Mechanism And Prognostic Significance Of Metabolic Genes In The Development And Progression Of Glioma

Background:Glioblastoma(GBM)is the most common primary malignant tumor of the central nervous system with poor prognosis.Metabolic pathways are closely related to life processes,and their alterations are also driving factors in the occurrence and development of glioma.Targeting abnormal metabolic pathways has emerged as a possible treatment option for GBM.Lipid metabolism plays an important role in normal life activities.It has been found that the expression of Apolipoprotein C1(ApoC1)is elevated in a variety of tumors.As an iron-dependent cell death mechanism,ferroptosis has been shown to be associated with the development of tumors including GBM.This study was designed to investigate the metabolic mechanisms in the development of glioma,and thus to identify biomarkers and establish prognostic models.Methods:In this study,transcriptomic data from the Gene Expression Omnibus(GEO)and Genotype-Tissue Expression(GTEx)databases were used to screen for differentially expressed metabolic genes between GBM tissue and normal brain.Combined with overall survival(OS),a metabolic prognostic prediction model was established by regression analysis.The Cancer Genome Atlas(TCGA)and clinical samples of GBM patients were used for validation.Further studies were conducted to explore the alterations of the lipid metabolic molecule ApoCl in glioma,and to detect ApoCl level in GBM patients’ tissues.The effect of ApoC1 overexpression on proliferation,migration,invasion and reactive oxygen species(ROS)levels of GBM cell lines were investigated.Finally,we investigated the prognostic significance of ferroptosis-related genes in GBM patients by screening ferroptosis-related genes that were differentially expressed between GBM and normal brain tissues through database analysis,and the prognostic prediction model was established by regression analysis and verified by database and clinical samples.Results:The database analysis identified 341 metabolic genes differentially expressed in normal brain tissue and GBM tissue,among which 56 genes were associated with OS in patients.The Lasso regression analysis was used to construct the metabolic prognosis prediction model.The metabolic prognosis prediction model consisted of 18 genes.including favorable genes COX 10,COMT and GPX2 and unfavorable genes OCRL and RRM2.The OS of patients classified as high-risk group was significantly shorter than that of patients in the low-risk group according to the risk score of this model,and this result was also present in the validation set.We further found that both bioinformatic and clinical samples suggested that ApoC1 expression was elevated in GBM tissues,and ApoC1 overexpression promoted GBM cell proliferation,migration and invasion,and inhibited cellular oxidative stress and reduced ROS levels.In the ferroptosis-related prognosis prediction model establishing,database analysis revealed 45 differentially expressed ferroptosis-related genes between GBM and normal brain tissues.The ferroptosis-related prognostic prediction model was constructed based on four favorable genes CRYAB,ZEB1,ATP5MC3 and NCOA4,and four unfavorable genes ALOX5,CHAC1,STEAP3 and MT1G.Significant differences in OS between the high-risk and low-risk groups were observed in both the training and validation cohorts.Conclusions:This study proposes ApoC1 as a potential diagnostic and prognostic biomarker for GBM,as well as two prognostic prediction models based on metabolic and ferroptosis-related,which can predict patient prognosis by calculating GBM patient risk scores,and further explore the molecular mechanisms through basic research,thus assisting neurosurgeons in predicting patient prognosis and assisting in the selection of treatment options.