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384 Features of neoantigen-reactive T cells with <i>ex vivo</i> expansion capacity

2025· article· W4415898841 on OpenAlexaff
Antoine Bernard, Nathalie Brassard, Mayra Carneiro, Mathieu Gigoux, Renata Kosovskaia, Larissa A. Pikor, Niloufar Khojandi, David F. Stojdl, Barbara Sennino, Simon Turcotte

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2025
Typearticle
Language
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsT cellT lymphocyteWork (physics)Population

Abstract

fetched live from OpenAlex

Background A high number of neoantigen-reactive tumor-infiltrating T lymphocytes (TIL) for adoptive transfer immunotherapy is a key mediator of clinical responses in metastatic melanoma and gastrointestinal cancers. 1 2 However, the baseline molecular features defining neoantigen-reactive TIL with ex vivo proliferative capacity remain poorly defined, which in turn limits the development of novel manufacturing methods and patient-selection criteria.Methods We analyzed 21 tumors from patients with colorectal, lung, ovarian, and melanoma cancers. Primary expansion of TIL from tumors was obtained with IL-2, followed by a standard bulk rapid expansion protocol (bulkREP) with irradiated allogeneic PBMC feeders, OKT3 and IL-2, and in parallel, a REP of TIL sorted based on their reactivity to predicted neoantigen peptides pulsed on autologous APC (neoREP). Single-cell CITEseq, RNA and TCR-seq ( n = 13) were performed at baseline in TIL from fresh tumors combined with flow cytometry and bulk TCR-seq, and ex vivo expansion was tracked with bulk TCR sequencing after primary expansion and REP.Results Flow cytometry and bulk TCR-seq revealed substantial clonotype attrition during REP, especially among CD8 + T cells, regardless of enrichment for neoantigen-reactivity. From the baseline single-cell analysis of 41,966 TIL, the starting frequency of predicted neoantigen-reactive TIL inferred from the most validated published gene signatures 3 was not predictive of neoantigen reactivity after primary expansion, bulkREP, or neoREP. However, neoantigen-reactive and ex vivo proliferative TIL (neoTILprolif) arose from specific cell clusters. In CD4+ T cells, follicular-like T cells expressing CXCL13 represented the main source, while in CD8+ T cells, clusters of already proliferative T cells and of GZMK-expressing effector memory cells sourced most cells, contrasting with a low input from tissue-resident memory T cells. Genes most highly expressed in neoTILprolif had little overlap with gene signatures that only predicted neoantigen reactivity. By differential protein expression analysis, the integrin α2 (CD49b) and PD-1 significantly distinguished both CD4+ and CD8+ neoTILprolif from neoantigen-reactive TIL that contracted in cultures, as well as from proliferative, naïve-like, bystanders.Conclusions Neoantigen-reactive TIL with ex vivo proliferative potential constitute a minority of T cells in tumors and have a unique transcriptomic profile and cell surface protein expression to guide antigen-agnostic manufacturing of T cells more likely to mediate clinical response.Acknowledgements This work was supported by preclinical research funding from Turnstone Biologics.References Kristensen NP, Heeke C, Tvingsholm SA, et al. Neoantigen-reactive CD8+ T cells affect clinical outcome of adoptive cell therapy with tumor-infiltrating lymphocytes in melanoma. J Clin Investig 2022;132:e150535.Lowery FJ, Goff SL, Gasmi B, et al. Neoantigen-specific tumor-infiltrating lymphocytes in gastrointestinal cancers: a phase 2 trial. Nat Med 2025;1–10.Lowery FJ, Krishna S, Yossef R, et al. Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers. Science 2022;375:877–84.Ethics Approval This study was approved by the Centre hospitalier de l’Université de Montréal Institutional Review Board, approval number 21.299.

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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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0040.001

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 head0.009
GPT teacher head0.206
Teacher spread0.198 · 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
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