Identification of COL6A1 as the Key Gene Associated with Antivascular Endothelial Growth Factor Therapy in Glioblastoma Multiforme.
Han LinYong YangChongxian HouJiantao ZhengGuangzhao LvRui MaoPeihong XuShanwei ChenYujun ZhouPeng WangDong ZhouPublished in: Genetic testing and molecular biomarkers (2021)
Background: Vascular endothelial growth factors (VEGFs) are important for glioblastoma multiforme (GBM) growth and development. However, the effects of VEGF-targeting drugs in primary GBM remain poorly understood. Aim: We aimed to explore the key genes correlated with VEGF expression and prognosis and elucidate their potential implications in GBM anti-VEGF therapy. Materials and Methods: RNA-seq data with the corresponding clinicopathological information was retrieved from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas. Weighted gene coexpression network analyses was performed on differentially expressed genes to construct coexpression modules and investigate their correlation with VEGFs. Functional enrichment analyses were performed based on the coexpressed genes from the most promising modules. CytoHubba and Kaplan-Meier analyses were implemented to identify the key genes in the modules of interest. The oncomine database, quantitative reverse transcription PCR, and the Human Protein Atlas were used to investigate the expression characteristics of the identified key genes. Results: Four modules (cyan, green, purple, and tan) correlated significantly with VEGF expression. Enrichment analyses suggested that extracellular matrix-receptor interaction, growth factor binding, and the PI3K-Akt pathways were involved in VEGF expression. Four hub genes (COL6A1, SNRPG, COL3A1, and AHI1) associated with VEGF were identified. Among them, COL6A1 was regarded as the key gene associated with anti-VEGF therapy. Further, COL6A1 was upregulated in GBM compared to that in normal brain tissues. COL6A1 overexpression was associated with a poor prognosis. Conclusion: COL6A1 was identified as the key gene associated with anti-VEGF therapy and may provide novel insight into GBM targeted therapy.
Keyphrases
- poor prognosis
- endothelial cells
- genome wide
- genome wide identification
- vascular endothelial growth factor
- growth factor
- network analysis
- bioinformatics analysis
- single cell
- long non coding rna
- rna seq
- genome wide analysis
- transcription factor
- dna methylation
- copy number
- extracellular matrix
- binding protein
- electronic health record
- cell proliferation
- cell therapy
- magnetic resonance
- machine learning
- emergency department
- risk assessment
- squamous cell carcinoma
- papillary thyroid
- magnetic resonance imaging
- multiple sclerosis
- deep learning
- resting state
- blood brain barrier
- human health
- induced pluripotent stem cells
- mass spectrometry