Nature Communications · 2022 · 68 citations · 64 references
MedicineMolecular BiologyOncologyNeuro-oncologyProteomicsTumor HeterogeneityCancer BiomarkersCancer ProteomicsGlioblastomaMass Spectrometry-based ProteomicsMolecular Tumor ProfilingTumor MarkersGlioblastoma BiomarkersGlioblastoma PrognosisIntra-tumor HeterogeneityMass Spectrometry ProteomicsProtein Expression BiomarkersProtein Expression HeterogeneityTumor Proteome ProfilingTumor Proteomics
Molecular heterogeneity is a key feature of glioblastoma that impedes patient stratification and leads to large discrepancies in mean patient survival. Here, we analyze a cohort of 96 glioblastoma patients with survival ranging from a few months to over 4 years. 46 tumors are analyzed by mass spectrometry-based spatially-resolved proteomics guided by mass spectrometry imaging. Integration of protein expression and clinical information highlights three molecular groups associated with immune, neurogenesis, and tumorigenesis signatures with high intra-tumoral heterogeneity. Furthermore, a set of proteins originating from reference and alternative ORFs is found to be statistically significant based on patient survival times. Among these proteins, a 5-protein signature is associated with survival. The expression of these 5 proteins is validated by immunofluorescence on an additional cohort of 50 patients. Overall, our work characterizes distinct molecular regions within glioblastoma tissues based on protein expression, which may help guide glioblastoma prognosis and improve current glioblastoma classification.
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