Background: Glioma is the most aggressive primary brain tumor with glioblastoma (GBM, IDH-wildtype) as its most malignant subtype, and is associated with a dismal prognosis, creating an urgent need for noninvasive biomarkers to enable early detection and prognostic stratification. Single-marker detection exhibits inherent limitations in clinical practice, whereas multi-marker panels hold greater promise for enhancing diagnostic efficacy.
Methods: Tandem mass tag (TMT)-based quantitative proteomics was performed on sera from 30 glioma patients and 30 matched healthy controls (HCs) to identify differentially expressed proteins (DEPs). Candidate tumor-associated antigens were used to design a custom peptide microarray assessing IgG/IgM autoantibodies in the discovery (n = 55 glioma patients, 30 HCs) and validation (n = 32 glioma patients, 29 HCs) cohorts. Prognostic value was analyzed via Kaplan–Meier and Cox regression, and findings were integrated with TCGA transcriptomics and single-cell RNA sequencing data to determine immune associations and cellular origins. Subgroup analysis by IDH status was performed for GBM IDH-wildtype cohort to verify subtype-specific biomarker potential.
Results: Proteomics identified 877 proteins, with DEPs enriched in extracellular matrix remodeling, complement/coagulation cascades, and metabolism/oxidative stress pathways. A three-IgM panel (anti-p-APOE-1, anti-p-P53-1, and anti-p-SAA4-1) showed high diagnostic performance (AUC = 0.96; 0.80 validation). In the GBM IDH-wildtype subgroup, IgG-p-P53-1 and IgM-p-P53-1 were significantly highly expressed in the training set and validation set (P < 0.05), while IgM-p-APOE-1 showed moderate diagnostic efficacy in the training set (AUC = 0.776) but poor generalization in the validation set (AUC = 0.483). IgM-p-SAA4-1 positivity was an independent protective factor for longer survival in pan-glioma patients(P = 0.010). APOE and IL1B are expressed predominantly by tumor-associated macrophages, with divergent prognostic implications at the transcript level.
Conclusion: Integrated proteomic–autoantibody profiling identified and validated a serum IgM panel with robust pan-glioma diagnostic accuracy and prognostic relevance in glioma. The three-IgM panel shows pan-glioma diagnostic value, while GBM IDH-wildtype subtype-specific biomarkers require further verification with expanded sample size. These biomarkers reflect interactions between humoral immunity, tumor gene expression, and the immune microenvironment, supporting their potential for clinical translation in glioma early detection and personalized patient stratification.
Keywords: Autoantibodies; Diagnostic biomarkers; Glioma; Prognostic biomarkers; Proteomics.