Risk of ovarian cancer and inherited variants in relapse-associated genes.
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2010-01-27
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Abstract
BACKGROUND: We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. METHODS AND FINDINGS: Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p = 0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p = 0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95% CI 0.66-0.98; p = 0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p<0.05), and there was increased risk at HEXIM1 rs1053578 (p = 0.04, OR 1.40, 95% CI 1.02-1.91). CONCLUSIONS: Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasive serous ovarian cancer.
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Peedicayil, Abraham, Robert A Vierkant, Lynn C Hartmann, Brooke L Fridley, Zachary S Fredericksen, Kristin L White, Elaine A Elliott, Catherine M Phelan, et al. (2010). Risk of ovarian cancer and inherited variants in relapse-associated genes. PLoS One, 5(1). p. e8884. 10.1371/journal.pone.0008884 Retrieved from https://hdl.handle.net/10161/4525.
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Scholars@Duke
Edwin Severin Iversen
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.
Joellen Martha Schildkraut
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 African American women diagnosed with ovarian cancer. She is also collaborating in a large a case-control study of meningioma risk factors and with which a genome wide association analysis is about to commence.
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