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Published on: October 4, 2019
Identification of Hub Genes and Key Pathways Associated with Anti-VEGF Resistant Glioblastoma Using Gene Expression
Kesavan R Arya1, Ramachandran P Bharath Chand1, Chandran S Abhinand1
1Department of Computational Biology and Bioinformatics, University of Kerala, Thiruvananthapuram, Kerala 695581, India.
Abstract:
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.
Insights
Researchers investigated resistance to anti-vascular endothelial growth factor (VEGF) therapy in glioblastoma multiforme (GBM). They identified key genes involved in resistance, suggesting potential new therapeutic targets and biomarkers for anti-VEGF therapy resistance.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Anti-vascular endothelial growth factor (VEGF) therapy shows promise for various tumors but faces limitations due to low efficacy and drug resistance.
- Tumor growth can be promoted through alternative mechanisms when anti-VEGF therapy fails.
Purpose of the Study:
- To elucidate the molecular mechanisms underlying resistance to anti-VEGF therapy in glioblastoma multiforme (GBM) using bioinformatics analysis.
- To identify potential therapeutic targets and biomarkers for anti-VEGF resistant GBM.
Main Methods:
- Re-analysis of gene expression data from bevacizumab-resistant GBM xenografts across multiple generations.
- Utilized bioinformatics tools including Gene Ontology (GO) and pathway enrichment analyses.
- Constructed protein-protein interaction networks and performed module analysis to identify hub genes.
Main Results:
- Identified differentially expressed genes (DEGs) across GBM xenograft generations, enriched in angiogenesis, cell proliferation, migration, and apoptosis.
- Discovered 21 hub genes involved in cancer pathways, cell cycle, HIF1 signaling, and microRNAs in cancer.
- Found nine upregulated (e.g., IL6, EGFR, VEGFA) and five downregulated hub genes within the VEGF pathway.
- Survival analysis indicated that CXCL8, VEGFA, and IDH1 are associated with poor patient survival.
Conclusions:
- Specific hub genes, including CXCL8, VEGFA, and IDH1, are implicated in GBM resistance to bevacizumab.
- These identified hub genes represent potential therapeutic targets or predictive biomarkers for anti-VEGF therapy resistance in GBM.
