Analysis of Prognostic and Immunological Relevance of Autophagy-Related lncRNAs in Uterine Corpus Endometrial Carcinoma Based on TCGA Database

Objective To identify autophagy-related long non-coding RNAs (ARLs) that affect the prognosis of uterine corpus endometrial carcinoma (UCEC) based on The Cancer Genome Atlas (TCGA) database, and to construct a prognostic prediction model for UCEC patients. Methods Transcriptome data and clinical information of UCEC were obtained from the TCGA database. Differentially expressed ARLs in UCEC were identified using differential expression analysis and correlation analysis. Cox analysis and least absolute shrinkage and selection operator (LASSO) algorithm were applied to determine prognostically significant ARLs, based on which a prognostic model for UCEC was constructed. The prognostic performance of the model was evaluated using Kaplan-Meier survival curve analysis, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Additionally, the relationships between the model and tumor microenvironment, immune infiltrating cells, and immune checkpoint genes were explored. Moreover, consensus clustering analysis was used to define molecular subtypes based on prognostic ARLs. Finally, functional enrichment analysis was performed on key prognostic ARLs. Results A predictive model containing 12 prognostic signature ARLs was constructed. Patients in the high-risk group had shorter overall survival, and immune function in tumor tissues was downregulated in the high-risk group. Furthermore, UCEC was classified into 5 significantly distinct molecular subtypes, among which subtypes 1 and 3 were significantly associated with autophagy and had better prognosis. Finally, functional enrichment analysis confirmed that knockdown of CDKN2B-AS1 and XPC-AS1 regulates autophagic activity through ciliary movement on the cell surface. Conclusion This study constructed a UCEC prognostic model composed of 12 autophagy-related lncRNAs, which is associated with immune function regulation and molecular subtypes of UCEC. CDKN2B-AS1 and XPC-AS1, as key prognostic markers, have the potential to be applied in risk stratification and precision therapy for UCEC patients.