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• W2996872173 abstract "Glioma is one of the most common types of human brain tumor, with high mortality in high-grade gliomas (HGG). Low-grade gliomas (LGG) can progress into HGG, leading to poor prognosis. However, it is unclear what factors affect the progression of LGG to HGG. This study aims to explore the function of the crosstalk genes on the progression and prognosis of LGG using bioinformatics analysis. Integrated transcriptome analysis was used to screen differentially expressed genes (DEGs). Then, gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the association between DEGs and gene functions and pathways by ClusterProfiler package and ClueGO plug-in. Protein-protein interaction (PPI) network analysis was applied to explore the connection between genes and biological processes. Subsequently, the gene clusters were analyzed using the Centiscape and molecular complex detection (MCODE) plug-in in Cytoscape software, where the crosstalk genes were identified for further study. Ultimately, the UALCAN website and Gene Expression Profiling Interactive Analysis (GEPIA) website were performed to visualize the expression levels and survival curves of genes, respectively. There were 74 DEGs identified in glioma, including 55 upregulated genes and 19 downregulated genes, which mainly were enriched in extracellular matrix (ECM)-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and so on. Then, six crosstalk genes were selected, including COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 genes. Overall survival (OS) analysis of crosstalk genes was conducted on the GEPIA website. High expression levels of crosstalk genes were closely related to the low survival rate of patients with LGG. The overexpressed crosstalk genes, such as COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 may participate in the progression and poor prognosis of LGG through the ECM-receptor interaction pathway." @default.
• W2996872173 created "2020-01-10" @default.
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• W2996872173 date "2020-06-01" @default.
• W2996872173 modified "2023-09-27" @default.
• W2996872173 title "Identification of genes related to low‐grade glioma progression and prognosis based on integrated transcriptome analysis" @default.
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• W2996872173 doi "https://doi.org/10.1002/jcb.29577" @default.
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