A Genomic Instability-Associated Prognostic Signature for Glioblastoma Patients

BACKGROUND: Genomic instability and aberrant tumor mutation burden are widely accepted hallmarks of cancer. Glioblastoma (GBM) is a common brain tumor in adults, and survival of patients with GBM is poor. This study aimed to investigate the prognostic value of genomic instability -derived genes in GBM.METHODS: GBM data were downloaded from The Can-cer Genome Atlas and Chinese Glioma Genome Atlas da-tabases. Differential expression analysis of all samples with different tumor mutation burden was performed. Uni-variate Cox and LASSO Cox regression analyses were in-tegrated to determine the optimal genes for constructing a risk score model. Multivariate Cox regression analysis and survival analysis determined independent prognostic in-dicators. Immune cell infiltration was analyzed by CIBER-SORT algorithm.RESULTS: In GMB patients with high and low tumor mutation burden, we identified 154 differentially expressed genes, which were significantly enriched in 47 Gene Ontology terms and 6 Kyoto Encyclopedia of Genes and Genomes pathways. To establish a risk score, 9 genes were further screened, including SDC1 , CXCL1 , CXCL6 , RGS4 , PCDHGB2 , CA9 , ZAR1 , CHRM3 , and SLN. High-risk patients had worse prognosis in two databases. The per-formance of a nomogram including prognostic factors (risk score and age) was good. Moreover, mast cells resting was significantly differentially infiltrated between high-and low-risk GBM samples.CONCLUSIONS: The risk score constructed by 9 genomic instability-derived genes could reliably predict prognosis of GBM patients. The nomogram based on age and risk score also had a good prognostic predictive value.

Automated summary

This study investigates the prognostic value of genomic instability-derived genes in glioblastoma (GBM) patients. They identified 154 differentially expressed genes in GBM patients with high and low tumor mutation burden, and established a risk score model using 9 genes. The risk score model reliably predicted the prognosis of GBM patients, and a nomogram combining the risk score and age showed good prognostic predictive value.