Bart A. Westerman

Background: Glioblastoma (GBM) is the most aggressive form of primary brain cancer. Blood platelets have emerged as biomarkers where their RNA expression pattern indicates a tumor's presence. Our study aimed to characterize these patterns to identify biological processes associated with GBM and to evaluate their potential as a non‐invasive biomarker. Methods: We analyzed platelet RNA‐seq expression profiles from 84 GBM patients and 319 healthy individuals using two complementary analytical approaches of Gene Set Enrichment Analysis and Threshold‐based Differential Expression Analysis with Elastic Net regularization. Together, these approaches may offer complementary perspectives on biological pathways associated with GBM and the descriptive functional annotation of a predictive platelet RNA gene signature, providing insight into platelet‐tumor interactions. Results: Our GSEA broad analysis highlighted platelet‐related biological processes, including coagulation, wound healing, immune regulation, and cytoskeletal organization. The Elastic Net framework additionally suggested pathways related to immune activation, cell signaling, and protein folding. Overall, these findings may suggest that platelet‐derived RNA not only has potential as a non‐invasive biomarker but may also provide insight into the systemic biological processes associated with the GBM tumor microenvironment. Conclusions: Our data suggests that platelet‐derived RNA may reflect biological processes associated with the GBM tumor microenvironment, where wound repair and immune‐related processes may play important roles. Our findings provide a resource for further research into the mechanisms that may underlie the pathophysiology and progression of glioblastoma.

Background: Epidermal growth factor receptor (EGFR) amplification occurs in ∼50% of IDH-wildtype glioblastoma (GBM) cases, frequently accompanied by expression of the oncogenic EGFRvIII variant. Although EGFR represents an attractive therapeutic target, EGFR-directed therapies have shown limited clinical efficacy in GBM. Resistance to kinase inhibitors is frequently attributed to activation of compensatory signaling pathways (“kinome rewiring”). We therefore investigated whether EGFR inhibition in GBM induces broad adaptive kinase responses that could be co-targeted to overcome resistance. Methods: We molecularly profiled 29 patient-derived GBM cell lines for EGFR status and selected five representative models spanning EGFR amplification states for functional analyses. Cells were treated with EGFR inhibitors and responses were assessed using viability assays, time-resolved immunoblotting, and phosphoproteomics (LC-MS/MS) with kinase activity inference. Results: EGFR inhibitors preferentially impaired viability in EGFR-driven models and transiently reduced EGFR phosphorylation during the initial response. However, partial restoration of EGFR phosphorylation and downstream signaling occurred after 24 hours of inhibitor exposure. Phosphoproteomics revealed no evidence of broad kinome rewiring within this timeframe but instead identified increased EGFR abundance, associated with partial restoration of EGFR pathway activity. The phosphorylated-to-total EGFR ratio remained stable, indicating that increased EGFR abundance may enable persistent residual kinase activity despite continued, but incomplete, target inhibition. Conclusions: Early responses to EGFR inhibition in GBM were not characterized by broad kinome rewiring but by restoration of EGFR signaling associated with increased EGFR abundance. These findings suggest that adaptive signaling remains largely EGFR-dependent despite inhibitor exposure, identifying regulation of EGFR abundance as a potential contributor to therapeutic resistance. Key points: - Early responses to EGFR inhibition occur without evidence of broad kinome rewiring. - EGFR signaling is restored during sustained inhibitor exposure. - Increased EGFR abundance is associated with restoration of pathway activity. Importance of the study: Adaptive resistance to EGFR-targeted therapies in GBM is commonly attributed to activation of alternative signaling pathways. Using patient-derived GBM models and phosphoproteomic profiling, we show that early adaptive responses to EGFR inhibition are not characterized by broad kinome signaling rewiring but instead remain centered on reactivation of EGFR signaling. Our findings suggest that increased EGFR abundance in response to inhibitor exposure may enhance residual EGFR signaling sufficiently to partially restore downstream pathway activity. These results indicate that early adaptive responses to EGFR inhibition may remain largely EGFR-dependent, potentially limiting the effectiveness of strategies primarily aimed at co-targeting alternative signaling pathways. Graphical

Background: We previously created a glioblastoma (GBM) DrugBank containing curated information on chemical structure, molecular target activity, and chemical biology for 500 compounds. This study expands the dataset to 1103 compounds, including molecular bioactivity, cellular dose-response, CRISPR-Cas9 knockout data, potential toxicity, and links to clinical trials and patents. Methods: We gathered information from literature on compounds and models, allowing direct comparisons between compounds, their targets, and biological effects. We also included our own dose-response and drug-induced gene expression data across various glioblastoma cell culture models. Compounds were curated for their effect in preclinical GBM models, and these parameters were projected onto an ECFP_6-based UMAP visualization. Results: The visualization facilitates comparisons of bioactivities, CRISPR-Cas9 effects in GBM, and potential toxicity in nontransformed models. The analysis highlights the strengths and weaknesses of GBM drug discovery, emphasizing the trade-offs between effectiveness, toxicity, and specificity. It also provides insights for optimizing targeting based on compound structure and characteristics, targets, and putative toxicity through cheminformatic or experimental approaches. Conclusions: The GBMdrug1000 dataset is a public state-of-the-art resource for drug discovery and cheminformatics analysis, complemented by patent information and links to clinical trial data. This curated resource forms a framework for future prioritization of targets or their combinations.

Supplementary Figure S2: Overview of averaged cell viability (n = 3) of all concentration-titrated combination therapies per cell line (continued)

Supplementary Figure S7: HRAS over expression in NF1 wildtype or NF1 mutant GB cell lines did not result in stronger synergy in dual mTOR/MEK inhibition.

Supplementary Figure S1: Overview of averaged cell viability (n = 3) of all concentration-titrated combination therapies per cell line.

Supplementary Figure S5: Gene signature analysis of transcriptomic data on primary cell lines.

Glioblastoma (GB) is the most common and aggressive brain-derived tumor. It often shows genetic alterations in kinase signaling pathways, such as the Pi3K/mTOR and RAS/MAPK pathways, which frequently converge onto oncogenic processes. However, it is unknown to what extend co-vulnerabilities exist within this network and which kinase drug targets are promising for GB treatment. We investigated the drug sensitivity of GB cell line models to monotherapy and synergy effects in dual combination therapy to targeting components of Pi3K/mTOR and RAS/MAPK pathways. In addition, we examined cell line drug sensitivities in relation to their individual genetic tumor-driving lesions [i.e., neurofibromin 1 (NF1) alterations as well as transcriptomic defined GB subtypes]. Synergy levels were correlated to in-lab generated phosphoproteomic data. Lastly, serial or simultaneous addition of MEK and mTOR inhibitors was investigated in longitudinal experiments. Dual inhibition of MEK and mTOR resulted in synergistic effects, which were associated with NF1 deficiency. Strong synergy effects were also associated with the mesenchymal subtype. Dual inhibition of MEK and mTOR led to prolonged growth inhibition in GB spheroids. In addition, sequential drug treatment resulted in similar growth inhibitory effects compared with simultaneous combination therapies. Our findings highlight the potential of dual inhibition strategies targeting multiple kinases for the treatment of GB, particularly in NF1-deficient and mesenchymal tumors, the most lethal subtype of GB.

Supplementary Table S8 shows Two-way ANOVA Tukey's multiple comparisons test U87 spheroid normalised drug effect