Affiliation:
1. Department of Gynecology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Abstract
The pathogenesis and progression of endometrial cancer (EC) are associated with epithelial–mesenchymal transition (EMT) and long noncoding RNAs (lncRNAs). In the present study, we aimed to identify an EMT-related lncRNA signature and evaluate its prognostic value in EC. We obtained the expression profile of lncRNAs and clinical information of patients with endometrioid EC from The Cancer Genome Atlas database (N = 401). We identified a signature of 5 EMT-related lncRNAs and calculated the risk score of each patient. Next, we validated the independence of the prognostic value of the EMT-related lncRNA signature. Furthermore, we performed Gene Set Enrichment Analysis to identify potential molecular function and Kyoto Encyclopedia of Genes and Genomes pathways related to the EMT-related lncRNA signature. Tumor microenvironment analysis and immune checkpoint blockade (ICB) response prediction were also assessed. Survival analysis revealed that the high-risk group, based on the EMT-related lncRNA signature, had a poorer prognosis than the low-risk group in the training, testing, and entire sets. The predictive value of the EMT-related lncRNA signature was independent of age, The International Federation of Gynecology and Obstetrics stage, tumor grade, and body mass index. Time-dependent receiver operating characteristic curves also demonstrate the prognostic accuracy of this risk model. Gene Set Enrichment Analysis showed that cytokine-cytokine receptor interaction, glycolysis/gluconeogenesis, and IL-17 signaling pathway were significantly enriched. Furthermore, tumor microenvironment analysis indicated a significant negative correlation between the immune score and EMT-related lncRNA signature risks core, while the low-risk group was more likely to respond to ICB therapy than the high-risk group. A reliable EMT-related lncRNA signature of endometrioid EC was identified that could be utilized as an independent prognostic biomarker to predict patient survival outcomes and provide references for the option of ICB therapy.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
1 articles.
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