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Record W2767090199 · doi:10.1158/1078-0432.ccr-17-2228

Allogeneic Human Double Negative T Cells as a Novel Immunotherapy for Acute Myeloid Leukemia and Its Underlying Mechanisms

2017· article· en· W2767090199 on OpenAlex
Jong Bok Lee, Mark D. Minden, Weihsu C. Chen, Elena Streck, Branson Chen, Hyeonjeong Kang, Andrea Arruda, Dalam Ly, Sandy D. Der, Sohyeong Kang, Paulina Achita, Cheryl D’Souza, Yueyang Li, Richard Childs, John E. Dick, Li Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Cancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsAmgen (Canada)Princess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchNational Institutes of HealthCanadian Cancer SocietyLeukemia and Lymphoma Society
KeywordsMyeloid leukemiaImmunotherapyLeukemiaMedicineImmunologyMyeloidCancer researchBiologyImmune system

Abstract

fetched live from OpenAlex

Abstract Purpose: To explore the potential of ex vivo expanded healthy donor–derived allogeneic CD4 and CD8 double-negative cells (DNT) as a novel cellular immunotherapy for leukemia patients. Experimental Design: Clinical-grade DNTs from peripheral blood of healthy donors were expanded and their antileukemic activity and safety were examined using flow cytometry–based in vitro killing assays and xenograft models against AML patient blasts and healthy donor–derived hematopoietic cells. Mechanism of action was investigated using antibody-mediated blocking assays and recombinant protein treatment assays. Results: Expanded DNTs from healthy donors target a majority (36/46) of primary AML cells, including 9 chemotherapy-resistant patient samples in vitro, and significantly reduce the leukemia load in patient-derived xenograft models in a DNT donor–unrestricted manner. Importantly, allogeneic DNTs do not attack normal hematopoietic cells or affect hematopoietic stem/progenitor cell engraftment and differentiation, or cause xenogeneic GVHD in recipients. Mechanistically, DNTs express high levels of NKG2D and DNAM-1 that bind to cognate ligands preferentially expressed on AML cells. Upon recognition of AML cells, DNTs rapidly release IFNγ, which further increases NKG2D and DNAM-1 ligands’ expression on AML cells. IFNγ pretreatment enhances the susceptibility of AML cells to DNT-mediated cytotoxicity, including primary AML samples that are otherwise resistant to DNTs, and the effect of IFNγ treatment is abrogated by NKG2D and DNAM-1–blocking antibodies. Conclusions: This study supports healthy donor–derived allogeneic DNTs as a therapy to treat patients with chemotherapy-resistant AML and also reveals interrelated roles of NKG2D, DNAM-1, and IFNγ in selective targeting of AML by DNTs. Clin Cancer Res; 24(2); 370–82. ©2017 AACR.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.424
GPT teacher head0.583
Teacher spread0.159 · 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