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Record W4416139719 · doi:10.1093/neuonc/noaf201.1913

TMOD-40. Genetic drivers shape tumor phenotype and composition of the tumor microenvironment in syngeneic mouse models of glioblastoma

2025· article· en· W4416139719 on OpenAlexaff
Joanna Pyczek, Shannon Snelling, Xueqing Lun, Bo Young Ahn, Heewon Seo, Miranda Yu, Daniela F. Quail, A. Sorana Morrissy, Jennifer A. Chan

Bibliographic record

VenueNeuro-Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill UniversityCalgary Laboratory ServicesInstitute of Cancer ResearchMcGill University Health CentreUniversity of Calgary
Fundersnot available
KeywordsNestinTumor microenvironmentPhenotypeMesenchymal stem cellTranscriptomeGlioblastomaElectroporationInfiltration (HVAC)MicrogliaGlioma

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION Glioblastoma (GBM) poses a great challenge for therapeutics development due to its heterogeneity and the lack of immunocompetent models that faithfully recapitulate human GBM. We sought to generate and characterize syngeneic mouse models for major GBM subtypes. METHODS Postnatal electroporation using the PiggyBac transposon/transposase for overexpression (OE) and CRISPR/Cas9 for knockout (KO) was used to generate models with common GBM alterations including EGFRvIII-OE/Cdkn2a-KO/Pten-KO, Nf1-KO/Pten-KO/p53-KO, and RasV12-OE/Cdk4-OE/p53-KO. Model characterization was done by HE staining, immunofluorescence staining, RNA sequencing and flow cytometry. RESULTS All models displayed histopathological and molecular features of GBM such as pseudopalisiding necrosis, microvascular proliferation, and cellular atypia, as well as Gfap and Nestin expression. On the transcriptomic level, Nf1/Pten/p53 tumors showed enrichment for the human mesenchymal signature, while RasV12/Cdk4/p53 and EGFRvIII/Cdkn2a/Pten tumors resembled the classical and proneural signatures. Each tumor was comprised of four cellular states, i.e., astrocytic, mesenchymal, OPC-like, and NPC-like, suggestive of intratumoral heterogeneity. On examining the microenvironment, EGFRvIII/Cdkn2a/Pten tumors had a higher relative abundance of T cells (48.6% vs 6.3%, p=0.0084, 48.6% vs 8.8%, p=0.0376,), NK cells, (1.2% vs 0.4%, p=0.1425, 1.2% vs 0.19%, p=0.0315) and dendritic cells (7.5% vs 0.4%, p=0.0272) than the Nf1/Pten/p53 and RasV12/Cdk4/p53 models. RasV12/Cdk4/p53 tumors had greater infiltration of monocyte-derived macrophages than Nf1/Pten/p53 (35.9% vs 4.18%, p=0.0012) and EGFRvIII/Cdkn2a/Pten (35.9% vs 10.4%, p=0.0620) tumors as well as an elevated CD4+/CD8+ T cell ratio. In the Nf1/Pten/p53 model, microglia were the most abundant cells within the CD45+ compartment, surpassing levels observed in EGFRvIII/Cdkn2a/Pten (60.2% vs 4.6%, p=0.0548) and RasV12/Cdk4/p53 (60.2%vs7.5%, p=0.0564) tumors. CONCLUSION We developed an array of syngeneic mouse models of GBM that recapitulate human inter- and intra- tumoral heterogeneity. Future studies will define the functional states of immune cells in the microenvironment and evaluate the impact of immune cell composition on the response to immunotherapies.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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 routes1
Has abstractyes

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