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Record W4392600366 · doi:10.1016/j.xcrm.2024.101465

Ex vivo activation of the GCN2 pathway metabolically reprograms T cells, leading to enhanced adoptive cell therapy

2024· article· en· W4392600366 on OpenAlexafffund
Michael St. Paul, Samuel D. Saibil, Meghan Kates, SeongJun Han, Scott Lien, Rob C. Laister, Kebria Hezaveh, Andreas Kloetgen, Susanne Penny, Tingxi Guo, Carlos R. Garcia-Batres, Logan K. Smith, Douglas C. Chung, Alisha R. Elford, Azin Sayad, Devanand M. Pinto, Tak W. Mak, Naoto Hirano, Tracy L. McGaha, Pamela S. Ohashi

Bibliographic record

VenueCell Reports Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsNational Research Council CanadaPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchPrincess Margaret Cancer Foundation
KeywordsCell biologyEx vivoCell therapyChemistryBiophysicsBiologyStem cellBiochemistryIn vitro

Abstract

fetched live from OpenAlex

The manipulation of T cell metabolism to enhance anti-tumor activity is an area of active investigation. Here, we report that activating the amino acid starvation response in effector CD8 + T cells ex vivo using the general control non-depressible 2 (GCN2) agonist halofuginone (halo) enhances oxidative metabolism and effector function. Mechanistically, we identified autophagy coupled with the CD98-mTOR axis as key downstream mediators of the phenotype induced by halo treatment. The adoptive transfer of halo-treated CD8 + T cells into tumor-bearing mice led to robust tumor control and curative responses. Halo-treated T cells synergized in vivo with a 4-1BB agonistic antibody to control tumor growth in a mouse model resistant to immunotherapy. Importantly, treatment of human CD8 + T cells with halo resulted in similar metabolic and functional reprogramming. These findings demonstrate that activating the amino acid starvation response with the GCN2 agonist halo can enhance T cell metabolism and anti-tumor activity.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.233
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.316
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 teacher head, not a consensus.

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

Citations24
Published2024
Admission routes2
Has abstractyes

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