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Integrated profiling identifies caveolae-associated protein 1 as a prognostic biomarker of malignancy in glioblastoma patients.
CNS Neuroscience & Therapeutics 2018 October 12
AIMS: Glioblastoma (GBM) is a lethal disease of the central nervous system with high mortality, and novel therapeutic targets and strategies for GBM are urgently needed. Caveolae-associated protein 1 (CAVIN1) is an essential caveolar component-encoding gene and has been poorly studied in glioma. To this end, in this study, we evaluated CAVIN1 expression in glioma tissue as well as the correlation between CAVIN1 expression and prognosis in glioma patients using the data collected from clinical samples or from the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Rembrandt, and Gene Expression Omnibus (GEO) data sets.
METHODS: Survival analysis was performed with the Kaplan-Meier curve and log-rank test. The predictive role of CAVIN1 in progressive malignancy in glioma was evaluated by using a receiver operator characteristic (ROC) curve. Gene ontology (GO), Gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) methods were used to interpret the functions of CAVIN1 in GBM.
RESULTS: CAVIN1 expression was elevated in GBM compared with that in low-grade glioma and nontumor brain samples and was correlated with unfavorable outcomes in glioma patients. Additionally, CAVIN1 could serve as an independent predictive factor for progressive malignancy in GBM. Furthermore, CAVIN1 was associated with disrupted angiogenesis and immune response in the tumor microenvironment of GBM.
CONCLUSIONS: We identified CAVIN1 as a prognostic biomarker and potential target for developing novel therapeutic strategies against GBM.
METHODS: Survival analysis was performed with the Kaplan-Meier curve and log-rank test. The predictive role of CAVIN1 in progressive malignancy in glioma was evaluated by using a receiver operator characteristic (ROC) curve. Gene ontology (GO), Gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) methods were used to interpret the functions of CAVIN1 in GBM.
RESULTS: CAVIN1 expression was elevated in GBM compared with that in low-grade glioma and nontumor brain samples and was correlated with unfavorable outcomes in glioma patients. Additionally, CAVIN1 could serve as an independent predictive factor for progressive malignancy in GBM. Furthermore, CAVIN1 was associated with disrupted angiogenesis and immune response in the tumor microenvironment of GBM.
CONCLUSIONS: We identified CAVIN1 as a prognostic biomarker and potential target for developing novel therapeutic strategies against GBM.
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