Constructing a Ferroptosis-Related LncRNA Prognostic Model Associated with the Therapy Response in Endometrial Cancer

Abstract

Background: Endometrial cancer (EC) is the most common malignancy in the female reproductive system in developed countries and exhibits high heterogeneity. Our aim was to construct a ferroptosis-related lncRNA prognostic model to guide tailored treatment for EC patients. Methods: RNA-sequencing data and clinical information about EC were obtained from the cancer genome atlas (TCGA). A risk model was established by least absolute shrinkage and selection operator (LASSO) analysis. Subsequently, gene set enrichment analyses (GSEA) was applied to explore the differences in biological characteristics. Immune cells abundance profile was evaluated using different methods, including XCELL, MCPcounter, EPIC, TIMER, and CIBERSORT. The R package “oncopredict” was used to estimate drug sensitivity. Results: In this study, 35 normal samples and 500 tumor samples were included. Five lncRNAs (AC092969.1, AL356489.2, AP000757.1, AP001189.3, and LINC01936) were selected to compose the ferroptosis-related lncRNA prognostic model, which possessed better predictive ability than individual indicators to predict 5-year survival (AUC (area under the ROC curve) = 0.75). A nomogram for overall survival was established, which integrated risk score, stage, grade, and age. There was a higher proportion of TP53-mut subtype serous papillary carcinoma in high-risk group, poorly differentiated. Ferroptosis-related pathways are significantly enriched in the GSEA of the low-risk group. We observed differences between low-risk and high-risk groups in their immune landscapes, immune checkpoint expression levels, drug sensitivity and mutation landscapes. Conclusions: The prognostic risk model is a reliable and robust predictor for survival outcomes in EC patients. It can identify patients that likely will derive benefit from immunotherapy and other drug therapies.