Proteomic Characterization of Necroptosis-Related Proteins Reveals the Role of Endometrial Dysfunction in Predicting Pregnancy Outcomes in Polycystic Ovary Syndrome.
This study investigated necroptosis-related molecular alterations in the endometrium of patients with polycystic ovary syndrome (PCOS) using quantitative proteomic analysis and developed a predictive model for pregnancy outcomes based on these findings.
Liquid chromatography-tandem mass spectrometry was used to identify and quantify endometrial proteins. Differentially expressed proteins (DEPs) were screened and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify key pathways. Candidate prognostic necroptosis-related proteins were obtained by intersecting DEPs with the necroptosis gene set, followed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to select those associated with pregnancy outcomes and construct a predictive model.
A total of 611 DEPs were identified (132 upregulated and 479 downregulated). KEGG enrichment revealed significant involvement of the necroptosis pathway. Six necroptosis-related proteins were identified using Cox and LASSO regression analyses and used to construct the predictive model. Kaplan-Meier analysis showed that the low-risk group had significantly better pregnancy outcomes than the high-risk group. The model achieved an area under the receiver operating characteristic curve of 0.903 for predicting live birth at 37 weeks, and decision curve analysis demonstrated superior clinical benefit compared to conventional clinical indicators. Furthermore, correlation analysis revealed significant associations between necroptosis-related proteins and classical endometrial receptivity markers, suggesting potential molecular crosstalk.
Proteomic profiling revealed enrichment of the necroptosis pathway in the endometrium of patients with PCOS. The constructed model indicated preliminary predictive potential for pregnancy outcomes, suggesting that necroptosis may contribute to impaired endometrial receptivity.
Liquid chromatography-tandem mass spectrometry was used to identify and quantify endometrial proteins. Differentially expressed proteins (DEPs) were screened and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify key pathways. Candidate prognostic necroptosis-related proteins were obtained by intersecting DEPs with the necroptosis gene set, followed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses to select those associated with pregnancy outcomes and construct a predictive model.
A total of 611 DEPs were identified (132 upregulated and 479 downregulated). KEGG enrichment revealed significant involvement of the necroptosis pathway. Six necroptosis-related proteins were identified using Cox and LASSO regression analyses and used to construct the predictive model. Kaplan-Meier analysis showed that the low-risk group had significantly better pregnancy outcomes than the high-risk group. The model achieved an area under the receiver operating characteristic curve of 0.903 for predicting live birth at 37 weeks, and decision curve analysis demonstrated superior clinical benefit compared to conventional clinical indicators. Furthermore, correlation analysis revealed significant associations between necroptosis-related proteins and classical endometrial receptivity markers, suggesting potential molecular crosstalk.
Proteomic profiling revealed enrichment of the necroptosis pathway in the endometrium of patients with PCOS. The constructed model indicated preliminary predictive potential for pregnancy outcomes, suggesting that necroptosis may contribute to impaired endometrial receptivity.