Abstract
Glioblastoma multiforme (GBM) is the most malignant and multiple tumors of the central nervous system. The survival rate for GBM patients is less than 15 months. We aimed to uncover the potential mechanism of GBM in tumor microenvironment and provide several candidate biomarkers for GBM prognosis. In this study, ESTIMATE analysis was used to divide the GBM patients into high and low immune or stromal score groups. Microenvironment associated genes were filtered through differential analysis. Weighted gene co-expression network analysis (WGCNA) was performed to correlate the genes and clinical traits. The candidate genes’ functions were annotated by enrichment analyses. The potential prognostic biomarkers were assessed by survival analysis. We obtained 81 immune associated differentially expressed genes (DEGs) for subsequent WGCNA analysis. Ten out of these DEGs were significantly associated with targeted molecular therapy of GBM patients. Three genes (S100A4, FCGR2B, and BIRC3) out of these genes were associated with overall survival and the independent test set testified the result. Here, we obtained three crucial genes that had good prognostic efficacy of GBM and may help to improve the prognostic prediction of GBM.
Highlights
Glioblastoma multiforme (GBM) is the most malignant and multiple tumors of the central nervous system (CNS), which is classified as grade IV glioma by the World Health Organization (WHO) (Ostrom et al, 2013; Louis et al, 2016; Hanif et al, 2017)
Identification of Differentially Expressed Genes Related to Tumor Microenvironments
We performed differential expression analysis to identify differentially expressed genes associated with microenvironments
Summary
Glioblastoma multiforme (GBM) is the most malignant and multiple tumors of the central nervous system (CNS), which is classified as grade IV glioma by the World Health Organization (WHO) (Ostrom et al, 2013; Louis et al, 2016; Hanif et al, 2017). GBM is a heterogeneous disease involving multiple subtypes with different clinical and molecular characteristics (Friedmann-Morvinski, 2014; Lee et al, 2018). The diagnosis of GBM is based on grading and histomorphology. The classification does not predict clinical outcomes after GBM development (Sasmita et al, 2018). In GBM, tumor cells interact with resident cells (neurons, glial cells, etc.) entangled in the extracellular matrix (ECM) and vascular system (De Luca et al, 2018).
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