Analysis of differentially co-expressed genes based on microarray data of hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the third leading cause of cancer related death worldwide. Although great progress in diagnosis and management of HCC have been made, the exact molecular mechanisms remain poorly understood. The study aims to identify potential biomarkers for HCC progression, mainly at transcription level. In this study, chip data GSE 29721 was utilized, which contains 10 HCC samples and 10 normal adjacent tissue samples. Differentially expressed genes (DEGs) between two sample types were selected by t-test method. Following, the differentially co-expressed genes (DCGs) and differentially co-expressed Links (DCLs) were identified by DCGL package in R with the threshold of q < 0.25. Afterwards, pathway enrichment analysis of the DCGs was carried out by DAVID. Then, DCLs were mapped to TRANSFAC database to reveal associations between relevant transcriptional factors (TFs) and their target genes. Quantitative real-time RT-PCR was performed for TFs or genes of interest. As a result, a total of 388 DCGs and 35,771 DCLs were obtained. The predominant pathways enriched by these genes were Cytokine-cytokine receptor interaction, ECM-receptor interaction and TGF-β signaling pathway. Three TF-target interactions, LEF1-NCAM1, EGR1-FN1 and FOS-MT2A were predicted. Compared with control, expressions of the TF genes EGR1, FOS and ETS2 were all up-regulated in the HCC cell line, HepG2; while LEF1 was down-regulated. Except NCAM1, all the target genes were up-regulated in HepG2. Our findings suggest these TFs and genes might play important roles in the pathogenesis of HCC and may be used as therapeutic targets for HCC management.