Cytotoxic and Regulatory Properties of Circulating Vδ1+ γδ T Cells: A New Player on the Cell Therapy Field?
Bibliographic record
Abstract
Exploration of cancer immunotherapy strategies that incorporate γδ T cells as primary mediators of antitumor immunity are just beginning to be explored and with a primary focus on the use of manufactured phosphoantigen-stimulated Vγ9Vδ2 T cells. Increasing evidence, however, supports a critical role for Vδ1+ γδ T cells, a minor subset in peripheral blood with distinct innate recognition properties that possess powerful tumoricidal activity. They are activated by a host of ligands including stress-induced self-antigens, glycolipids presented by CD1c/d, and potentially many others that currently remain unidentified. In contrast to Vγ9Vδ2 T cells, tumor-reactive Vδ1+ T cells are not as susceptible to activation-induced cell death and can persist in the circulation for many years, potentially offering durable immunity to some cancers. In addition, specific populations of Vδ1+ T cells can also exhibit immunosuppressive and regulatory properties, a function that can also be exploited for therapeutic purposes. This review explores the biology, function, manufacturing strategies, and potential therapeutic role of Vδ1+ T cells. We also discuss clinical experience with Vδ1+ T cells in the setting of cancer, as well as the potential of and barriers to the development of Vδ1+ T cell-based adoptive cell therapy strategies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".