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Record W4399787504 · doi:10.1093/neuonc/noae064.378

IMMU-07. COMBINED PD1 AND LAG3 INHIBITION IN PRECLINICAL MODELS AND PATIENTS WITH DNA REPLICATION REPAIR DEFICIENT GLIOBLASTOMA (RRD-GBM): AN IRRDC STUDY

2024· article· en· W4399787504 on OpenAlexaff
Anirban Das, Owen Crump, Olha Kos, Lucie Stengs, Amanda Li, Adrian Levine, Yoshiko Nakano, Alexander Stein, Gadi Abebe‐Campino, Annika Bronsema, Vanessa Bianchi, Melissa Edwards, Stergios Zacharoulis, Birgit Ertl-Wagner, Daniel A. Morgenstern, Trevor J. Pugh, Pamela S. Ohashi, Éric Bouffet, Cynthia Hawkins, Peter B. Dirks, Uri Tabori

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreHospital for Sick Children
Fundersnot available
KeywordsCancer researchImmune checkpointImmune systemCD8ImmunotherapyMedicineNestinBiologyImmunologyStem cellNeural stem cellCell biology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND RRD-GBM harbour high tumor mutation burden (TMB) and respond to anti-PD1 immune checkpoint inhibition (ICI). However, the majority ultimately progress, highlighting the need for combinatorial therapies for sustained immune-surveillance. METHODS We performed transcriptomic analyses of human RRD-GBM specimens for immune checkpoint expression, and accordingly, tested combined ICI in immunocompetent murine models. Based on these preclinical data, we treated refractory patients using a combination of anti-PD1 and anti-LAG3 through single-patient trials/ compassionate access. Complimentary immuno-genomic biomarker analyses including circulating tumor DNA (ctDNA) were performed to study mechanisms and track responses. RESULTS Human RRD-GBM (n=80) demonstrated high LAG3 expression, providing a strong rationale for targeting. We tested combined anti-PD1 and anti-LAG3 inhibition in three immunocompetent RRD-GBM murine models. In the anti-PD1-responsive (Nestin-Cre-MSH2LoxP/LoxP-POLES459F/+) model, combined inhibition resulted in universal tumor response and survival. In the anti-PD1 resistant models (Mlh1-/-/Nestin-Cre+/Trp53LoxP/LoxP and therapy-induced hypermutant ENU/Trp53-/- gliomas), the combination improved survival despite a lack of response to anti-PD1 monotherapy. Biologically, high LAG3 expression and exhaustion was observed in CD8 T-cells after treatment with anti-PD1, which was subsequently ablated by the addition of anti-LAG3. Serially transplanted mice showed response and improved survival to the combination, suggesting that resistance to anti-PD1 could be abrogated by the combination. Four patients with RRD-GBM who had failed anti-PD1 treatment were treated using the combination, resulting in objective radiological responses and prolonged ongoing survival in patients with RRD-GBM and high LAG3 expression. Tolerability was better than a previous study of combined CTLA4 and PD1 inhibition for similar patients. Correlation with paired immuno-genomic tumor analyses, flow-cytometry, T-cell receptor clonotype and CSF ctDNA are ongoing prospectively. CONCLUSION LAG3 is an effective target in refractory RRD-GBM. Combined inhibition with anti-PD1 inhibition demonstrated radiological response, prolonged survival and manageable toxicities in patients, and will be tested in future clinical trials.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

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

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 head0.031
GPT teacher head0.331
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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