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418 Dendritic cell-activation of T cells provides metabolic signals for improved <i>in vivo</i> persistence and anti-tumour performance

2024· article· en· W4404064955 on OpenAlexaff
Meghan Kates, Kieran Coppens, Carlos R. Garcia-Batres, Alisha R. Elford, Azin Sayad, Pamela S. Ohashi, Sam Saibil

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsIn vivoPersistence (discontinuity)Cell biologyCellChemistryBiologyEngineeringBiochemistryBiotechnology

Abstract

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<h3>Background</h3> Adoptive cellular therapy (ACT), such as chimeric antigen receptor (CAR)-T cell therapy, has provided impressive clinical efficacy for treatment of patients with hematological malignancies.<sup>1</sup> However, its efficacy for solid tumours has been limited<sup>2</sup> largely due to immunosuppressive signals and competition for metabolic resources in the tumour microenvironment (TME) that can limit the efficacy and killing capacity of T cells.<sup>3</sup> Overcoming these metabolic challenges is vital for enhancing the efficacy of ACT. Many strategies for reprogramming T cell metabolism have emerged in the literature, however the impact of the clinical activation strategy – bead-bound anti-CD3 and anti-CD28 antibodies – remains largely unexplored. This study aims to compare the metabolic programming, effector function, persistence and resilience to metabolic stress of T cells activated with bead-bound antibodies (beads) or with dendritic cells (DCs). <h3>Methods</h3> We isolated CD8+ T cells from P14 mice that have a transgenic T cell receptor recognizing the gp33 peptide from lymphocytic choriomeningitis virus (LCMV). These T cells are co-cultured with either LPS-activated bone-marrow derived DCs pulsed with gp33 peptide, or with beads at ratios of 1:1 or 10:1 (beads:T cells). These T cells were activated for 72 hours followed by baseline analysis, transfer into <i>in vitro</i> stress conditions, or use for ACT in mice with established B16-gp33 melanoma tumours. <h3>Results</h3> Increasing the ratio of beads resulted in increased oxidative and glycolytic metabolism to a level comparable with DC-activated T cells. Despite the comparable bioenergetic profile, DC-activated T cells demonstrated superior tumour clearance compared to all ratios of bead-activated T cells. Additionally, <i>in vivo</i> in the same TME, DC-activated T cells showed significantly improved survival, suggesting DC-activation provides additional signals that confer resiliency to stress and improved function. Similar resiliency was observed in DC-activated T cells <i>in vitro</i> after exposure to stress conditions such as IL-2 withdrawal. Metabolomics and RNA-sequencing analyses have revealed distinct signaling and phospholipid metabolism between DC and bead-activated T cells. <h3>Conclusions</h3> DC-activation of T cells provides superior programming for efficacy, survival and resiliency to stress compared to bead-activation. These enhanced metrics are associated with unique metabolic and transcriptional programming. Current investigations are ongoing to determine if altering phospholipid metabolism in bead-activated T cells is sufficient to enhance their efficacy and resilience. This could then be incorporated into clinical protocols to improve ACT outcomes for patients. <h3>References</h3> Cappell KM, Kochenderfer JN. Long-term outcomes following CAR T cell therapy: what we know so far. <i>Nat Rev Clin Oncol</i> 2023;<b>20</b>:359–71. Hou B, Tang Y, Li W, Zeng Q, Chang D. Efficiency of CAR-T therapy for treatment of solid tumor in clinical trials: a meta-analysis. <i>Dis Markers</i> 2019;<b>2019</b>:e3425291. Hou AJ, Chen LC, Chen YY. Navigating CAR-T cells through the solid-tumour microenvironment. <i>Nat Rev Drug Discov</i> 2021;<b>20</b>:531–50. <h3>Ethics Approval</h3> This study was approved by the University Health Network Animal Care Committee approval number 929 and 6895.

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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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.845

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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 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
Published2024
Admission routes1
Has abstractyes

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