Reclassification of Hepatocellular Cancer With Neural-Related Genes

Abstract

Neural infiltration is a critical component of the tumor microenvironment; however, owing to technological limitations, its role in hepatocellular cancer remains obscure. Herein, we obtained the RNA-sequencing data of liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas database and performed a series of bioinformatic analyses, including prognosis analysis, pathway enrichment, and immune analysis, using the R software packages, Consensus Cluster Plus and Limma. LIHC could be divided into two subtypes according to the expression of neural-related genes (NRGs); moreover, there are statistic differences in the prognosis, stage, and immune regulation between the two subtypes. The prognostic model showed that high expression of NRGs correlated with a poor survival prognosis (P<0.05). Further, CHRNE, GFRA2, GFRA3, and GRIN2D was significantly correlated with LIHC clinical prognosis, clinical stage, immune infiltration, immune response, and vital signaling pathways. There was nerve-cancer crosstalk in LIHC. A reclassification of LIHC based on NRG expression may prove beneficial to clinical practice. CHRNE, GFRA2, GFRA3, and GRIN2D may serve as potential biomarker for liver cancer prognosis or immune response.