Development and validation of a RNA binding protein-associated prognostic model for lung adenocarcinoma

Abstract

RNA binding proteins (RBPs) dysregulation have been reported in various malignant tumors and associated with the occurrence and development of cancer. However, the role of RBPs in lung adenocarcinoma (LUAD) is poorly understood. We downloaded the RNA sequencing data of LUAD from the Cancer Genome Atlas (TCGA) database and determined the differently expressed RBPs between normal and cancer tissues. The study then systemically investigated the expression and prognostic value of these RBPs by a series of bioinformatics analysis. A total of 223 differently expressed RBPs were identified, including 101 up-regulated and 122 down-regulated RBPs. Eight RBPs (IGF2BP1, IFIT1B, PABPC1, TLR8, GAPDH, PIWIL4, RNPC3, and ZC3H12C) were identified as prognosis related hub gene and used to construct a prognostic model. Further analysis indicated that the patients in the high-risk subgroup had poor overall survival(OS) compared to those in low-risk subgroup based on the model. The area under the curve of the time-dependent receiver operator characteristic curve of the prognostic model are 0.775 in TCGA cohort and 0.814 in GSE31210 cohort, confirming a good prognostic model. We also established a nomogram based on eight RBPs mRNA and internal validation in the TCGA cohort, which displayed a favorable discriminating ability for lung adenocarcinoma.