Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.
Repository Usage Stats
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 InfoSchildkraut, Joellen M; Iversen, Edwin S; Wilson, Melanie A; Clyde, Merlise A; Moorman, Patricia G; Palmieri, Rachel T; ... Berchuck, Andrew (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 https://hdl.handle.net/10161/8883.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
More InfoShow full item record
Professor of Pathology
Outcome-based research on pathology of endometrial carcinoma, including prognostic significance of histologic features of endometrial carcinoma, variants of endometrial carcinoma, definitions of atypia and well-differentiated carcinoma, and collaborative studies of oncogenes and tumor suppressor genes in endometrial carcinoma. Endometrial pathology, especially as it relates to molecular/genetic alterations in neoplasms. Ovarian pathology, especially as it relates to
James M. Ingram Distinguished 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.
Professor of Surgery
I have been engaged in basic and applied cancer research for over 28 years beginning with my post-doctoral fellowship under Arnold Levine at Princeton. Since being appointed to the faculty in the Department of Surgery at Duke, my primary interest has been towards understanding breast and ovarian cancer. I am a charter member of the NCI-Early Detection Research Network (EDRN) and have been an integral scientist in the breast and gynecologic collaborative group for 15 years including leading th
Professor Emeritus in Family Medicine and Community Health
Dr. Moorman's research focuses on the epidemiology of women's health issues. Her work includes research on ovarian cancer, breast cancer and hysterectomy. Areas of particular interest include disparities in cancer risk factors and outcomes and the effects of hysterectomy on ovarian function. As part of the Duke Evidence Synthesis group, she has also been involved in systematic reviews and meta-analyses related to ovarian cancer, breast cancer and infertility.
Professor Emeritus in Family Medicine and Community Health
Dr. Schildkraut is an epidemiologist whose research includes the molecular epidemiology of ovarian, breast and brain cancers. Dr. Schildkraut's research interests include the study of the interaction between genetic and environmental factors. She is currently involved in a large study of genome wide association and ovarian cancer risk and survival. Some of her work is also focused on particular genetic pathways including the DNA repair and apoptosis pathways. She currently leads a study of
Alphabetical list of authors with Scholars@Duke profiles.