A New Necroptosis-Related lncRNA Signature Predicts the Prognosis of Kidney Renal Clear Cell Carcinoma Patients

Abstract

Abstract This study aimed to construct a necroptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using data obtained from The Cancer Genome Atlas (TCGA) database. The KIRC patient data were downloaded from TCGA database. Univariate Cox regression analyses, Lasso, and multivariate Cox regression analyses were used to identifying prognostic risk-associated lncRNAs. Pearson correlation analysis was implemented to obtain necroptosis-related lncRNAs. 8 lncRNAs were identified and used to construct a predictive signature. Kaplan–Meier curves and receiver operating characteristic (ROC) curves were applied to evaluate reliability and sensitivity of the signature. A prognostic nomogram was established to predict the probable 1, 2, and 3-years overall survival of KIRC patients quantitatively. Functional Enrichment Analysis was used to explore the functional differences between the high and low risk groups. We constructed and verified a necroptosis-related lncRNAs prognostic signature of KIRC patients(LINC00565、AL731567.1、PRKAR1B-AS1、PROX1-AS1、C3orf36、LINC02446、AL355377.4、LINC01738). We confirmed that the survival rates of KIRC patients with high-risk subgroup were significantly poorer than those with low-risk subgroup. Kaplan-Meier and ROC curves revealed that the signature had an acceptable predictive potency. ROC curves indicated that the prognostic signature had a reliable predictive capability(AUC = 0.725). Cox regression and survival analysis indicated that the predictive signature can predict the prognosis of KIRC patients independent of various clinical parameters. The risk score and 8 necroptosis-related lncRNAs(NRLs) were significantly correlated with immune cell infiltration. Functional enrichment analysis provided us with new ways to search for potential biological functions. We constructed a necroptosis-related lncRNAs prognostic signature which could accurately predict the prognosis of KIRC patients.