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Record W2913199767 · doi:10.1182/blood-2018-99-119045

T Cells Engineered with T Cell Antigen Coupler (TAC) Receptors for Haematological Malignancies

2018· article· en· W2913199767 on OpenAlexaff
Christopher W. Helsen, Vivian Wing Chong Lau, Joanne A. Hammill, Kenneth A. Mwawasi, Danielle L Hayes, Arya Afsahi, Ksenia Bezverbnaya, Craig Aarts, Galina Denisova, Jonathan L. Bramson

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsTrillium Therapeutics (Canada)McMaster University
Fundersnot available
KeywordsChimeric antigen receptorCytotoxic T cellAntigenCancer researchT-cell receptorImmunologyBiologyT cellCytokineCD19Antigen-presenting cellMolecular biologyImmune systemIn vitroBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background: We recently described the T cell antigen coupler (TAC) technology (Helsen et. al. Nature Communications) which is a chimeric receptor that targets antigens in an MHC-independent fashion and activates T cells by co-opting the natural TCR receptor. In vitro and in vivo assessments of TAC T cells in solid tumor models have revealed that TACs mediate biological effects that are distinct from conventional chimeric antigen receptors (CARs) and offer safety advantages, including greater target selectivity and reduced off-target toxicity. Here, we present in vitro and in vivo data showing that TAC-engineered T cells directed against CD19 and BCMA demonstrate robust anti-tumor efficacy in haematological malignancies with no detectable side effects. Materials and Methods: T cells from health donors were engineered with TAC receptors directed against CD19 or BCMA using lentivirus vectors. Flow cytometry was employed to measure surface expression of TAC receptors, cytokine production and proliferation of TAC T cells following stimulation with relevant target cells. Antigen-specific toxicity was measured using a luciferase-based killing assay. Anti-tumor activity was measured against acute lymphoblast leukemia for CD19 and multiple myeloma for BCMA xenografts in immunodeficient NRG mice. Results: Engineering T cells with TAC receptors targeted against either CD19 or BCMA revealed antigen-specific activation of cytokine production, cytotoxic function and proliferation. TAC T cells, but not CAR engineered T cells, show significant selectivity towards the context of antigen presentation. This is reflected by the differential proliferative response to a diverse framework of antigen surface arrangement, potentially indicating that TAC T cells are less susceptible to off target activation and the resulting toxicities. Treatment of established NALM-6 xenografts (acute lymphoblastic leukemia) and KMS-11 xenografts (multiple myeloma) with CD19 TAC T cells and BCMA TAC T cells, respectively, resulted in clearance of tumors within a few weeks of T cell infusion. Mice that cleared tumors following TAC T cell treatment were resistant to subsequent challenge with fresh tumor cells demonstrating persistence of TAC T cells. Treatment with control TAC T cells that carry no binding domain had no impact on tumor growth. Monitoring of TAC T cells post-infusion revealed robust expansion that peaked in the peripheral blood 1-2 weeks post-infusion. A clinical manufacturing protocol has been developed for the CD19 TAC T cells in anticipation of human trials. Conclusion: Our pre-clinical evaluation suggests that TAC therapy has the potential to becoming a safer and more effective alternative to conventional CAR therapy. A first in human Phase I/II trial with CD19 TAC T cells is expected to start in the first half of 2019. Disclosures Helsen: Triumvira Immunologics: Employment, Patents & Royalties. Hammill:Triumvira Immunologics: Other: Holding shares, Patents & Royalties. Mwawasi:Triumvira Immunologics: Other: Holding shares, Patents & Royalties. Hayes:Triumvira Immunologics: Employment. Afsahi:Triumvira Immunologics: Patents & Royalties. Denisova:Triumvira Immunologics: Patents & Royalties. Bramson:Triumvira Immunologics: Employment, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.274
Teacher spread0.248 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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