Immune cell infiltration and drug response in glioblastoma multiforme: insights from oxidative stress-related genes

• Published in: Cancer cell international Vol. 24; no. 1; p. 123
• Main Authors: Wang, Kan, Xiao, Yifei, Zheng, Ruipeng, Cheng, Yu
• Format: Journal Article
• Language: English
• Published: England BioMed Central 02-04-2024; BMC
• Subjects: Algorithms; Angiogenesis; Brain cancer; Cancer therapies; Cell death; Cell proliferation; Datasets; Gene expression; Genomes; Genomics; Glioblastoma; Glioma; Glioma cells; Immune infiltration; Immunotherapy; Infiltration; Malignancy; Medical prognosis; Metastases; Mutation; ORGs; Oxidation; Oxidative stress; Patients; Prognostic signature; Regression analysis; Software; Tumors; Prognostic signature; ORGs; Glioblastoma; Immune infiltration
• ISSN: 1475-2867; 1475-2867
• DOI: 10.1186/s12935-024-03316-2

GBM, also known as glioblastoma multiforme, is the most prevalent and lethal type of brain cancer. The cell proliferation, invasion, angiogenesis, and treatment of gliomas are significantly influenced by oxidative stress. Nevertheless, the connection between ORGs and GBM remains poorly comprehended. The objective of this research is to investigate the predictive significance of ORGs in GBM and their potential as targets for therapy.
We identified differentially expressed genes in glioma and ORGs from public databases. A risk model was established using LASSO regression and Cox analysis, and its performance was evaluated with ROC curves. We then performed consistent cluster analysis on the model, examining its correlation with immunity and drug response. Additionally, PCR, WB and IHC were employed to validate key genes within the prognostic model.
9 ORGs (H6PD, BMP2, SPP1, HADHA, SLC25A20, TXNIP, ACTA1, CCND1, EEF1A1) were selected via differential expression analysis, LASSO and Cox analysis, and incorporated into the risk model with high predictive accuracy. Enrichment analyses using GSVA and GSEA focused predominantly on malignancy-associated pathways. Subtype C of GBM had the best prognosis with the lowest risk score. Furthermore, the model exhibited a strong correlation with the infiltration of immune cells and had the capability to pinpoint potential targeted therapeutic medications for GBM. Ultimately, we selected HADHA for in vitro validation. The findings indicated that GBM exhibits a significant upregulation of HADHA. Knockdown of HADHA inhibited glioma cell proliferation and diminished their migration and invasion capacities and influenced the tumor growth in vivo.
The risk model, built upon 9 ORGs and the identification of GBM subtypes, suggests that ORGs have a broad application prospect in the clinical immunotherapy and targeted drug treatment of GBM. HADHA significantly influences the development of gliomas, both in vivo and in vitro.