Integrated bioinformatic analysis for the Identification of Potential Genetic markers in Hepatocellular Carcinoma

Objective of the study was to identify differentially expressed genes (DEGs) and miRNAs as potential genetic markers to differentiate cancerous versus non-cancerous hepatic tissues as well as to compare the DEGs in those patients with and without IL-28B gene polymorphisms using bioinformatics tools. Microarray data (GSE41804) of liver tissue with/without cancer, deposited by Hodo et al8 was obtained from NCBI GEO database. Genotyping of patients with HCC associated with chronic hepatitis C was carried out to determine the association between the IL-28B genotype (rs8099917) and clinical outcome. The gene expressions were analysed using integrated bioinformatics. R software was used to process the data: Gene ontology and the KEGG database for the enrichment of pathways, STRING database for protein-protein interactions, TARBASE software to obtain miRNAs of DEGs and STITCH for drug-gene interactions. Polymorphisms of IL-28B gene were analysed by SIFT and Polyphen softwares. A total of 50,810 genes were extracted from which 250 differentially expressed genes (DEGs) were downloaded. Top 20 highly significant DEGs (p<0.00035) were analysed in detail. DEGs in cancerous tissues with major allele (TT of rs8099917) showed two upregulated genes (SPINK1, VAMP4) and five downregulated genes (MGMT, TREH, PXDC1, BGGAT1 and FREM2) as compared to non-cancerous tissues. In case of tissues with minor alleles (TG + GG), proportion of DEGs was equal. In cancerous tissues with major allele, ITGA1 and TNFAIP8L were upregulated, GPR84 gene was downregulated as compared to cancerous tissues with minor alleles. hsa-miR-335-5p, hsa-miR-940, has-miR-23a-3p etc. were the predominant miRNAs. String analysis showed 189 nodes,430 edges, average node degree 4.55, protein enrichment value p<1.0e. The study demonstrates the efficacy of bioinformatics analytic approaches in identifying probable pathogenic genes for HCC associated with hepatitis C. The interaction network identified miRNAs, hsa-miR-335-5p, hsa-miR-940 and genes TREH and TRIM16 as the key genetic markers for HCC.