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Glioblastoma, the most aggressive primary brain cancer, has a dismal prognosis, yet systemic treatment is limited to DNA-alkylating chemotherapies. New therapeutic strategies may emerge from exploring neurodevelopmental and neurophysiological vulnerabilities of glioblastoma. To this end, we systematically screened repurposable neuroactive drugs in glioblastoma patient surgery material using a clinically concordant and single-cell resolved platform. Profiling more than 2,500 ex vivo drug responses across 27 patients and 132 drugs identified class-diverse neuroactive drugs with potent anti-glioblastoma efficacy that were validated across model systems. Interpretable molecular machine learning of drug-target networks revealed neuroactive convergence on AP-1/BTG-driven glioblastoma suppression, enabling expanded in silico screening of more than 1 million compounds with high patient validation accuracy. Deep multimodal profiling confirmed Ca 2+ -driven AP-1/BTG-pathway induction as a neuro-oncological glioblastoma vulnerability, epitomized by the anti-depressant vortioxetine synergizing with current standard-of-care chemotherapies in vivo. These findings establish an actionable framework for glioblastoma treatment rooted in its neural etiology., Competing Interests: Competing interests B.S. is scientific co-founder and shareholder of Prevision Medicine AG and Graph Therapeutics. T.W. has received honoraria from Philogen. M.C.N. received a research grant from Novocure and honoraria for consulting or lectures from WISE, Merck Sharp & Dohme, Osteopore and Novocure. M.W. has received research grants from Novartis, Quercis and Versameb and honoraria for lectures or advisory board participation or consulting from Anheart, Bayer, Curevac, Medac, Neurosense, Novartis, Novocure, Orbus, Pfizer, Philogen, Roche and Servier. The other authors declare no competing interests., (© 2024. The Author(s).)

The hepatocyte growth factor (HGF)/MET signaling pathway has been proposed to be involved in the resistance to radiotherapy of glioblastoma via proinvasive and DNA damage response pathways.Here we assessed the role of the MET pathway in the response to radiotherapy in vitro and in vivo in syngeneic mouse glioma models. We find that the murine glioma cell lines GL-261, SMA-497, SMA-540 and SMA-560 express HGF and its receptor MET and respond to exogenous HGF with MET phosphorylation. Glioma cell viability or proliferation are unaffected by genetic or pharmacological MET inhibition using tepotinib or CRISPR/Cas9-engineered Met gene knockout and MET inhibition fails to sensitize glioma cells to irradiation in vitro. In contrast, the combination of tepotinib with radiotherapy prolongs survival of orthotopic SMA-560 or GL-261 glioma-bearing mice compared with radiotherapy or tepotinib treatment alone. Synergy is lost when such experiments are conducted in immunodeficient Rag1 -/- mice, and, importantly, also when Met gene expression is disrupted in the tumor cells. Combination therapy suppresses a set of pro-inflammatory mediators including matrix metalloproteases that are upregulated by radiotherapy alone and that have been linked to poor outcome in glioblastoma. Several of these mediators are positively regulated by transforming growth factor (TGF)-β, and pSMAD2 levels as a surrogate marker of TGF-β pathway activity are suppressed by combination treatment. We conclude that synergistic suppression of experimental syngeneic glioma growth by irradiation and MET inhibition requires MET expression in the tumor as well as an intact immune system. Clinical evaluation of this combined strategy in newly diagnosed glioblastoma is warranted., (© 2023. The Author(s).)

Unlike other tumours, the anatomical extent of brain tumours is not objectified and quantified through staging. Staging systems are based on understanding the anatomical sequence of tumour progression and its relationship to histopathological dedifferentiation and survival. The aim of this study was to describe the spatiotemporal phenotype of the most frequent brain tumour entities, to assess the association of anatomical tumour features with survival probability and to develop a staging system for WHO grade 2 and 3 gliomas and glioblastoma. Anatomical phenotyping was performed on a consecutive cohort of 1000 patients with first diagnosis of a primary or secondary brain tumour. Tumour probability in different topographic, phylogenetic and ontogenetic parcellation units was assessed on preoperative MRI through normalization of the relative tumour prevalence to the relative volume of the respective structure. We analysed the spatiotemporal tumour dynamics by cross-referencing preoperative against preceding and subsequent MRIs of the respective patient. The association between anatomical phenotype and outcome defined prognostically critical anatomical tumour features at diagnosis. Based on a hypothesized sequence of anatomical tumour progression, we developed a three-level staging system for WHO grade 2 and 3 gliomas and glioblastoma. This staging system was validated internally in the original cohort and externally in an independent cohort of 300 consecutive patients. While primary CNS lymphoma showed highest probability along white matter tracts, metastases enriched along terminal arterial flow areas. Neuroepithelial tumours mapped along all sectors of the ventriculocortical axis, while adjacent units were spared, consistent with a transpallial behaviour within phylo-ontogenetic radial units. Their topographic pattern correlated with morphogenetic processes of convergence and divergence of radial units during phylo- and ontogenesis. While a ventriculofugal growth dominated in neuroepithelial tumours, a gradual deviation from this neuroepithelial spatiotemporal behaviour was found with progressive histopathological dedifferentiation. The proposed three-level staging system for WHO grade 2 and 3 gliomas and glioblastoma correlated with the degree of histological dedifferentiation and proved accurate in terms of survival upon both internal and external validation. In conclusion, this study identified specific spatiotemporal phenotypes in brain tumours through topographic probability and growth pattern assessment. The association of anatomical tumour features with survival defined critical steps in the anatomical sequence of neuroepithelial tumour progression, based on which a staging system for WHO grade 2 and 3 gliomas and glioblastoma was developed and validated., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Brain tumors, whether primary or secondary, have limited therapeutic options despite advances in understanding driver gene mutations and heterogeneity within tumor cells. The cellular and molecular composition of brain tumor stroma, an important modifier of tumor growth, has been less investigated to date. Only few studies have focused on the vasculature of human brain tumors despite the fact that the blood-brain barrier (BBB) represents the major obstacle for efficient drug delivery., Methods: In this study, we employed RNA sequencing to characterize transcriptional alterations of endothelial cells (EC) isolated from primary and secondary human brain tumors. We used an immunoprecipitation approach to enrich for EC from normal brain, glioblastoma (GBM), and lung cancer brain metastasis (BM)., Results: Analysis of the endothelial transcriptome showed deregulation of genes implicated in cell proliferation, angiogenesis, and deposition of extracellular matrix (ECM) in the vasculature of GBM and BM. Deregulation of genes defining the BBB dysfunction module was found in both tumor types. We identified deregulated expression of genes in vessel-associated fibroblasts in GBM., Conclusion: We characterize alterations in BBB genes in GBM and BM vasculature and identify proteins that might be exploited for developing drug delivery platforms. In addition, our analysis on vessel-associated fibroblasts in GBM shows that the cellular composition of brain tumor stroma merits further investigation., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Understanding the topographic-anatomical patterns of brain tumors has the potential to improve our pathophysiological understanding and may allow for anatomical tailoring of surgery and radiotherapy. This study analyzed topographic-anatomical patterns underlying neuroepithelial tumors, primary CNS lymphoma and metastases., Methods: Any histologically confirmed supra- or infratentorial parenchymal neoplasia of one institution over a 4-year period was included. Using high-resolution magnetic resonance imaging data, a detailed analysis of the topographic-anatomical tumor features was performed. Differences between neuroepithelial tumors, primary central nervous system lymphoma (PCNSL) and metastases were assessed using pairwise comparisons adjusted for multiple testing, upon significance of the omnibus test., Results: Based on image analysis of 648 patients-419 (65%) neuroepithelial tumors, 28 (5%) PCNSL and 201 (31%) metastases-entity-specific topographic-anatomical patterns were identified. Neuroepithelial tumors showed a radial ventriculo-cortical orientation, inconsistent with the current belief of a growth along white matter tracts, whereas the pattern in PCNSL corresponded to a growth along such. Metastases preferentially affected the cortex and subcortical white matter of large arteries' terminal supply areas. This study provides a comprehensive anatomical description of the topography of NT, PCNSL and metastases intended to serve as a topographic reference for clinicians and neuroscientists., Conclusions: The identified distinct anatomical patterns provide evidence for a specific interaction between tumor and anatomical structures, following a pathoclitic concept. Understanding differences in their anatomical behavior has the potential to improve our pathophysiological understanding and to tailor therapy of brain tumors.

Objective: Decision-making for intracranial tumor surgery requires balancing the oncological benefit against the risk for resection-related impairment. Risk estimates are commonly based on subjective experience and generalized numbers from the literature, but even experienced surgeons overestimate functional outcome after surgery. Today, there is no reliable and objective way to preoperatively predict an individual patient's risk of experiencing any functional impairment., Methods: The authors developed a prediction model for functional impairment at 3 to 6 months after microsurgical resection, defined as a decrease in Karnofsky Performance Status of ≥ 10 points. Two prospective registries in Switzerland and Italy were used for development. External validation was performed in 7 cohorts from Sweden, Norway, Germany, Austria, and the Netherlands. Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded. Discrimination and calibration metrics were evaluated., Results: In the development (2437 patients, 48.2% male; mean age ± SD: 55 ± 15 years) and external validation (2427 patients, 42.4% male; mean age ± SD: 58 ± 13 years) cohorts, functional impairment rates were 21.5% and 28.5%, respectively. In the development cohort, area under the curve (AUC) values of 0.72 (95% CI 0.69-0.74) were observed. In the pooled external validation cohort, the AUC was 0.72 (95% CI 0.69-0.74), confirming generalizability. Calibration plots indicated fair calibration in both cohorts. The tool has been incorporated into a web-based application available at https://neurosurgery.shinyapps.io/impairment/., Conclusions: Functional impairment after intracranial tumor surgery remains extraordinarily difficult to predict, although machine learning can help quantify risk. This externally validated prediction tool can serve as the basis for case-by-case discussions and risk-to-benefit estimation of surgical treatment in the individual patient.

Objective: The aim of this study was to identify relevant risk factors for epileptic seizures upon initial diagnosis of a brain tumor and to develop and validate a machine learning based prediction to allow for a tailored risk-based antiepileptic therapy., Methods: Clinical, electrophysiological and high-resolution imaging data was obtained from a consecutive cohort of 1051 patients with newly diagnosed brain tumors. Factor-associated seizure risk difference allowed to determine the relevance of specific topographic, demographic and histopathologic variables available at the time of diagnosis for seizure risk. The data was divided in a 70/30 ratio into a training and test set. Different machine learning based predictive models were evaluated before a generalized additive model (GAM) was selected considering its traceability while maintaining high performance. Based on a clinical stratification of the risk factors, three different GAM were trained and internally validated., Results: A total of 923 patients had full data and were included. Specific topographic anatomical patterns that drive seizure risk could be identified. The involvement of allopallial, mesopallial or primary motor/somatosensory neopallial structures by brain tumors results in a significant and clinically relevant increase in seizure risk. While topographic input was most relevant for the GAM, the best prediction was achieved by a combination of topographic, demographic and histopathologic information (Validation: AUC: 0.79, Accuracy: 0.72, Sensitivity: 0.81, Specificity: 0.66)., Conclusions: This study identifies specific phylogenetic anatomical patterns as epileptic drivers. A GAM allowed the prediction of seizure risk using topographic, demographic and histopathologic data achieving fair performance while maintaining transparency., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: Deciding whether to re-operate patients with intracranial tumor recurrence or remnant is challenging, as the data on safety of repeated procedures is limited. This study set out to evaluate the risks for morbidity, mortality, and complications after repeated operations, and to compare those to primary operations., Methods: Retrospective observational two-center study on consecutive patients undergoing microsurgical tumor resection. The data derived from independent, prospective institutional registries. The primary endpoint was morbidity at 3 months (M3), defined as significant decrease on the Karnofsky Performance Scale (KPS). Secondary endpoints were mortality, rate and severity of complications according to the Clavien-Dindo Grade (CDG)., Results: 463/2403 (19.3%) were repeated procedures. Morbidity at M3 occurred in n = 290 patients (12.1%). In univariable analysis, patients undergoing repeated surgery were 98% as likely as patients undergoing primary surgery to experience morbidity (OR 0.98, 95% CI 0.72-1.34, p = 0.889). In multivariable analysis adjusted for age, sex, tumor size, histology and posterior fossa location, the relationship remained stable (aOR 1.25, 95% CI 0.90-1.73, p = 0.186). Mortality was n = 10 (0.4%) at discharge and n = 95 (4.0%) at M3, without group differences. At least one complication occurred in n = 855, and the rate (35.5% vs. 35.9%, p = 0.892) and severity (CDG; p = 0.520) was similar after primary and repeated procedures. Results were reproduced in subgroup analyses for meningiomas, gliomas and cerebral metastases., Conclusions: Repeated surgery for intracranial tumors does not increase the risk of morbidity. Mortality, and both the rate and severity of complications are comparable to primary operations. This information is of value for patient counseling and the informed consent process.

The aim of the present study was to assess the safety of microsurgical resection of intracranial tumors performed by supervised neurosurgical residents. We analyzed prospectively collected data from our institutional patient registry and dichotomized between procedures performed by supervised neurosurgery residents (defined as teaching procedures) or board-certified faculty neurosurgeons (defined as non-teaching procedures). The primary endpoint was morbidity at discharge, defined as a postoperative decrease of ≥10 points on the Karnofsky Performance Scale (KPS). Secondary endpoints included 3-month (M3) morbidity, mortality, the in-hospital complication rate, and complication type and severity. Of 1,446 consecutive procedures, 221 (15.3%) were teaching procedures. Patients in the teaching group were as likely as patients in the non-teaching group to experience discharge morbidity in both uni- (OR 0.85, 95%CI 0.60-1.22, p = 0.391) and multivariate analysis (adjusted OR 1.08, 95%CI 0.74-1.58, p = 0.680). The results were consistent at time of the M3 follow-up and in subgroup analyses. In-hospital mortality was equally low (0.24 vs. 0%, p = 0.461) and the likelihood (p = 0.499), type (p = 0.581) and severity of complications (p = 0.373) were similar. These results suggest that microsurgical resection of carefully selected intracranial tumors can be performed safely by supervised neurosurgical residents without increasing the risk of morbidity, mortality or perioperative complications. Appropriate allocation of operations according to case complexity and the resident's experience level, however, appears essential.