Antioxidants and Therapeutic Targets in Ovarian Clear Cell Carcinoma

A clinical prognostic model of oxidative stress-related genes linked to tumor immune cell infiltration and the prognosis of ovarian cancer patients

Background

According to statistics, ovarian cancer (OV) is the most prevalent type of gynecologic malignancy and has the highest mortality rate of all gynecologic tumors. Although several studies have shown that oxidative stress (OS) contributes significantly to the onset and progression of cancer, the role of OS in OV needs to be investigated further. Thus, it is critical to comprehend the function of OS-related genes in OV.

Methods

In this study, all data related to the transcriptome and clinical status of the patients were retrieved from "The Cancer Genome Atlas" (TCGA) and "Gene Expression Omnibus" (GEO) databases. Using the unsupervised cluster analysis technique, all patients with OV were classified into two different subtypes (categories) based on the OS gene. All hub genes were screened using the weighted gene co-expression network analysis (WGCNA). Since the hub genes and the differentially expressed genes (DEGs) in both categories were found to intersect, the univariate Cox regression analysis was implemented. A multivariate Cox analysis was also performed to construct a novel clinical prognosis model, which was validated using data from the GEO cohort. In addition, the relationship between risk score and immune cell infiltration level was evaluated using CIBERSORT. Finally, qRT-PCR was used to confirm the expression of the genes used to construct the model.

Results

Two subtypes of OS were obtained. The findings indicated that OS-C1 had a better survival outcome than OS-C2. The results of WGCNA yielded 112 hub genes. For univariate COX regression analyses, 49 OS-related trait genes were obtained. Finally, a clinical prognostic model containing two genes was constructed. This model could differentiate between patients with OV having varying years of survival in the TCGA and GEO cohorts. The model risk score was verified as an independent prognostic indicator. According to the results of CIBERSORT, many tumor-infiltrating immune cells were found to be significantly related to the risk score. Furthermore, the results revealed that patients with low-risk OV in the CTLA4 treatment group had a high likelihood of benefiting from immunotherapy. qRT-PCR results also showed that the expression of MARVELD1 and VSIG4 was high in the OV samples.

Conclusions

Analysis of the results suggested that the newly developed model, which contained two characteristic OS-related genes, could successfully predict the survival outcomes of all patients with OV. The findings of this study could offer valuable information and insights into the refinement of personalized therapy and immunotherapy for OV in the future.

Nanocurcumin preserves kidney function and haematology parameters in DMBA-induced ovarian cancer treated with cisplatin via its antioxidative and anti-inflammatory effect in rats

CONTEXT

Cisplatin, as a first-line treatment for ovarian cancer, is associated with debilitating adverse effects, including nephrotoxic and haematotoxic effects.

OBJECTIVE

This study determines whether nanocurcumin, combined with cisplatin, would give additional benefit to kidney function and haematological parameters in rats with ovarian cancer.

MATERIALS AND METHODS

Twenty-five Wistar rats were divided into five untreated rats and 20-dimethylbenz(a)anthracene (DMBA)-induced ovarian cancer rats. The 20 ovarian cancer rats were divided into four treatment groups: vehicle, cisplatin, cisplatin-curcumin, and cisplatin-nanocurcumin. Cisplatin was given at the dose of 4 mg/kg BW once weekly, while curcumin or nanocurcumin was administered at 100 mg/kg BW daily for four weeks. At the end of treatment, we analysed kidney function, haematological parameters, and inflammatory and oxidative stress markers from plasma.

RESULTS

Nanocurcumin alleviates the increase in kidney function markers and abnormalities in haematological indices in rats treated with cisplatin. Compared to cisplatin-treated rats, plasma urea levels decreased from 66.4 to 47.7 mg/dL, creatinine levels lowered from 0.87 to 0.82 mg/dL, and neutrophil gelatinase-associated lipocalin (NGAL) levels declined from 8.51 to 3.59 mIU/mg protein. Furthermore, the therapy increased glutathione activities (from 2.02 to 3.23 U/µL), reduced lipid peroxidation (from 0.54 to 0.45 nmol/mL), and decreased plasma TNF-α (from 270.6 to 217.8 pg/mL).

CONCLUSIONS

Cisplatin with nanocurcumin in an ovarian cancer rat model may provide additional benefits as a preventive agent against renal impairment and cisplatin-induced haematological toxicity. However, further research is required to prove that using nanocurcumin for a more extended time would not affect its anticancer properties.

Characterization of a fluorescence imaging probe that exploits metabolic dependency of ovarian clear cell carcinoma

The purpose of this study is to clarify the metabolic dependence of ovarian clear cell carcinoma (CCC) by comparing normal tissues and to examine the applicability of fluorescence imaging probe to exploit these metabolic differences. Enhanced glutathione synthesis was supported by the increased uptake of related metabolites and elevated expression levels of genes. Accumulation of intracellular iron and lipid peroxide, induction of cell death by inhibition of the glutathione synthesis pathway indicated that ferroptosis was induced. The activation of γ-glutamyl hydroxymethyl rhodamine green (gGlu-HMRG), a fluorescent imaging probe that recognizes γ-glutamyl transferase, which is essential for the synthesis of glutathione, was investigated in fresh-frozen surgical specimens. gGlu-HMRG detected extremely strong fluorescent signals in the tumor lesions of CCC patients, compared to normal ovaries or endometrium. These results revealed that CCC occurs in the stressful and unique environment of free radical-rich endometrioma, and that glutathione metabolism is enhanced as an adaptation to oxidative stress. Furthermore, a modality that exploits these metabolic differences would be useful for distinguishing between CCC and normal tissues.

Exploring the cellular and molecular differences between ovarian clear cell carcinoma and high-grade serous carcinoma using single-cell RNA sequencing and GEO gene expression signatures

The two most prevalent subtypes of epithelial ovarian carcinoma (EOC) are ovarian clear cell carcinoma (OCCC) and high-grade serous ovarian carcinoma (HGSC). Patients with OCCC have a poor prognosis than those with HGSC due to chemoresistance, implying the need for novel treatment target. In this study, we applied single-cell RNA sequencing (scRNA-seq) together with bulk RNA-seq data from the GEO (Gene Expression Omnibus) database (the GSE189553 dataset) to characterize and compare tumor heterogeneity and cell-level evolution between OCCC and HGSC samples. To begin, we found that the smaller proportion of an epithelial OCCC cell subset in the G2/M phase might explain OCCC chemoresistance. Second, we identified a possible pathogenic OCCC epithelial cell subcluster that overexpresses LEFTY1. Third, novel biomarkers separating OCCC from HGSC were discovered and subsequently validated on a wide scale using immunohistochemistry. Amine oxidase copper containing 1 (AOC1) was preferentially expressed in OCCC over HGSC, while S100 calcium-binding protein A2 (S100A2) was detected less frequently in OCCC than in HGSC. In addition, we discovered that metabolic pathways were enriched in the epithelial compartment of the OCCC samples. In vitro experiments verified that inhibition of oxidative phosphorylation or glycolysis pathways exerted direct antitumor effects on both OCCC and HGSC cells, while targeting glutamine metabolism or ferroptosis greatly attenuated chemosensitivity only in OCCC cells. Finally, to determine whether there were any variations in immune cell subsets between OCCC and HGSC, data from scRNA-seq and mass cytometry were pooled for analysis. In summary, our work provides the first holistic insights into the cellular and molecular distinctions between OCCC and HGSC and is a valuable source for discovering new targets to leverage in clinical treatments to improve the poor prognosis of patients with OCCC.

Comprehensive analysis of the glutathione S-transferase Mu (GSTM) gene family in ovarian cancer identifies prognostic and expression significance

Background

Ovarian cancer (OC) is one of the most common types of gynecologic tumor over the world. The Glutathione S-transferase Mu (GSTM) has five members, including GSTM1-5. These GSTMs is involved in cell metabolism and detoxification, but their role in OC remains unknown.

Methods

Data from multiple public databases associated with OC and GSTMs were collected. Expression, prognosis, function enrichment, immune infiltration, stemness index, and drug sensitivity analysis was utilized to identify the roles of GSTMs in OC progression. RT-qPCR analysis confirmed the effect of AICAR, AT-7519, PHA-793887 and PI-103 on the mRNA levels of GSTM3/4.

Results

GSTM1-5 were decreased in OC samples compared to normal ovary samples. GSTM1/5 were positively correlated with OC prognosis, but GSTM3 was negatively correlated with OC prognosis. Function enrichment analysis indicated GSTMs were involved in glutathione metabolism, drug metabolism, and drug resistance. Immune infiltration analysis indicated GSTM2/3/4 promoted immune escape in OC. GSTM5 was significantly correlated with OC stemness index. GSTM3/4 were remarkedly associated with OC chemoresistance, especially in AICAR, AT-7519, PHA-793887 and PI-103.

Conclusion

GSTM3 was negatively correlated with OC prognosis, and associated with OC chemoresistance and immune escape. This gene may serve as potential prognostic biomarkers and therapeutic target for OC patients.

Retinol dehydrogenase 10 contributes to cancer stemness and intracellular carbohydrate storage in ovarian clear cell carcinomas

BACKGROUND

Ovarian clear cell carcinomas (OCCCs) have been recurrent and refractory among the present treatments, so novel therapeutics are urgently needed.

OBJECTIVE

The present study accumulates the proof of concept to examine the feasibility of RDH10 as a therapeutic target for treating OCCCs.

METHODS

Immunohistochemically, RDH10 expression was evaluated in 111 primary epithelial ovarian cancers, including 55 OCCCs, 31 ovarian endometrioid carcinomas and 25 ovarian serous carcinomas. The spherogenecity provoked by RDH10 was evaluated in OCCC cells. To analyze whether RDH10 promotes carbohydrate storage via the vitamin A-gluconeogenesis pathway, phosphoenolpyruvate carboxykinase 1 (PCK1) protein levels and intracellular carbohydrate content were measured in response to modified RDH10 expression.

RESULTS

Abundant RDH10 was expressed specifically in OCCCs. RDH10 promoted spherogenecity and intracellular carbohydrate storage via modulation of PCK1 expression in OCCC cells.

CONCLUSIONS

In the present study, abundant RDH10 contributed to cancer cell stemness and intracellular carbohydrate storage in OCCCs. RDH10 is a potentially, new therapeutic candidate for treating OCCC cases.

Identification of biomarkers for the diagnosis and targets for therapy in patients with clear cell ovarian cancer: a systematic literature review

Clear cell ovarian cancer (CCOC) is a rare type of epithelial cancer often resistant to platinum-based chemotherapy. Biomarkers for the diagnosis of CCOC, and targets for immunotherapy, both have the potential to improve outcomes for patients. Our review aims to determine whether any antigens already identified in the literature could fulfil this remit. PubMed, Medline, Web of Science, Scopus, Cochrane, CINAHL and EMBASE were searched and included all reported studies up until August 2021. Primary research articles on human adult females including at least 10 CCOC patients were included. Quality assurance was carried out using a modified version of the QUADAS-2 tool. Sensitivity, specificity and area under the curve were extracted from each included study by two independent reviewers. Twenty-three articles were included which identified 19 gene transcripts/proteins and one antibody, with reported sensitivities between 21% and 100% and specificities between 0% and 100% for expression in CCOC and differentiation from other epithelial ovarian cancer subtypes, benign gynaecological disease or normal tissue. Twelve studies identified biomarkers with a sensitivity and specificity above 80%. A panel of biomarkers consisting of IMP3, napsin A and hepatocyte nuclear factor 1 beta achieved the highest area under the curve of 0.954. This review demonstrates that there are promising candidate biomarkers for the diagnosis of CCOC, some of which are highly specific, and have the potential to act as targets for therapy. However, larger cohort studies are needed to validate these biomarkers and their potential use in clinical practice.

Insights into the Role of Oxidative Stress in Ovarian Cancer

Oxidative stress (OS) arises when the body is subjected to harmful endogenous or exogenous factors that overwhelm the antioxidant system. There is increasing evidence that OS is involved in a number of diseases, including ovarian cancer (OC). OC is the most lethal gynecological malignancy, and risk factors include genetic factors, age, infertility, nulliparity, microbial infections, obesity, smoking, etc. OS can promote the proliferation, metastasis, and therapy resistance of OC, while high levels of OS have cytotoxic effects and induce apoptosis in OC cells. This review focuses on the relationship between OS and the development of OC from four aspects: genetic alterations, signaling pathways, transcription factors, and the tumor microenvironment. Furthermore, strategies to target aberrant OS in OC are summarized and discussed, with a view to providing new ideas for clinical treatment.