Introduction/Background Ovarian cancer is highly lethal and heterogeneous. Several hormones are involved in its etiology, including estrogens. After menopause, when ovarian cancer usually develops, estrogens are formed primarily in the local tissues from the circulating steroid precursors dehydroepiandrosterone sulfate (DHEA-S) or estrone-sulfate (E1-S). Despite the known tumor-promoting role of estrogens in ovarian cancer, the expression of E1-S or DHEA-S transporters, estrogen biosynthetic or metabolic enzymes, estrogen receptors, and the metabolism of estrogens has not yet been systematically evaluated in this disease.

Methodology We performed targeted transcriptomics analysis of 50 genes using qPCR and estrogen metabolism analyses using LC-MS/MS. The model systems were high-grade serous ovarian cancer (HGSOC) cell lines OVSAHO, Kuramochi, COV632, and immortalized normal ovarian epithelial HIO-80 cells. The results in cell lines were compared with public transcriptome and proteome data for the HGSOC tissues.

Results In all model systems, HGSOC cell lines and tissues, high steroid sulfatase expression, and weak/undetected aromatase (CYP19A1) expression supported the formation of estrogens from the E1-S precursor. In ovarian cancer cells, the metabolism of E1-S to estradiol was the highest in OVSAHO, followed by Kuramochi and COV362 cells, and decreased with increasing chemoresistance. In addition, higher HSD17B14 and CYP1A2 expressions were observed in highly chemoresistant COV362 cells and platinum-resistant tissues compared to HIO-80 cells and platinum-sensitive tissues. The HGSOC cell models differed in HSD17B10, CYP1B1, and NQO1 expression. Proteomic data also showed different levels of HSD17B10, CYP1B1, NQO1, and SULT1E1 between the four HGSOC subtypes: differentiated, immunoreactive, proliferative, and mesenchymal.

Conclusion The results of our study suggest that in HGSOCs, the metabolism of E1-S precursor into estrogens decreases with increasing chemoresistance and that HGSOC subtypes form different levels of estrogens and their metabolites. The estrogen-biosynthesis-associated targets identified in our research present a base for further studies leading to potential personalized treatment development.