Serpins are serine proteinase inhibitors, with several serpins being overexpressed in cancer cells. Thus, we aim to analyze the single-nucleotide polymorphism (SNP) of Serpinb11 and its association with GBM survival. A cohort of 63 GBM patients recruited from King Abdullah University Hospital in Jordan underwent polymorphism analysis and overall survival (OS) assessments. The Cancer Genome Atlas (GBM) cohort was useful for validation. We constructed a risk score using the principal component analysis for the following Serpin genes: Serpinb3, Serpinb5, Serpinb6, Serpinb11, and Serpinb12, and patients were grouped into high- vs. low-risk groups based on the median cutoff. Univariable Cox models were used to study the survival outcomes. We identified a significant association between rs4940595 and survival. In the TCGA cohort, Serpinb3 alterations showed worse OS. Univariable Cox showed worse PFS outcomes with higher SERPINB5 and SERPINB6 expression. A Serpin B 5-gene risk score showed a trend towards worse PFS in the high-risk group. Upregulated DEGs showed GO enrichment in cytokine regulation and production, positive regulation of leukocyte activation, and the MAPK cascade. The high-risk group showed a significantly higher infiltration of M2 macrophages and activated mast cells. Our findings showed a significant role of the Serpin B family in GBM survival in the Jordanian population.

Glioblastoma multiforme (GBM) is a very aggressive primary central nervous system (CNS) tumor with limited therapeutic options and poor prognosis. This study aimed to analyze the association between single nucleotide polymorphisms (SNPs), including IDH1 rs121913500C > T, IDH2 rs11540478G > A, and EGFR rs1468727C > T, and their association on the risk and overall survival of GBM patients in Jordan. Using a case-control study design involving 63 GBM patients and 226 healthy controls was conducted at King Abdullah University Hospital in Jordan. DNA extraction was performed using formalin-fixed and paraffin-embedded tissue for GBM samples and blood samples for controls. SNPs analysis was performed using the Sequenom iPLEX assay sequencing technique. Survival outcomes were assessed using Cox models and hazard ratios (HR), and single-cell RNA (scRNA) analysis was performed from GSE70630. The study showed a significant association between genotype frequency in GBM cases and controls for specific SNPs, including IDH1 rs121913500C > T, and EGFR rs1468727C > T. The G/G genotype of rs11540478 (IDH2) was associated with better prognostic outcomes in GBM patients. The scRNA analysis demonstrated the differential expression of IDH1, IDH2, and EGFR in GBM, with enrichment in central carbon metabolism in cancer. Our findings suggest that SNPs, particularly in IDH1 and IDH2 genes and EGFR, may serve as diagnostic and prognostic biomarkers for GBM. While the study underscores the clinical relevance of these genetic variants, further investigations with larger and more diverse populations are essential to validate and extend these associations.