Identification of m6A-Related lncRNA to Predict the Prognosis of Patients with Hepatocellular Carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. In the past decades, HCC treatment has achieved great progress; however, the overall prognosis remains poor. Therefore, it is the need of the hour to identify new prognostic biomarkers which can advance our understanding related to the underlying molecular mechanism of adverse prognosis and apply them to clinical work in prognosis prediction. In the present study, data of 576 HCC patients and 292 normal control cases from TCGA and ICGC databases were enrolled to our bioinformatic analysis. SNHG1 and SNHG3 were identified as overlapping genes in TCGA and ICGC databases using Pearson correlation analysis and univariate Cox regression analysis. Further, we used the median of the SNHG1 and SNHG3 expression values as the cutoff values to define the HCC patient groups with high or low expression level. The subsequent analysis revealed that abnormal high expression of SNHG1 or SNHG3 affected the immune infiltration patterns and the crosstalk among immune cells. Moreover, high expression of SNHG1 or SNHG3 resulted in drug resistant to AKT inhibitor VII, bexarotene, bicalutamide, dasatinib, erlotinib, and gefitinib. In addition, lower tumor neoantigen burden was observed in high SNHG1 or SNHG3 group. Further, we found significant relation between the aberrant upregulation of SNHG1 and SNHG3 in tumor grade and stage. We established a nomogram to systematically predict the 5- and 8-year overall survival of liver cancer patients with good accuracy. Finally, the in vitro assays suggest that SNHG1 and SNHG3 promote the proliferative, migratory, and invasive abilities of HCC cells.