Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.
Abstract
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.
Type
Journal articleSubject
Bayes TheoremCase-Control Studies
Cystadenocarcinoma, Serous
DNA Damage
DNA Repair
Data Collection
Female
Humans
Models, Statistical
Neoplasm Invasiveness
Ovarian Neoplasms
Polymorphism, Single Nucleotide
Probability
Risk
Tumor Suppressor Protein p53
Permalink
https://hdl.handle.net/10161/8883Published Version (Please cite this version)
10.1371/journal.pone.0010061Publication Info
Schildkraut, 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.
Collections
More Info
Show full item recordScholars@Duke
Rex Colle Bentley
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
Andrew Berchuck
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
Merlise Clyde
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.
Edwin Severin Iversen Jr.
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.
Jeffrey R. Marks
Professor in 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
Patricia Gripka Moorman
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.
Joellen Martha Schildkraut
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.

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy
Rights for Collection: Scholarly Articles
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info