Patterns of Associations with Epidemiologic Factors by High-Grade Serous Ovarian Cancer Gene Expression Subtypes

Lindsay J Collin & Jennifer A. Doherty et al.

Abstract

Background:

Ovarian high-grade serous carcinomas (HGSC) comprise four distinct molecular subtypes based on mRNA expression patterns, with differential survival. Understanding risk factor associations is important to elucidate the etiology of HGSC. We investigated associations between different epidemiologic risk factors and HGSC molecular subtypes.

Methods:

We pooled data from 11 case–control studies with epidemiologic and tumor gene expression data from custom NanoString CodeSets developed through a collaboration within the Ovarian Tumor Tissue Analysis consortium. The PrOTYPE-validated NanoString-based 55-gene classifier was used to assign HGSC gene expression subtypes. We examined associations between epidemiologic factors and HGSC subtypes in 2,070 cases and 16,633 controls using multivariable-adjusted polytomous regression models.

Results:

Among the 2,070 HGSC cases, 556 (27%) were classified as C1.MES, 340 (16%) as C5.PRO, 538 (26%) as C2.IMM, and 636 (31%) as C4.DIF. The key factors, including oral contraceptive use, parity, breastfeeding, and family history of ovarian cancer, were similarly associated with all subtypes. Heterogeneity was observed for several factors. Former smoking [OR = 1.25; 95% confidence interval (CI) = 1.03, 1.51] and genital powder use (OR = 1.42; 95% CI = 1.08, 1.86) were uniquely associated with C2.IMM. History of endometriosis was associated with C5.PRO (OR = 1.46; 95% CI = 0.98, 2.16) and C4.DIF (OR = 1.27; 95% CI = 0.94, 1.71) only. Family history of breast cancer (OR = 1.44; 95% CI = 1.16, 1.78) and current smoking (OR = 1.40; 95% CI = 1.11, 1.76) were associated with C4.DIF only.

Conclusions:

This study observed heterogeneous associations of epidemiologic and modifiable factors with HGSC molecular subtypes.

Impact:

The different patterns of associations may provide key information about the etiology of the four subtypes.

Funding
Multi-omic Predictive Markers for Ovarian Cancer Therapy Response and OutcomesIdentifying Prognostic Markers and Therapeutic Targets for Serous Ovarian CancerEpidemiology of Ovarian Cancer:New HypothesesCore A: Biospecimen and High-Dimensional Data Management CoreIdentifying factors associated with ovarian cancer recurrence using a population-based approachCollaborative Genetic Study of Ovarian Cancer RiskDana-Farber/Harvard Cancer Center Ovarian Cancer SPOREOVARIAN CANCER RISK AND SURVIVAL IN BRCA CARRIERSHormone-Related CancersIdentifying factors associated with ovarian cancer recurrence using a population-based approachRelating Molecular Subgroups of Endometriosis-Associated Ovarian Cancers to Survival and RiskHormone Therapy and Risk of Ovarian CancerCommon biology underlying pleiotropic breast, prostate and ovarian cancer risk lociCommon biology underlying pleiotropic breast, prostate and ovarian cancer risk lociGeneral Clinical Research CenterInflammation and Ovarian CancerGenes, Hormones & Environment in an Ovarian Cancer ModelCancer Risk Assessment, Early Detection, and Interception Research ProgramNational Health and Medical Research Council (NHMRC) Grant 1092856The Molecular Epidemiology Of Ovarian CancerEpidemiologic factors and survival by molecular subtypes of ovarian cancerSteroid Hormone Genes and Ovarian Cancer RiskProject 2: Next Generation TOP1 Inhibition for the Treatment of Ovarian CancerNational Health and Medical Research Council Grant 1117044National Health and Medical Research Council Grant 2008781

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