Apoptosis Induced via Gamma Delta T Cell Antigen Receptor “Blocking” Antibodies: A Cautionary Tale
Bibliographic record
Abstract
Mechanistic studies contribute greatly to our understanding of γδ T cell (γδTc) biology, aiding development of these cells as immunotherapeutic agents. The antibody blocking assay is an accepted method to determine the receptors involved in γδTc killing of tumor targets. Effectors and/or targets are preincubated with microgram quantities of monoclonal antibodies (mAb), often described by commercial sources to be useful for blocking assays. We and others have used such assays extensively in the past, correlating decreases in cytotoxicity against specific targets with involvement of the blocked receptor(s). However, we wondered whether other mechanisms might be at play beyond cytotoxicity inhibition. Indeed, administration of certain "blocking" mAb to the γδ T cell antigen receptor (γδTCR) induced γδTc death. Upon further investigation, we discovered that γδTc underwent apoptosis triggered by incubation with mAb to the γδTCR. This effect was specific, as no apoptosis was observed when αβ T cells (αβTc) were incubated with these mAb. Apoptosis was further potentiated by the presence of interleukin (IL)-2, often included in cytotoxicity assays; however, exogenous interleukin-2 (IL-2) did not contribute significantly to γδTc cytotoxicity against breast cancer cell lines. Here, we have investigated the usefulness of four mAb for use in blocking assays by assessing blocking properties in conjunction with their propensity to induce apoptosis in cultured primary human γδTc. We found that the 5A6.E9 clone was usually a better alternative to the commonly used B1 (or B1.1) and 11F2 clones; however, some variability in susceptibility to apoptosis induction was observed among donor cultures. Thus, viability assessment of primary effector cells treated with mAb alone should be undertaken in parallel with cytotoxicity assays employing blocking antibodies, to account for cytotoxicity reduction caused by effector cell death. Previous findings should be reassessed in this light.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".