Identification Key Genes of Hepatocellular Carcinoma Base on TCGA Database

Abstract

Objective: Hepatocellular carcinoma (HCC) is a common cancer of the digestive system, is the third cause of death worldwide and the second cause of death in China. The Cancer Genome Atlas (TCGA) aims to better understand the molecular mechanisms of cancer by using a large-scale genome se-quencing-based analysis techniques and extensive cooperation. This study introduces TCGA data-base to find key genes of HCC events. Materials and Methods: The data from TCGA were processed, integrated according to the standard procedure of TCGA, data types and levels were carefully as-sessed. Bioinformatics analysis was done using the DESeq and edgeR package of R language (3.1.1 version). Results were showed as pheatmap, VennDiagram, hist, PlotMA etc. Differences were de-fined as follows: expression increased more than two folds; P <0.05; gene ranked in the top 10%. Results: 17 mRNA chips of HCC and 9 mRNA chips of normal tissue were collected from TCGA data-base. Hist figure reflected the number of different gene was large. PLotMA map showed the distribu-tion of gene expression, suggesting most genes of different expression were increased. 719 diffe-rentially expressed genes were found by DESeq, while 4413 by edger, among which 713 were com-mon different genes. Conclusion: Compared to conventional microarray, TCGA method has its own advantages such as larger number of samples, less cost and easier for analyzing, offering opportuni-ty for large-scale genomic studies of HCC and subsequent functional genomics-based research.