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Anti- VEGF therapy is considered to be a useful therapeutic approach in many tumors, but the low efficacy and drug resistance limit its therapeutic potential and promote tumor growth through alternative mechanisms. We reanalyzed the gene expression data of xenografts of tumors of bevacizumab-resistant glioblastoma multiforme (GBM) patients, using bioinformatics tools, to understand the molecular mechanisms of this resistance. An analysis of the gene set data from three generations of xenografts, identified as 646, 873 and 1220, differentially expressed genes (DEGs) in the first, fourth and ninth generations, respectively, of the anti- VEGF -resistant GBM cells. Gene Ontology (GO) and pathway enrichment analyses demonstrated that the DEGs were significantly enriched in biological processes such as angiogenesis, cell proliferation, cell migration, and apoptosis. The protein-protein interaction network and module analysis revealed 21 hub genes, which were enriched in cancer pathways, the cell cycle, the HIF1 signaling pathway, and microRNAs in cancer. The VEGF pathway analysis revealed nine upregulated ( IL6 , EGFR , VEGFA , SRC , CXCL8 , PTGS2 , IDH1 , APP , and SQSTM1 ) and five downregulated hub genes ( POLR2H , RPS3 , UBA52 , CCNB1 , and UBE2C ) linked with several of the VEGF signaling pathway components. The survival analysis showed that three upregulated hub genes ( CXCL8 , VEGFA , and IDH1 ) were associated with poor survival. The results predict that these hub genes associated with the GBM resistance to bevacizumab may be potential therapeutic targets or can be biomarkers of the anti- VEGF resistance of GBM.

Identification of Hub Genes and Key Pathways Associated with Anti-VEGF Resistant Glioblastoma Using Gene Expression Data Analysis