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Record W1979942820 · doi:10.1002/ijc.10325

Adenosine acts through an A<sub>3</sub> receptor to prevent the induction of murine anti‐CD3‐activated killer T cells

2002· article· en· W1979942820 on OpenAlexafffund
David W. Hoskin, Dennis Drapeau, S.M. Mansour Haeryfar, Jonathan Blay

Bibliographic record

VenueInternational Journal of Cancer · 2002
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsDalhousie University
FundersFaculty of Medicine, Dalhousie UniversityKillam TrustsDalhousie UniversityNatural Sciences and Engineering Research Council of CanadaDalhousie Medical Research Foundation
KeywordsAdenosineCytotoxic T cellBiologyAdenosine A2B receptorAdenosine receptorAdenosine deaminaseAdenosine A3 receptorT cellMolecular biologyReceptorEndocrinologyBiochemistryImmunologyImmune systemAgonistIn vitro

Abstract

fetched live from OpenAlex

Adenosine, a purine nucleoside found at high levels in solid tumors, is able to suppress the recognition/adhesion and effector phases of killer lymphocyte-mediated tumor cell destruction. Here, we demonstrate that adenosine, at concentrations that are typically present in the extracellular fluid of solid tumors, exerts a profound inhibitory effect on the induction of mouse cytotoxic T cells, without substantially affecting T-cell viability. T-cell proliferation in response to mitogenic anti-CD3 antibody was impaired in the presence of 10 microM adenosine (plus coformycin to inhibit endogenous adenosine deaminase). Antigen-specific T-cell proliferation was similarly inhibited by adenosine. Anti-CD3-activated killer T (AK-T) cells induced in the presence of adenosine exhibited reduced major histocompatibility complex-unrestricted cytotoxicity against P815 mastocytoma cells in JAM and (51)Cr-release assays. Diminished tumoricidal activity correlated with reduced expression of mRNAs coding for granzyme B, perforin, Fas ligand and tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), as well as with diminished Nalpha-CBZ-L-lysine thiobenzylester (BLT) esterase activity. Interleukin-2 and interferon-gamma synthesis by AK-T cells was also inhibited by adenosine. AK-T cells express mRNA coding for A(2A), A(2B) and A(3) receptors, but little or no mRNA coding for A(1) receptors. The inhibitory effect of adenosine on AK-T cell proliferation was blocked by an A(3) receptor antagonist (MRS1191) but not by an A(2) receptor antagonist (3,7-dimethyl-1-propargylxanthine [DMPX]). The A(3) receptor agonists (N(6)-2-(4-aminophenyl)ethyladenosine [APNEA] and N(6)-benzyl-5'-N-ethylcarboxamidoadenosine [N(6)-benzyl-NECA]) also inhibited AK-T cell proliferation. Adenosine, therefore, acts through an A(3) receptor to prevent AK-T cell induction. Tumor-associated adenosine may act through the same mechanism to impair the development of tumor-reactive T cells in cancer patients.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.110
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.042
GPT teacher head0.354
Teacher spread0.312 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations76
Published2002
Admission routes2
Has abstractyes

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