Ferroptosis-related lncRNA model based on CFAP58-DT for predicting prognosis and immunocytes infiltration in endometrial cancer.

Abstract

Endometrial cancer (EC) is a kind of common gynecological tumor. Further study on the markers related to the prognosis of endometrial cancer is important for women worldwide. The Cancer Genome Atlas (TCGA) database was used to obtain the transcriptome profiling and clinical data. A model was built using packages based on R software. Immune-related databases were employed to analyze the infiltration of immunocytes. Quantitative real-time PCR (qRT-PCR), cell counting kit-8 (CCK-8), and transwell assays were utilized to investigate the role of CFAP58-DT in EC. Following Cox regression analysis, 1,731 ferroptosis-related long non-coding RNA (lncRNA) were screened, and a 9-related lncRNA prognostic model was constructed. Patients were classified as high- and low-risk according to their expression spectrum. Kaplan-Meier (KM) analysis showed that the prognosis of low-risk patients was poor. Operating characteristic curves, decision curve analysis, and a nomogram suggested the model could independently guide prognostic evaluation, with higher sensitivity, specificity, and efficiency than other common clinical characteristics. Gene Set Enrichment Analysis (GSEA) was conducted to determine the enriched pathways among the two groups and evaluation of the immune-infiltrating conditions were performed to help improve immune therapy. Finally, we conducted cytological studies on the model's most important indicators. Overall, we identified a prognostic ferroptosis-related lncRNA model based on CFAP58-DT for predicting the prognosis and immune-infiltrating conditions in EC. We concluded that the potential oncogenic role of CFAP58-DT can further guide immunotherapy and chemotherapy.