Purpose: Metabolic alterations are crucial for tumor progression and response to therapy. The comprehensive model of combined central carbon metabolism–associated genes that contribute to the outcomes of glioma and astrocytoma… Click to show full abstract
Purpose: Metabolic alterations are crucial for tumor progression and response to therapy. The comprehensive model of combined central carbon metabolism–associated genes that contribute to the outcomes of glioma and astrocytoma is not well understood. Method: We studied the profiles of 63 genes involved in central carbon metabolism in 514 relatively low-grade glioma patients. The different distributions of gene expression in gliomas and astrocytoma were identified. The differential gene expression between each cohort and the correlations with prognosis were detected. Finally, we built a tentative model to detect the prognostic roles of carbon metabolism–associated genes in astrocytoma. Result: Two primary clusters and four subclusters with significantly different overall survival were identified in low-grade glioma. The differences of histological diagnoses, grade, tumor site, and age were detected between each cluster. Comparing with other histological types, patients with astrocytoma exhibited the worst prognosis. Between astrocytoma patients with poor and favorable prognoses, expression profiles of 11 genes were significantly discrepant. We detected that 18 genes were respectively correlated with overall survival in astrocytoma; moreover, four genes (RAF1, AKT3, IDH1, and FGFR1) were detected as dependent variables for the prediction of the survival status of astrocytoma patients and were capable to predict the survival. Conclusion: Central carbon metabolism–associated genes are differentially expressed in all patients with glioma and histological subtype astrocytoma. The gene expression profile is significantly associated with clinical manifestations. These results suggested that both the multigene expression patterns and individual central carbon metabolism–associated genes were potentially capable to predict the prognosis of patients with low-grade glioma.
               
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