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Record W4414786598 · doi:10.1093/neuonc/noaf193.335

P10.24.A TARGETING NON-GENETIC KINASE-DEPENDENT SIGNALING TO PREVENT GROUP 3 MEDULLOBLASTOMA RECURRENCE

2025· article· en· W4414786598 on OpenAlexaffabout
Helgi Kuzmychova, Uma Chawla, Emma Martell, Harshal Senthil, A. Grewal, Chirag Jain, Chitra Venugopal, Sheila K. Singh, Tanveer Sharif

Bibliographic record

VenueNeuro-Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsMcMaster UniversityUniversity of Manitoba
Fundersnot available
KeywordsMedulloblastomaHedgehog signaling pathwayDownregulation and upregulationSignal transductionKinaseSonic hedgehogIn vivoHedgehog

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Brain tumors are the leading cause of cancer-related death in children, with medulloblastoma (MB) comprising 20-25% of cases. Proteogenomic profiling categorizes MB into four subgroups: Wingless (WNT), Sonic Hedgehog (SHH), Group 4 (G4), and Group 3 (G3), with G3 MB being the most aggressive one. Despite intensive chemoradiotherapy (CRT), which often leads to long-term side effects, G3 MB is prone to develop treatment-resistant relapse tumors, resulting in a five-year survival rate below 60%. Genomic analyses show that recurrent tumors retain their original genomic features, suggesting that changes in non-genomic signaling pathways drive relapse. Kinases, as central regulators of phosphorylation-driven signaling, can control pathways involved in proliferation, migration, and survival. We hypothesize that kinase-driven changes in signaling pathways underlie treatment resistance and tumor relapse in G3 MB. Understanding these adaptations will provide insights into novel therapeutic strategies for targeting recurrent MB. MATERIAL AND METHODS We used well-characterized MB cell lines and orthotopic intracerebellar patient-derived xenograft (PDOX) mouse models treated with a clinically relevant CRT regimen. Kinase activity changes were assessed via human phospho-kinase arrays, immunoblotting, and immunohistochemistry. The efficacy of kinase inhibitors in combination with CRT treatment was evaluated in vitro using viability, tumorsphere formation, and migration assays, and in vivo by assessing tumor progression and animal survival. RESULTS CRT-resistant G3 MB cells showed elevated activating phosphorylation of Src kinase and its downstream targets, with minimal changes in other key oncogenic kinases. Notably, upregulation of p-Src was not observed in CRT-treated SHH MB cells or normal human stem cells, suggesting a tumor- and subgroup-specific adaptation. G3 MB CRT-resistant cells demonstrated marked sensitivity towards repurposed FDA-approved brain-penetrant Src inhibitors, which significantly impaired their stemness and migratory potential in vitro and extended animal survival in the CRT PDOX animal model. CONCLUSION These results identify Src signaling as a subgroup-specific driver of therapy resistance and recurrence in G3 MB. Targeting this pathway may offer a promising therapeutic strategy to combat CRT resistance in recurrent G3 MB to ultimately improve patient outcomes. SUPPORT This work was supported by the Canadian Institute of Health Research (CIHR), Canadian Cancer Society (CCS), Cancer Research Society (CRS), and Natural Sciences and Engineering Research Council of Canada (NSERC).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.331
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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