Patterns of associations with epidemiologic factors by high grade serous ovarian cancer gene expression subtypes.
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. 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%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.