Construction of cuproptosis-related genes risk model predicts the prognosis of Uterine Corpus Endometrial Carcinoma

构建与铜凋亡相关的基因风险模型可预测子宫内膜癌的预后

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Abstract

Cuproptosis, a recently discovered form of cell death, has emerged as a crucial player in tumor development, although its role in uterine corpus endometrial carcinoma (UCEC) remains inadequately explored. This study aims to identify prognostically relevant cuproptosis-related genes in endometrial cancer. Cuproptosis-related genes were sourced from previously published studies and the FerrDb database. UCEC gene expression profiles and clinical data were obtained from the TCGA database. Differential gene expression was determined using LIMMA analysis, and functional enrichment analysis was conducted on identified cuproptosis-related genes. A prognostic model for UCEC was developed using LASSO Cox regression analysis and a Nomogram, integrating survival data, status, and gene signatures. TIMER analysis assessed the impact of crucial cuproptosis-related genes on immune cell infiltration in UCEC. Validation of the selected genes, CDKN2A, GLS, and PPAT, was performed at both mRNA and protein levels. A total of 27 cuproptosis-related genes were identified, with 19 upregulated and 6 downregulated in UCEC. These genes were associated with key signaling pathways, including the TCA cycle, Pyruvate metabolism, Glycolysis/Gluconeogenesis, and Platinum drug resistance. The LASSO regression and Nomogram models demonstrated robust predictive performance for UCEC prognosis, identifying CDKN2A, GLS, and PPAT as critical prognostic genes. Furthermore, these genes played essential roles in immune cell infiltration in UCEC, confirming their significance. Validation at both mRNA and protein levels solidified the role of CDKN2A, GLS, and PPAT. The identified signature of CDKN2A, GLS, and PPAT demonstrates significant predictive value for UCEC prognosis, suggesting their potential as therapeutic targets, including their application in immunotherapy strategies.

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