Identification of Paxillin as a Prognostic Factor for Glioblastoma via Integrated Bioinformatics Analysis

Abstract

Glioblastoma (GBM) is the most prevalent and aggressive type of brain tumor in the central nervous system. Clinical outcomes for patients with GBM are unsatisfactory. Here, we aimed to identify novel, reliable prognostic factors for GBM. Cox and interactive analyses were used to identify hub genes from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas datasets. After validation using various cohorts, survival analysis, meta-analysis, and prognostic analysis were performed. Coexpression and enrichment analyses were performed to elucidate the biological pathways of hub genes involved in GBM. ESTIMATE and CIBERSORT methods were applied to analyze the association of hub genes with the tumor microenvironment (TME). Paxillin (PXN) was identified as a hub gene with a high expression in GBM. PXN expression was negatively correlated with overall survival, progression-free survival, and disease-free survival in patients with GBM. Meta-analysis and Cox analysis revealed that PXN could act as an independent prognostic factor in GBM. In addition, PXN was significantly coexpressed with signal transducer and activator of transcription 3 and transforming growth factor β1 and participated in focal adhesion, extracellular matrix/receptor interactions, and the phosphatidylinositol 3-kinase/AKT signaling pathway. The results of ESTIMATE and CIBERSORT analyses revealed that PXN was implicated in TME alterations, particularly the infiltration of regulatory T cells, activated memory T cells, and activated natural killer cells. PXN may be a reliable prognostic factor for GBM. Further studies are needed to validate these findings.