ArticleFrontiers in endocrinology2023
A novel model based on necroptosis to assess progression for polycystic ovary syndrome and identification of potential therapeutic drugs.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrative Transcriptomic Analysis and Functional Validation Implicate GPT2 in Glycolytic Regulation in Polycystic Ovary Syndrome.Food science & nutrition · 2026Article
- Interpreting the molecular and cellular landscape of PCOS through bulk transcriptomics, single-cell transcriptomics and machine learning.Journal of ovarian research · 2026Article
- Article
- Exploring the mechanism of Schisandra rubriflora in the treatment of polycystic ovary syndrome based on network pharmacology and molecular docking.Journal of ovarian research · 2025Article
- Exploration of key genes associated with oxidative stress in polycystic ovary syndrome and experimental validation.Frontiers in medicine · 2025Article
- Identification of necroptosis-related gene expression and the immune response in polycystic ovary syndrome.Journal of assisted reproduction and genetics · 2024Article
- Unraveling the pathogenic interplay between SARS-CoV-2 and polycystic ovary syndrome using bioinformatics and experimental validation.Scientific reports · 2024Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Polycystic ovary syndrome (PCOS), a common endocrine and reproductive disorder, lacks precise diagnostic strategies. Necroptosis was found to be crucial in reproductive and endocrine disorders, but its function in PCOS remains unclear. We aimed to identify differentially diagnostic genes for necroptosis (NDDGs), construct a diagnostic model to assess the progression of PCOS and explore the potential therapeutic drugs. Methods: Gene expression datasets were combined with weighted gene co-expression network analysis (WGCNA) and necroptosis gene sets to screen the differentially expressed genes for PCOS. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a necroptosis-related gene signatures. Independent risk analyses were performed using nomograms. Pathway enrichment of NDDGs was conducted with the GeneMANIA database and gene set enrichment analysis (GSEA). Immune microenvironment analysis was estimated based on ssGSEA algorithm analysis. The Comparative Toxicogenomics Database (CTD) was used to explore potential therapeutic drugs for NDDGs. The expression of NDDGs was validated in GSE84958, mouse model and clinical samples. Results: Four necroptosis-related signature genes, IL33, TNFSF10, BCL2 and PYGM, were identified to define necroptosis for PCOS. The areas under curve (AUC) of receiver operating characteristic curve (ROC) for training set and validation in diagnostic risk model were 0.940 and 0.788, respectively. Enrichment analysis showed that NDDGs were enriched in immune-related signaling pathways such as B cells, T cells, and natural killer cells. Immune microenvironment analysis revealed that NDDGs were significantly correlated with 13 markedly different immune cells. A nomogram was constructed based on features that would benefit patients clinically. Several compounds, such as resveratrol, tretinoin, quercetin, curcumin, etc., were mined as therapeutic drugs for PCOS. The expression of the NDDGs in the validated set, animal model and clinical samples was consistent with the results of the training sets. Conclusion: In this study, 4 NDDGs were identified to be highly effective in assessing the progression and prognosis of PCOS and exploring potential targets for PCOS treatment.
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