Identification of a novel cuproptosis-associated lncRNA model that can improve prognosis prediction in uterine corpus endometrial carcinoma

Abstract

Uterine corpus endometrial carcinoma (UCEC) is a common female reproductive system cancer. Cuproptosis, a new type of mitochondrial respiration-regulated cell death, is associated with several cancer types. Here, we developed a cuproptosis-associated long non-coding RNA (lncRNA) model to predict the prognosis of patients with UCEC and their response to immune-based treatments. RNA sequencing (RNA-seq) and somatic mutation data for UCEC were obtained from The Cancer Genome Atlas (TCGA) database. LncRNAs co-expressed with cuproptosis-related genes were screened. Patients were randomly divided into two groups, one of which was used as training group to build the model, while the other group served as the validation group. A prognostic model comprising 13 cuproptosis-associated lncRNAs was constructed, and each lncRNA was individually related to patient prognosis. Our model clearly distinguished between risk variables in afflicted individuals. The risk score can provide a more accurate prognostic prediction compared with other clinical covariates. Patient groups at various risk groups were different according to tumor mutational burden and tumor immune dysfunction and exclusion analysis. We identified drugs for which patient populations at various risk groups showed higher sensitivity. Our model may contribute to immune related research and clinical decision-making for optimized treatment.