A clinically applicable molecular classification for high-grade serous ovarian cancer based on hormone receptor expression

To establish an effective hormone receptor-based molecular classification of high-grade serous ovarian cancer (HGSC), we retrospectively examined 875 consecutive HGSC patients who underwent primary surgery at our hospital and constructed tissue microarrays from these specimens. The expression levels of the hormone receptors were as follows: ER 64.4%, PR 12.6%, AR 35.6%, FSHR 54.5%, LHR 34.8%, and GnRHR 88.3%. Based on clustering of their expression patterns, we classified patients into five subgroups with distinctive clinical features (PR+, PR − ER + AR+, PR − ER + AR−, PR − ER − AR+, and PR − ER − AR−). Patients in the PR + group were younger compared to those in the other groups (p < 0.001). More patients were of advanced stage in the PR − ER + AR− group than the other groups (p = 0.020). A greater proportion of patients were sensitive to platinum-based chemotherapy in the PR − ER − AR + group compared with the other groups (p = 0.034). A trend of increasing risk of death was observed among these subgroups (p < 0.001). In the multivariate analysis, patients also had orderly increased hazard ratios for death in the PR + (HR = 2.256, 95% CI, 0.983–5.175), PR − ER + AR + (HR = 2.188, 95% CI, 1.004–4.796), PR − ER − AR− (HR = 2.316, 95% CI, 1.097–5.082) and PR − ER + AR− (HR = 2.928, 95% CI, 1.366–6.276) subgroups compared to the PR − ER − AR+ subgroup. Our classification could help predict patient clinical outcomes, guide individual treatments and stratify patients in future clinical trials.