Identification of novel biomarkers for hepatocellular carcinoma using transcriptome analysis

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer in the world. To comprehensively investigate the utility of microRNAs (miRNAs) and protein-encoding transcripts (messenger RNAs [mRNAs]) in HCC as potential biomarkers for early detection and diagnosis, we exhaustively mined genomic data from three available omics datasets (GEO, Oncomine, and TCGA), analyzed the overlaps among gene expression studies from 920 hepatocellular carcinoma samples and 508 healthy (or adjacent normal) liver tissue samples available from six laboratories, and identified 178 differentially expressed genes (DEGs) associated with HCC. Paired with miRNA and lncRNA data, we identified 23 core genes that were targeted by nine differentially expressed miRNAs and 21 HCC-specific lncRNAs. We further demonstrated that alterations in these 23 genes were quite frequent, with five genes altered in over 5% of the population. Patients with high levels of YWHAZ, ENAH, and HMGN4 tended to have high-grade tumors and shorter overall survival, suggesting that these genes could be promising candidate biomarkers for disease and poor prognosis in patients with HCC. Our comprehensive mRNA, miRNA, and lncRNA omics analyses from multiple independent datasets identified robust molecules that may be used as biomarkers for early HCC detection and diagnosis.