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Record W2077416999 · doi:10.1002/cyto.b.20115

Flow cytometric assessment of autologous γδ T cells in patients with acute myeloid leukemia: Potential effector cells for immunotherapy?

2006· article· en· W2077416999 on OpenAlexafffund
Jorg M Aswald, Xinghua Wang, S. Aswald, Andrzej Lutynski, Mark D. Minden, Hans A. Messner, Armand Keating

Bibliographic record

VenueCytometry Part B Clinical Cytometry · 2006
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
FundersUniversity Health Network
KeywordsMedicineImmunophenotypingImmunologyImmunotherapyBone marrowMyeloidT cellFlow cytometryMyeloid leukemiaMinimal residual diseaseImmune systemPopulationLeukemia

Abstract

fetched live from OpenAlex

BACKGROUND: Gammadelta T cells are a rare component of the circulating innate immune system capable of exerting anti-neoplastic activity. This population may be suitable for the adoptive immunotherapy of acute myeloid leukemia (AML). Little is known however, about the frequency and function of circulating gammadelta T cells in AML. The aim of the study was to enumerate peripheral blood gammadelta T cells in patients with AML and explore the feasibility of their use clinically. METHODS: We compared the absolute circulating gammadelta T cell levels in 33 AML patients before and after treatment versus 20 healthy volunteers using flow cytometry. The function of gammadelta T cells was assessed by detection of intracelluar interferon-gamma (IFN-gamma) and cytotoxicity against leukemic blasts. RESULTS: AML patients with high blast counts prior to induction chemotherapy had marginally decreased gammadelta T cell levels compared with healthy controls: median 38/microL versus 83/microL; P = 0.051. Sequential gammadelta T cell enumeration after induction showed significantly decreased counts in patients with a persistently high blast burden compared to patients with reduced but detectable residual disease (molecular maker or borderline bone marrow infiltration): median 7/microL versus 105/microL; P = 0.008. Patients with residual disease had significantly higher gammadelta T cell counts compared to those retested after they had achieved complete remission (CR); P = 0.0025. In CR, gammadelta T cell counts remained lower than those of healthy individuals: median 33/microL versus 83/microL, P = 0.030. We detected a sharp increase (on average, four-fold higher than values in CR) of gammadelta T cells in patients in very early morphologic or molecular relapse. We also tested the functional properties of gammadelta T cells from patients with AML in CR. Flow cytometric assessment of IFN-gamma revealed similar numbers of gammadelta T cells expressing the T1 cytokine compared with healthy controls. We also showed that gammadelta T cells were able to kill leukemic target cells in vitro. CONCLUSION: Flow cytometric assessment of gammadelta T cells in patients with AML revealed quantitative shifts with respect to disease status. Our data suggest that gammadelta T cells warrant further investigation as potential therapeutic agents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.020
GPT teacher head0.354
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2006
Admission routes2
Has abstractyes

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