Metabolism-related gene vaccines and immune infiltration in ovarian cancer: A novel risk score model of machine learning.

BACKGROUND: The present study aims to develop a metabolic gene signature to evaluate the survival rate of ovarian cancer (OC) patients and analyze the potential mechanisms of metabolic genes in OC because the difficulty in early detection of OC often leads to poor treatment outcomes. METHODS: A non-negative matrix factorization algorithm was applied to determine molecular subtypes according to metabolism genes. To build a risk prognosis model, least absolute shrinkage and selection operator multivariate Cox analysis was carried out with weighted correlation network analysis (WCGNA). Glycolytic flux and mitochondrial function were evaluated by conducting seahorse analysis. RESULTS: On the basis of metabolism-related genes, the two subtypes of OC samples present in The Cancer Genome Atlas database were distinguished. An analysis of WGCNA identified 1056 genes. Lastly, a 10-gene signature (CMAS, ADH1B, PLA2G2D, BHMT, CACNA1C, AADAC, ALOX12, CYP2R1, SCN1B and ME1) was constructed that demonstrated promising performance in predicting outcome in patients with OC. The RiskScore of the gene signature was linked to microenvironment cell infiltration and immune checkpoint. Higher RiskScores were associated with poorer results for OC patients. Seahorse analysis shows the influence of CMAS in cell energy metabolism. CONCLUSIONS: In the present study, a novel marker for evaluating the survival of OC patients was developed through the creation of a gene signature incorporating metabolism-related genes. Our knowledge of immunotherapy and microenvironment cell infiltration may be enriched by evaluating metabolism-related gene modification patterns.

Metabolic and senescence characteristics associated with the immune microenvironment in ovarian cancer.

Ovarian cancer is a highly malignant gynecological cancer influenced by the immune microenvironment, metabolic reprogramming, and cellular senescence. This review provides a comprehensive overview of these characteristics. Metabolic reprogramming affects immune cell function and tumor growth signals. Cellular senescence in immune and tumor cells impacts anti-tumor responses and therapy resistance. Targeting immune cell metabolism and inducing tumor cell senescence offer potential therapeutic strategies. However, challenges remain in identifying specific targets and biomarkers. Understanding the interplay of these characteristics can lead to innovative therapeutic approaches. Further research is needed to elucidate mechanisms, validate strategies, and improve patient outcomes in ovarian cancer.

[Retracted] Inhibition of microRNA­19b promotes ovarian granulosa cell proliferation by targeting IGF­1 in polycystic ovary syndrome.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the colony formation assay data (or portions of the data thereof) shown in Figs. 2C and 5G were strikingly similar to data that had appeared in different form in other articles by different authors at different research institutes. Owing to a general lack of confidence in the presented data, and due to the fact that the contentious data in the above article may have already been published, prior to its submission to Molecular Medicine Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 17: 4889­4898, 2018; DOI: 10.3892/mmr.2018.8463].

Inhibition of microRNA-19b promotes ovarian granulosa cell proliferation by targeting IGF-1 in polycystic ovary syndrome.

The purpose of the present study was to investigate the functional role of microRNA (miR)-19b in polycystic ovary syndrome (PCOS) and try to elucidate its underlying mechanisms. Expression of miR­19b and insulin­like growth factor 1 (IGF-1) was examined in ovarian cortexes [(from 18 women with PCOS and 10 who did not have PCOS (non­PCOS)] and KGN cells. Cell proliferation assays (cell viability and colony formation assay) were performed following overexpression or inhibition of miR­19b and IGF­1 or following insulin treatment in KGN cells. Expression levels of the cell cycle-associated protein cyclin D1 and cyclin­dependent kinase (CDK) 1 were analyzed following overexpression or inhibition of miR-19b and IGF-1. Potential miR­19b targets were identified by bioinformatics. Luciferase assay, reverse transcription­quantitative polymerase chain reaction and western blotting were performed to determine whether IGF­1 was a target of miR­19b. miR­19b expression was significantly decreased in the PCOS ovarian cortex and KGN cells and its identified target, IGF­1, was upregulated. miR­19b overexpression inhibited cell proliferation at G2/M phrase. Overexpression of IGF­1 promoted cell viability and colony formation ability in KGN cells. The expression of cyclin D1 and CDK1 was statistically increased by inhibition of miR­19b and overexpression of IGF­1. High concentrations of insulin decreased levels of miR­19b, stimulated KGN cell proliferation, and elevated IGF­1 levels. Inhibition of miR­19b promoted ovarian granulosa cell proliferation by targeting IGF­1 in PCOS. Insulin decreased the expression levels of miR­19b and stimulated cell proliferation. The present study suggested that overexpression of miR­19b may be a potential therapeutic approach for PCOS.