Bioinformatics approach for shedding light on controversial information of IGF۱/۲ expression pattern in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignant tumorsworldwide [۱]. The present study aimed to identify the expression patterns of IGF۱/۲ and pathwaysassociated with HCC by using bioinformatics methods. The raw microarray data of GSE۸۴۴۰۲,including ۱۴ pairs of HCC tissues and the corresponding non-cancerous tissues, were obtained from theGene Expression Omnibus (GEO) database. These data were contributed by Wang et al. [۲]. Afterdefining two groups and analyzing with GEO۲R, a group of genes was achieved; in order to find thehub genes between them, a group of genes was screened out according to adjusted P-value <۰.۰۵ and— logFC—≥۲; second, we constructed the protein-protein interaction (PPI) network from the STRINGdatabase. Finally, among some genes, IGF۱/۲ was chosen according to its good betweenness centrality.To define the expression patterns of IGF۱/۲ in HCC tissue, we used the UALCAN and GEPIA databasesand used the KEGG database to construct a network of HCC; The signaling pathway of IGF۱/۲ wasobtained from REACTOME database. In conclusion, based on bioinformatics analyses, we observeddown-regulation of IGF۱/۲ in cancer samples compared to control, although the in vivo and in vitroresults were not similar. We found that down-regulation of IGF۱/۲, increases cancerous phenotypethrough increasing the activity of Wnt/β- catenin, mTOR and ERBB۲ signaling pathway and resultingin enhanced survival, proliferation and differentiation of cells; So targeting these molecular pathwayscan be a promising therapeutic approach in future.

کلیدواژه ها:

Insulin-like growth factor system ، Hepatocellular carcinoma ، System biology ، Wnt/β- catenin ، ERBB۲