A soluble activator that favors the ex vivo expansion of CD8+CD27+ T cells
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".