley, RC; Berchuck, Andrew; Clyde, Merlise; Iversen, Edwin S; Marks, JR; Moorman, PG; ... Wilson, MA (2010). Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer. PLoS One, 5(4). pp. e10061. 10.1371/journal.pone.0010061. Retrieved from http://hdl.handle.net/10161/8883.
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James M. Ingram Professor of Gynecologic Oncology
Dr. Andrew Berchuck is Director of the Duke Division of Gynecologic Oncology and holds the James M. Ingram Distinguished Professorship. He is a practicing oncologist who is actively involved in the surgical and chemotherapy management of women with ovarian, endometrial and lower genital tract cancers. This includes minimally invasive laparoscopic surgical approaches. He also has developed a research program that focuses on the molecular-genetic alterations involved in malignant transformation of
Professor of Statistical Science
Model uncertainty and choice in prediction and variable selection problems for linear, generalized linear models and multivariate models. Bayesian Model Averaging. Prior distributions for model selection and model averaging. Wavelets and adaptive kernel non-parametric function estimation. Spatial statistics. Experimental design for nonlinear models. Applications in proteomics, bioinformatics, astro-statistics, air pollution and health effects, and environmental sciences.
Research Professor of Statistical Science
Bayesian statistical modeling with application to problems in genetic epidemiology and cancer research; models for epidemiological risk assessment, including hierarchical methods for combining related epidemiological studies; ascertainment corrections for high risk family data; analysis of high-throughput genomic data sets.
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