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Record W3103985965 · doi:10.1172/jci.insight.141293

A soluble activator that favors the ex vivo expansion of CD8+CD27+ T cells

2020· article· en· W3103985965 on OpenAlexafffund
Esther Matus, Amanda Sparkes, Jean Gariépy

Bibliographic record

VenueJCI Insight · 2020
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of TorontoSunnybrook Hospital
FundersCanadian Institutes of Health Research
KeywordsCD28Ex vivoCytotoxic T cellT cellCD8ChemistryPopulationCell biologyMolecular biologyBiologyImmunologyIn vitroImmune systemBiochemistryMedicine

Abstract

fetched live from OpenAlex

Adoptive cell therapy involves the infusion of tumor-reactive T cells into patients with cancer to provide antitumor immunity. The ex vivo expansion and differentiation of such T cells are key parameters that affect their therapeutic potential. Human T cells are presently expanded in culture through the use of anti-CD3 and anti-CD28 mAbs immobilized on beads, expressed on cells, or assembled in the context of soluble antibody complexes. Here we report the design of a small, bispecific single-chain variable fragment construct agonizing both CD3 and CD28 pathways. This soluble T cell expansion protein, termed T-CEP, activates, expands, and differentiates human T cells ex vivo at concentrations in the femtomolar range. Importantly, T-CEP promotes the preferential growth of human CD8+ T cells over the course of 12 days in comparison with methods involving immobilized anti-CD3 mAb/soluble anti-CD28 mAb or soluble anti-CD3/CD28 mAb complexes. The differentiation profile of the resulting human T cell population is also singularly affected by T-CEP, favoring the expansion of a preferred CD8+CD27+ T cell phenotype. The activity profile of T-CEP on human T cells ex vivo suggests its use in generating human T cell populations that are more suited for adoptive cell therapy.

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 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 score0.266
Threshold uncertainty score0.995

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)0.0060.000

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 head0.062
GPT teacher head0.301
Teacher spread0.239 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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