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Record W4380354507 · doi:10.1093/neuonc/noad073.037

BIOL-18. NEWLY DEVELOPED REPLICATION REPAIR DEFICIENT (RRD) MOUSE MODELS PROVIDE INSIGHTS INTO MEDULLOBLASTOMA/GLIOMAGENESIS AND RESPONSE TO IMMUNOTHERAPY

2023· article· en· W4380354507 on OpenAlexaff
Zoya Aamir, Melissa A. Galati, Emma Gattoni, Owen Crump, Nuno M. Nunes, Anirban Das, Nicholas R. Fernandez, Angel K Q Wong, Jérôme Fortin, Lucie Stengs, Vanessa Bianchi, Melissa Edwards, Logine Negm, Jiil Chung, David Malkin, Sean E. Egan, Cynthia Hawkins, Uri Tabori

Bibliographic record

VenueNeuro-Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsQueen's UniversityPrincess Margaret Cancer CentreHospital for Sick Children
Fundersnot available
KeywordsOLIG2MedulloblastomaCancer researchNestinGliomaBiologyGermlineMLH1Germline mutationDNA mismatch repairMutationGeneticsStem cellGeneDNA repairNeural stem cellNeuroscienceOligodendrocyteMyelinCentral nervous system

Abstract

fetched live from OpenAlex

Abstract Replication Repair Deficiency (RRD), caused by germline monoallelic (Lynch Syndrome) or biallelic (Constitutional Mismatch Repair Deficiency, CMMRD) mutations in MMR genes, is present in 5-10% of glioblastomas in children, adolescents, and young adults. RRD glioblastomas are chemoradiation-resistant, but respond favorably to immune checkpoint inhibition (ICI). Representative immunocompetent animal models are urgently needed for 3 recently identified subgroups based on specific somatically-acquired mutations, survival, and immunotherapy response (RRD1: MMRD with POLE mutations, RRD2: MMRD associated with TP53 mutations, and RRD3: MMRD harboring IDH1 mutations). Using germline mutations and brain-specific Cre-drivers, we genetically engineered mouse models that recapitulate each human RRD-subgroup. RRD1 (Nestin- and Olig2-Cre+/ Msh2LoxP/LoxP/PoleS459F/+ and LSL-PoleP286R/+): CMMRD-like Nestin-Cre-driven mice develop posterior-fossa glioma-like or medulloblastoma (MB)-like tumors at ~2.7 months. Olig2-Cre-driven mice display hemispheric gliomas at ~10 months, suggesting distinct cell-of-origin. RRD2 (Nestin-Cre+/Trp53LoxP/LoxP and Msh2LoxP/LoxP or Mlh1-/-): CMMRD-like tumors develop in heterogenous locations at ~4.5 months (p<0.0001), classifying primarily as MB-like in hindbrain, and glioma-like in other brain regions. Strikingly, germline Mlh1 tumors occur earlier than Nestin-Cre-driven RRD2 tumors, indicating early developmental mutation accumulation in CMMRD-patients. Lynch-like RRD1/2 mice succumb exclusively to gliomas >13 months (p<0.0001). RRD3 (Olig2-Cre+/Msh2LoxP/LoxP/Trp53LoxP/LoxP/LSL-Idh1R132H/+): brain tumors occur later and are hemispheric. These observations recapitulate human data, where CMMRD-patients develop glioblastoma/MB earlier than Lynch-patients (8.6 vs. 14-years; p<0.0001), and posterior-fossa glioblastoma/MB presents earlier than hemispheric gliomas (p=0.04). Additionally, tumor onset and location vary (RRD1: 7.6-years, RRD2: 8.3-years, hemispheric/posterior-fossa; RRD3: 12-years, hemispheric; p=0.005). In both mice and humans, RRD1 exhibits ultra-hypermutation, high immune infiltration, and response to ICI, whereas RRD2 harbors lower mutational burden, are immune-cold, and ICI-monotherapy resistant. Temporal dynamics of RRD tumor development is currently being tracked by serial MRI to define biologically relevant time points. Our models accurately mimic the human condition and provide unique insights into RRD tumorigenesis, allowing optimization of subgroup-tailored therapeutic approaches.

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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.044
GPT teacher head0.330
Teacher spread0.286 · 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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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