Anti-Leukemia Activity of In Vitro-Expanded Human Gamma Delta T Cells in a Xenogeneic Ph+ Leukemia Model
Bibliographic record
Abstract
Gamma delta T cells (GDTc) lyse a variety of hematological and solid tumour cells in vitro and in vivo, and are thus promising candidates for cellular immunotherapy. We have developed a protocol to expand human GDTc in vitro, yielding highly cytotoxic Vgamma9/Vdelta2 CD27/CD45RA double negative effector memory cells. These cells express CD16, CD45RO, CD56, CD95 and NKG2D. Flow cytometric, clonogenic, and chromium release assays confirmed their specific cytotoxicity against Ph(+) cell lines in vitro. We have generated a fluorescent and bioluminescent Ph(+) cell line, EM-2eGFPluc, and established a novel xenogeneic leukemia model. Intravenous injection of EM-2eGFPluc into NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice resulted in significant dose-dependent bone marrow engraftment; lower levels engrafted in blood, lung, liver and spleen. In vitro-expanded human GDTc injected intraperitoneally were found at higher levels in blood and organs compared to those injected intravenously; GDTc survived at least 33 days post-injection. In therapy experiments, we documented decreased bone marrow leukemia burden in mice treated with GDTc. Live GDTc were found in spleen and bone marrow at endpoint, suggesting the potential usefulness of this 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) | 0.001 | 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 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".