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Glycoprotein non-metastatic melanoma protein B (GPNMB), a transmembrane glycoprotein, has been reported to be involved in tumor progression, but its prognostic value for glioma and the mechanistic effects on glioma progression have not been clearly explored. The present study aimed to investigate the prognostic role of GPNMB in glioma and the potential mechanisms of how GPNMB mediates glioma progression. Differentially expressed genes between the four highest and four lowest GPNMB expression samples in the GSE53733 dataset were first determined. Gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene set enrichment analysis results demonstrated that the significantly enriched pathways in samples with high GPNMB expression compared with those with low GPNMB expression were associated with hypoxia, angiogenesis, migration and invasion. Pearson correlation analysis was conducted to investigate the correlations between GPNMB expression and the markers of hypoxia, angiogenesis, migration and invasion in GSE53733, which were further validated using another mRNA microarray dataset from the Chinese Glioma Genome Atlas (CGGA). In addition, using the CGGA dataset, high GPNMB expression was demonstrated to be significantly associated with advanced WHO grade and short survival time in patients with glioma. Of note, based on the immunohistochemical staining of the tissue microarrays, Kaplan-Meier analysis with the Renyi test and a Cox proportional hazards model were used to validate the unfavorable prognostic role of high GPNMB expression in glioma. In conclusion, high GPNMB expression may be associated with high tumor grade and unfavorable prognosis in glioma. GPNMB expression was demonstrated to correlate with the markers of hypoxia, angiogenesis, migration and invasion, which may be potential mechanisms through which GPNMB mediates glioma progression.

oncology letters

High expression of GPNMB indicates an unfavorable prognosis in glioma: Combination of data from the GEO and CGGA databases and validation in tissue microarray