Evaluation of secretome biomarkers in glioblastoma cancer stem cells: A bioinformatics analysis

Glioblastoma (GBM) is a very aggressive brain tumor. This research explores potential biomarkers in the proteins released by GBM cells, called the secretome, which could help improve diagnosis and treatment. Cancer stem cells (CSCs) within GBM tumors contribute to treatment resistance and recurrence. The study aims to identify signaling pathways and proteins, especially secretory biomarkers, that could be targeted for new therapies. Using bioinformatics, the study analyzed gene expression data to find key pathways and proteins involved in the tumor microenvironment, with the goal of identifying biomarkers for GBM prognosis and therapy.

• 1
  The study identified 890 differentially expressed genes (DEGs) in GBM cells, with 475 upregulated and 415 downregulated.
• 2
  SQLE, DHCR7, delta-1 phospholipase C (PLCD1), and MINPP1 genes are highly expressed in GBM, while Enolase 2 (ENO2) and hexokinase-1 (HK1) genes showed low expression.
• 3
  ITM2A, FLRT3, NOG, and SEMA3D genes increased expression and are relatively directly related to the mortality rate of patients with GBM.