Discovery of Biomarkers in Hepatocellular Carcinoma Metastasis Using Bioinformatic Analysis

Abstract

Background: Liver cancer is one of the most deadly malignancies worldwide. Tumor metastasis is the main cause of liver cancer-related death. So far, the mechanism of liver cancer metastasis is far away from fully elucidated. In this study, we aimed to discover key regulators involved in liver cancer metastasis by data mining. Methods: Two different types of data, including mRNA microarray (GSE6222 and GSE6764) and miRNA microarray (GSE67138), were analyzed. A total of 83 intersectant differently expressed genes (DEGs) with the same expression pattern in GSE6222 and GSE6764 were identified. One hundred and thirty-one differently expressed miRNAs (DEMs) were identified in GSE 67138. Furthermore, a total of 26 pairs of miRNA-target, including 18 DEMs and 13 DEGs were identified as critical miRNA-target axis via miRNA-target gene interaction analysis. Result and Conclusion: Among the 18 DEMs and 13 DEGs, 10 miRNAs and 10 target genes are significantly correlated with patients’ survival (p<0.05). Our results and methods might be interesting for data mining and helpful for further experimental functional validation.