A new prognostic model for GBM based on coagulation-related genes

Abstract

Abstract Background: Glioblastoma multiforme (GBM) has the highest aggressiveness and is the most common and lethal types of primary brain tumor. Multiple cancers have been associated with abnormalities in the coagulation system that facilitate tumor invasion and metastasis. In GBM, the prognostic value and underlying mechanism of coagulation-related genes (CRGs) have not been explored. Methods: RNA sequencing (RNA-seq) and clinical information on GBM were obtained from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), respectively. Following the identification of differentially expressed CRGs (DECRGs) between BGM and control samples, the survival-related DECRGs were selected by the univariate and multivariable Cox regression analysis to establish a prognostic signature. The prognostic performance and clinical utility of the prognostic signature were assessed by the Kaplan-Meier analysis, receiver operating characteristic (ROC) analysis and the construction of nomogram. The signature genes-related underlying mechanisms were analyzed according to Gene set enrichment analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-cell analysis. Finally, the difference in immune cell infiltration, stromal score, immune score, and ESTIMATE score were compared between different risk groups. Results: A five-gene prognostic signature (PLAUR, GP6, C5AR1, SERPINA5, F2RL2) was established for overall survival prediction of BGM patients. The predicted efficiency of the prognostic signature was confirmed in TGGA-BGM dataset and validated in CGGA-BGM dataset, revealing that it could differentiate BGM patients from controls well, and high risk score was accompanied with poor prognosis. Moreover, biological process and signaling pathway analyses showed that signature genes were mainly enriched in the functions of blood coagulation and tumor invasion and metastasis. Moreover, high-risk patients exhibited higher levels of immune cell infiltration, stromal score, immune score, and ESTIMATE score than low-risk patients. Conclusion:An analysis of coagulation-related prognostic signatures was conducted in this study, as well as how signature genes may affect GBM progress, providing information that might provide new ideas for the development of GBM-related molecular targeted therapies.