Cancer Epidemiology Biomarkers & Prevention · 2010 · 66 citations · 17 references
Life SciencesGeneticsOncologyCancer GeneticsGenetic EpidemiologyGenomicsDisease Susceptibility LociGenome-wide Association StudiesGenotype-phenotype Association AnalysisGermline Cancer PredispositionGermline Cancer SusceptibilityCancer Risk AssociationGenetic Prognostic MarkersGenetic Risk MarkersGenome-wide Association Study DesignGermline Genetic PolymorphismsRelative SurvivalRelative Survival HazardSingle-nucleotide Polymorphisms
BACKGROUND: Traditional clinicopathologic features of breast cancer do not account for all the variation in survival. Germline genetic variation may provide additional prognostic information. MATERIALS AND METHODS: We conducted a genome-wide association study of survival after a diagnosis of breast cancer by obtaining follow-up data and genotyping information on 528,252 single-nucleotide polymorphisms for 1,145 postmenopausal women with invasive breast cancer (7,711 person-years at risk) from the Nurses' Health Study scanned in the Cancer Genetic Markers of Susceptibility initiative. We genotyped the 10 most statistically significant loci (most significant single-nucleotide polymorphism located in ARHGAP10; P = 2.28 x 10(-7)) in 4,335 women diagnosed with invasive breast cancer (38,148 years at risk) in the SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity) breast cancer study. RESULTS: None of the loci replicated in the SEARCH study (all P > 0.10). Assuming a minimum of 10 associated loci, the power to detect at least one with a minor allele frequency of 0.2 conferring a relative hazard of 2.0 at genome-wide significance (P = 5 x 10(-8)) was 99%. CONCLUSION: We did not identify any common germline variants associated with breast cancer survival overall. IMPACT: Our data suggest that it is unlikely that there are common germline variants with large effect sizes for breast cancer survival overall (hazard ratio >2). Instead, it is plausible that common variants associated with survival could be specific to tumor subtypes or treatment approaches. New studies, sufficiently powered, are needed to discover new regions associated with survival overall or by subtype or treatment subgroups.
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Gene expression profiling predicts clinical outcome of breast cancer
Laura van ‘t Veer, Hongyue Dai, Marc J. van de Vijver et al. · Nature · 2002 · 9.6K citations · Full text
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
Marc J. van de Vijver, Yudong D. He, Laura van ‘t Veer et al. · New England Journal of Medicine · 2002 · 6.5K citations · Full text
Medicine, Bioinformatics, Oncology +17
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