Identification of an m6A-Related lncRNA Signature for Predicting the Prognosis in Patients With Kidney Renal Clear Cell Carcinoma.

ABSTRACT:

Purpose

This study aimed to construct an m6A-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.

Methods

The KIRC patient data were downloaded from TCGA database and m6A-related genes were obtained from published articles. Pearson correlation analysis was implemented to identify m6A-related lncRNAs. Univariate, Lasso, and multivariate Cox regression analyses were used to identifying prognostic risk-associated lncRNAs. Five lncRNAs were identified and used to construct a prognostic signature in training set. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were applied to evaluate reliability and sensitivity of

SUBMITTER: Yu J 

PROVIDER: S-EPMC8187870 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature