Extended Data Fig. 4: High-neural glioblastoma is linked with synapse formation and trans-synaptic signaling from proteomic profiling.

a – e) Proteomic profiling of low- (n=19) and high-neural (n=9) glioblastoma. a). WGCNA analysis showed differentially abundant proteome modules between both neural subgroups. b). High-neural glioblastomas are clustered to module ‘blue’ (top figure), while low-neural glioblastomas have a higher abundance in module ‘brown’ (bottom figure). Data are mean ± s.e.m. Two-sided t-test P = 0.0.029 (top figure) and P = 0.002 (bottom figure). c, d). Network analysis revealed e). most expressed proteins and f). associated gene ontology terms for each neural subgroup (high-neural: top, low-neural: bottom). e). Integrating transcriptomic single-cell data showed an OPC-/NPC-like character in high-neural tumors (‘ME blue’). f). Transcriptomic single-cell copy number variation plot analysis of glioblastomas with a high-neural signature. g). Immunohistostaining of representative low- and high-neural glioblastoma samples. n=10 biological replicates. h). Analysis of OLIG2⁺ cells between low- and high-neural glioblastoma samples. **P < 0.01, two-tailed Student’s t-test. i). Comparison of abundance of cell states analyzed by reference-free deconvolution between newly diagnosed, high-neural, and low-neural glioblastomas. j). Stem cell-like state significantly correlated with an increase of the neural signature in glioblastoma samples. Simple linear regression, P = 0.000003024480. Error bands representing the 95% confidence interval. k). An anticorrelation was seen between the abundance of the immune compartment and the neural signature. Simple linear regression, P = 0.000000000005. Error bands representing the 95% confidence interval.