Metabolism of Estrogens: Turnover Differs Between Platinum-Sensitive and -Resistant High-Grade Serous Ovarian Cancer Cells

Steroid metabolism and hormonal dynamics in normal and malignant ovaries

The ovaries are key steroid hormone production sites in post-pubertal females. However, current research on steroidogenic enzymes, endogenous hormone concentrations and their effects on healthy ovarian function and malignant development is limited. Here, we discuss the importance of steroid enzymes in normal and malignant ovaries, alongside hormone concentrations, receptor expression and action. Key enzymes include STS, 3β-HSD2, HSD17B1, ARK1C3, and aromatase, which influence ovarian steroidal action. Both androgen and oestrogen action, via their facilitating enzyme, drives ovarian follicle activation, development and maturation in healthy ovarian tissue. In ovarian cancer, some data suggest STS and oestrogen receptor α may be linked to aggressive forms, while various oestrogen-responsive factors may be involved in ovarian cancer metastasis. In contrast, androgen receptor expression and action vary across ovarian cancer subtypes. For future studies investigating steroidogenesis and steroidal activity in ovarian cancer, it is necessary to differentiate between disease subtypes for a comprehensive understanding.

Metabonomic analysis of tumor microenvironments: a mini-review

Metabolomic analysis is a vital part of studying cancer progression. Metabonomic crosstalk, such as nutrient availability, physicochemical transformation, and intercellular interactions can affect tumor metabolism. Many original studies have demonstrated that metabolomics is important in some aspects of tumor metabolism. In this mini-review, we summarize the definition of metabolomics and how it can help change a tumor microenvironment, especially in pathways of three metabonomic tumors. Just as non-invasive biofluids have been identified as early biomarkers of tumor development, metabolomics can also predict differences in tumor drug response, drug resistance, and efficacy. Therefore, metabolomics is important for tumor metabolism and how it can affect oncology drugs in cancer therapy.

Model Cell Lines and Tissues of Different HGSOC Subtypes Differ in Local Estrogen Biosynthesis

Simple Summary

Ovarian cancer (OC) comprises a heterogeneous group of hormone-dependent diseases with very high mortality. Estrogens have been shown to promote the progression of OC; however, their exact role in OC subtypes remains unknown. Here, we investigated the local estrogen biosynthesis in OC. We performed targeted transcriptomics and estrogen metabolism analyses in high-grade serous OC (HGSOC) cell lines that differed in chemoresistance status and compared these data with publicly available transcriptome and proteome data for HGSOC tissues. In HGSOC cells, estrogen metabolism decreased with increasing chemoresistance. In highly chemoresistant cells and platinum-resistant HGSOC tissues, HSD17B14 expression was increased. Proteome data showed differential levels of HSD17B10, SULT1E1, CYP1B1, and NQO1 between the four HGSOC subtypes. Our results confirm that estrogen biosynthesis differs between different HGSOC cell models and possibly between different HGSOC subtypes. Such differentially expressed enzymes have potential as targets in the search of new treatment options.

Abstract

Ovarian cancer (OC) is highly lethal and heterogeneous. Several hormones are involved in OC etiology including estrogens; however, their role in OC is not completely understood. Here, we performed targeted transcriptomics and estrogen metabolism analyses in high-grade serous OC (HGSOC), OVSAHO, Kuramochi, COV632, and immortalized normal ovarian epithelial HIO-80 cells. We compared these data with public transcriptome and proteome data for the HGSOC tissues. In all model systems, high steroid sulfatase expression and weak/undetected aromatase (CYP19A1) expression indicated the formation of estrogens from the precursor estrone-sulfate (E1-S). In OC 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 those in 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. These results suggest that different HGSOC subtypes form different levels of estrogens and their metabolites and that the estrogen-biosynthesis-associated targets should be further studied for the development of personalized treatment.

Recent Metabolomics Analysis in Tumor Metabolism Reprogramming

Metabolic reprogramming has been suggested as a hallmark of cancer progression. Metabolomic analysis of various metabolic profiles represents a powerful and technically feasible method to monitor dynamic changes in tumor metabolism and response to treatment over the course of the disease. To date, numerous original studies have highlighted the application of metabolomics to various aspects of tumor metabolic reprogramming research. In this review, we summarize how metabolomics techniques can help understand the effects that changes in the metabolic profile of the tumor microenvironment on the three major metabolic pathways of tumors. Various non-invasive biofluids are available that produce accurate and useful clinical information on tumor metabolism to identify early biomarkers of tumor development. Similarly, metabolomics can predict individual metabolic differences in response to tumor drugs, assess drug efficacy, and monitor drug resistance. On this basis, we also discuss the application of stable isotope tracer technology as a method for the study of tumor metabolism, which enables the tracking of metabolite activity in the body and deep metabolic pathways. We summarize the multifaceted application of metabolomics in cancer metabolic reprogramming to reveal its important role in cancer development and treatment.

Estrogen- and estrogen receptor (ER)-mediated cisplatin chemoresistance in cancer

Cisplatin is a platinum-based chemotherapeutic drug used in the standard treatment of various solid cancers including testicular, bladder, head and neck, cervical and ovarian cancer. Although successful clinical responses are observed in patients following initial cisplatin treatment, resistance to cisplatin ultimately develops in most patients, leading to therapeutic failure. Multiple molecular mechanisms contributing to cisplatin resistance in cancer cells have been identified to date. In this review, we discuss the effect of estrogen, estrogen receptors (ERs) and estrogen-related receptors (ERRs) on cisplatin resistance in various cancer types. We highlight that estrogen treatment or increased expression of ERs or ERRs are generally associated with higher cisplatin resistance in cancer in vitro, mostly due to decreased caspase activity, increased anti-apoptotic protein levels such as BCL-2, higher drug efflux and higher levels of antioxidant enzymes. Targeted inhibition of ERs or estrogen production in combination with cisplatin treatment thus can be a useful strategy to overcome chemoresistance in certain cancer types. Estrogen levels and ER status can also be considered to identify cancer patients with a high potential of therapy response against cisplatin. A better mechanistic understanding of the involvement of estrogen, ERs and ERRs in the development of cisplatin resistance is needed to improve the management of cancer treatment.

Research progress of omics technology in the field of tumor resistance: From singleomics to multiomics combination application

Drug resistance is the main obstacle in the treatment of many cancers. It is of great clinical significance to study the mechanism of drug resistance and find new targets. Multi-omics mainly includes genomics, epigenomics, transcriptomics, proteomics, metabolomics, and radiomics. In recent years, the research of tumor resistance has made rapid development, which has significantly accelerated the discovery of new targets.