Chimeric CD3ζ chains containing CD28 signalling motifs enhance antigen-specific IL-2 production and expansion of human TCR-engineered T cells <i>in vitro</i>
Bibliographic record
Abstract
Abstract Gene-engineered T-cell products have been developed for immunotherapy to treat cancers, with great success observed in haematological malignancies but limited efficacy in treating solid cancers. TCR-engineered T cells utilize transferred TCRs targeting tumour-associated and cancer-specific peptides presented by MHC molecules. The CD3ζ chains are part of the TCR-CD3 complex expressed by T cells and mediate signal transduction when the TCR binds to MHC-presented peptides. In this study, we explored whether co-stimulation domains, that were effective in improving the function of T cells engineered with chimeric antigen receptors (CARs), can be exploited to improve the functionality of TCR-engineered T cells. We inserted the signalling domains of CD28 or 4–1BB at the membrane proximal or the membrane distal position of the intracellular tail of CD3ζ and engineered human T cells to express a specific TCR in combination with either modified CD3ζ or unmodified control. Antigen-specific in vitro stimulation assays revealed that T cells expressing CD3ζ constructs with CD28 signal domains displayed enhanced peptide-specific IL-2 production and, following repeated antigen stimulation, expanded to substantially greater numbers than T cells expressing unmodified CD3ζ. Importantly, greater expansion seen with the CD28-containing ζ did not result in any reduction of effector function as assessed by peptide-specific cytotoxicity and cytokine production. The data indicate that modification of the CD3ζ chain with a CD28 signal motif provides an opportunity to improve antigen-specific expansion and effector function of TCR-engineered T cells by combining signal 1 and co-stimulatory signal 2 in one molecular TCR-CD3 complex.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".