The prognosis model of glioblastoma was constructed based on lactic acid metabolism-related genes

Abstract

Abstract Related studies have shown that lactate played a key role in immune escape and metastasis. Exploring the roles of lactic acid metabolism-related genes (LRGs) in glioblastoma (GBM) has great significance for clinic treatment of GBM.The target genes were obtained by intersecting the differentially expressed genes (DEGs) and the module genes. Biomarkers of GBM were screened out to construct the survival risk model, and the nomogram of GBM was constructed to clinically predict the survival of GBM patients. Moreover, the gene set enrichment analysis (GSEA) and the tumor micro-environment analysis were conducted to study the functions of different risk groups and the potential mechanism of GBM. Furthermore, the drug sensitivity analysis were carried out to provide theoretical support for clinical treatment of GBM.The risk score was constructed with six biomarkers, including CALN1, CDHR1, CRTAC1, GNAL, SLC7A14, and SPHKAP, and SLC7A14 was negative factors of GBM. Based on it, the prognostic model was constructed with age, IDH status, grade, and risk score. Noticeable, the clinical risk of GBM were associated with proliferation, migration, apoptosis, and immune related signaling pathways. In addition, the level of immune escape was higher in high risk group, and samples in high risk group were more sensitive to Vinorelbine_2048, Paclitaxel_1080, Docetaxel_1007, Gefitinib_1010, Erlotinib_1168, and etc. drugs. In this study, we identified six LRGs, including CALN1, CDHR1, CRTAC1, GNAL, SLC7A14, and SPHKAP. These findings might help to deepen the understanding of the regulatory mechanism of LRGs in GBM.