Subject terms
death, tumor, cancer, UCEC, TCGA, gynecological cancer, Uterine Corpus Endometrial Carcinoma, Cancer
TUMOR, CANCER, MINOR, DYSFUNCTION, SOMATIC MUTATION, CANCER
Disulfidptosis, the demise of cells caused by the abnormal breakdown of disulfide bonds and actin in the cytoprotein backbone, has attracted attention in studies concerning disulfide-related cell death and its potential implications in cancer treatment. This study utilized bioinformatics to detect disulfidptosis associated lncRNA prognostic markers (DALPMs) with Uterine Corpus Endometrial Carcinoma (UCEC)-related to investigate the correlation between these indicators and the tumor immune microenvironment. The RNA sequencing data and somatic mutation information of patients with UCEC were obtained from the Cancer Genome Atlas (TCGA) database. Patients were randomly divided into Train and Test groups. The findings revealed a potential prognostic model comprising 14 DALPMs. Both univariate and multivariate Cox analyses demonstrated that the model-derived risk score functioned as a standalone prognostic indicator for patients. Significant disparities in survival outcomes were observed between the high- and low-risk groups as defined by the model. Differences in tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and tumor microenvironment (TME) stromal cells between patients of the high- and low-risk groups were also observed. The forecast model comprising long non-coding RNAs (lncRNAs) associated with disulfidptosis can effectively anticipate patients' prognoses.Uterine Corpus Endometrial Carcinoma (UCEC) is a prevalent gynecological cancer among females, presenting a significant risk to both physical and psychological well-beingAccording to Ingenbleek and KimuraAlthough a considerable amount of RNA is transcribed from the human genome, only a minor proportion is responsible for protein encodingIn this study, we developed a predictive model using lncRNAs associated with disulfidptosis to predict the prognosis of patients with UCEC and performed immune correlation analysis. The findings of our study introduce novel possibilities and concepts for UCEC research.