Investigation of FG F7 gene expression profile in 20 common cancers by R and WGCNA softwares

Abstract

Cancer is a group of diseases that involve the abnormal growth of cells that can spread to other parts of the body. There are related genetic pathways that may play an important role in the formation, spread, and metastatic processes of cancer. The fibroblast growth factor gene family, in close association with signaling pathways including PI3K / AKT, MAPK / ERK1, is an influential target for many cancers. Various studies have shown that incorrect expression of FGF can induce deformity of epithelial cells and fibroblasts, and these deformed cells cause tumors. Considering the role of FGF family, with emphasis on FGF7 gene and considering that the study and evaluation of molecular and regulatory pathways involved in cancer patients is important, so in the present study we intend to identify FGF7 gene expression in 20 common cases Cancers by R and WGCNA software. WGCNA is a biological system method for describing patterns of correlation between genes in microarray samples. In this study, 20 cancers were examined using mathematical methods as well as R and WGCNA programming. Preliminary studies for each cancer were performed online with Geo2R. The results showed that FGF7 gene was significantly expressed in 9 cancers. WGCNA was applied to each cancer expression matrix individually, and FGF7 co-expression genes were obtained. For each cancer, the information of the modules was classified using R software and its diagrams were drawn. KEGG analysis and gene ontology were performed on each cancer for FGF7-related genes, and a network of FGF7-related regulatory pathways was plotted by Cytoscape software. In breast cancer, the FGF7 gene module was enriched in fatty acid metabolism and in bladder, thyroid, melanoma, and prostate cancers in focal adhesion. FGF7 co-expression genes in colorectal, esophageal, and cervical cancers were enriched in the immune response pathways.