Multiomics Integration of Serum Proteome and Autoantibody Profiles Reveals Diagnostic and Prognostic Biomarkers in Glioma

Methods: Tandem mass tag (TMT)-based quantitative proteomics was performed on sera from 30 GBM 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 GBM patients, 30 HCs) and validation (n = 32 GBM 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. 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; 0.85 validation). IgM-p-SAA4-1 positivity was correlated with longer survival, whereas elevated IgM-p-IL-1β-2 levels predicted poor prognosis and adverse molecular subtypes (IDH1/ATRX wild-type, unmethylated MGMT). 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 diagnostic accuracy and prognostic relevance in GBM. These biomarkers reflect interactions between humoral immunity, tumor gene expression, and the immune microenvironment, supporting their potential for clinical application in GBM detection and patient stratification.