Bioinformatics analysis of key biomarkers and pathways in KSHV infected endothelial cells

Abstract

Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein-protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.