Bioinformatic analysis reveals CYP2C9 as a potential prognostic marker for HCC and liver cancer cell lines suitable for its mechanism study

Abstract

Hepatocellular carcinoma (HCC) is a common cancer and the sixth most lethal malignancy in the world. We chose gene expression profile of GSE14520 from GEO database aiming to find key genes that affect HCC progression. 22 paired tumor and non-tumor samples were included in this analysis. Differentially expressed genes (DEGs) between tumor and non-tumor were selected using GEO2R. Gene ontology (GO) enrichment and protein-protein interaction (PPI) of the DEGs were done using Metascape. There were 357 DEGs, including 70 up-regulated genes and 287 down-regulated genes. These DEGs were enriched in drug metabolic process, organic acid catabolic process, monocarboxylic metabolic process and etc. Three important modules were detected from PPI network using Molecular Complex Detection (MCODE) algorithm. Moreover, the Kaplan-Meier analysis for overall survival and disease-free survival were applied to those genes in top PPI group. In conclusion, this bioinformatic analysis demonstrated that DEGs, such as CYP2C9, might promote the development of HCC, especially in drug metabolism. It could also be used as a new biomarker for diagnosis.