Functional proteomic and phosphoproteomic profiling of routine FFPE CNS tumor tissue complements genomic and epigenomic characterization

Abstract

Genomic and DNA methylation-based analyses have transformed the classification of central nervous system (CNS) tumors by enabling robust molecular diagnosis and subclassification. However, these approaches primarily define tumor identity and do not directly capture the functional state of intracellular signaling networks. Proteomic and phosphoproteomic profiling provide complementary molecular layers by measuring protein abundance and site-specific phosphorylation. Recent methodological advances have made a comprehensive analysis of formalin-fixed, paraffin-embedded (FFPE) tissue increasingly feasible, raising the question of how functional proteomic information can complement established molecular diagnostics. Here, we applied an FFPE-compatible workflow for proteomic and phosphoproteomic profiling of ten comprehensively characterized glioblastomas, including five EGFR-amplified and five non-amplified tumors. Mass spectrometry generated robust proteomic and phosphoproteomic coverage across all cases. Global proteomic profiling revealed group-associated protein abundance and pathway differences, including increased EGFR abundance in EGFR-amplified tumors, while showing substantial intertumoral overlap. Protein-abundance-adjusted phosphoproteomic profiles similarly showed partial group-level separation with substantial intertumoral overlap. Differential analysis of protein-abundance-adjusted phosphoproteomic data identified 443 phosphosites based on predefined exploratory statistical criteria. Kinase-substrate enrichment further revealed coordinated EGFR- and SRC-family-associated signaling with marked variability across individual tumors. These findings demonstrate that routine FFPE tissue retains biologically coherent functional information at both the protein abundance and phosphosignaling levels that can be interpreted alongside genomic and epigenomic data. Phosphoproteomics therefore represents an orthogonal functional layer that may complement established molecular characterization of CNS tumors.