An Immune-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer

BACKGROUND: Endometrial cancer is among the most common malignant tumors threatening the health of women. Recently, immunity and long noncoding RNA (lncRNA) have been widely examined in oncology and shown to play important roles in oncology. Here, we searched for immune-related lncRNAs as prognostic biomarkers to predict the outcome of patients with endometrial cancer. METHODS: RNA sequencing data for 575 endometrial cancer samples and immune-related genes were downloaded from The Cancer Genome Atlas (TCGA) database and gene set enrichment analysis (GSEA) gene sets, respectively. Immune-related lncRNAs showing a coexpression relationship with immune-related genes were obtained, and Cox regression analysis was performed to construct the prognostic model. Survival, independent prognostic, and clinical correlation analyses were performed to evaluate the prognostic model. Immune infiltration of endometrial cancer samples was also evaluated. Functional annotation of 12 immune-related lncRNAs was performed using GSEA software. Prognostic nomogram and survival analysis for independent prognostic risk factors were performed to evaluate the prognostic model and calculate the survival time based on the prognostic model. RESULTS: Twelve immune-related lncRNAs (ELN-AS1, AC103563.7, PCAT19, AF131215.5, LINC01871, AC084117.1, NRAV, SCARNA9, AL049539.1, POC1B-AS1, AC108134.4, and AC019080.5) were obtained, and a prognostic model was constructed. The survival rate in the high-risk group was significantly lower than that in the low-risk group. Patient age, pathological grade, the International Federation of Gynecology and Obstetrics (FIGO) stage, and risk status were the risk factors. The 12 immune-related lncRNAs correlated with patient age, pathological grade, and FIGO stage. Principal component analysis and functional annotation showed that the high-risk and low-risk groups separated better, and the immune status of the high-risk and low-risk groups differed. Nomogram and receiver operating characteristic (ROC) curves effectively predicted the prognosis of endometrial cancer. Additionally, age, pathological grade, FIGO stage, and risk status were all related to patient survival. CONCLUSION: We identified 12 immune-related lncRNAs affecting the prognosis of endometrial cancer, which may be useful as therapeutic targets and molecular biomarkers.