An integrated transcriptomic and computational analysis for biomarker identification in human glioma

Malignant glioma is one of the most common primary brain tumors and is among the deadliest of human cancers. The molecular mechanism for human glioma is poorly understood. Early prognosis of this disease and early treatment are vital. Thus, it is crucial to target the key genes controlling pathogenesis in the early stage of glioma. In this study, differentially expressed genes in human glioma and paired peritumoral tissues were detected by transcriptome microarray analysis. Following gene microarray analysis, the gene expression profile in the differential grade glioma was further validated by bioinformatic analyses, co-expression network construction. Microarray analysis revealed that 1725 genes were differentially expressed and classified into different glioma stage. The analysis revealed 14 genes that were significantly associated with survival with a false discovery rate. Among these genes, macrophage capping protein (CAPG), a member of the actin-regulatory protein, was the key gene in a 20-gene network that modulates cell motility by interacting with the cytoskeleton. Furthermore, the prognostic impact of CAPG was validated by use of quantitative real-time polymerase chain reaction (qPCR) and immunohistochemistry on human glioma tissue. CAPG protein was significantly upregulated in clinical high-grade glioblastoma as compared with normal brain tissues. Overexpression of CAPG levels also predict shorter overall survival of glioma patients. These data demonstrated CAPG protein expression in human glioma was associated with tumorigenesis and may be a biomarker for identification of the pathological grade of glioma.