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Record W2769000166 · doi:10.3389/fimmu.2017.01653

Glycogen Synthase Kinase 3 Inactivation Compensates for the Lack of CD28 in the Priming of CD8+ Cytotoxic T-Cells: Implications for anti-PD-1 Immunotherapy

2017· article· en· W2769000166 on OpenAlexaff
Alison Taylor, Christopher E. Rudd

Bibliographic record

VenueFrontiers in Immunology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersCancer Research UKWellcome TrustWellcome
KeywordsCytotoxic T cellPriming (agriculture)GSK-3CD28CD8ImmunotherapyCancer researchChemistryBiologyBiochemistryKinaseImmunologyImmune systemIn vitro

Abstract

fetched live from OpenAlex

The rescue of exhausted CD8+ cytolytic T-cells (CTLs) by anti-PD-1 blockade has been found to require CD28 expression. At the same time, we have shown that the inactivation of the serine/threonine kinase GSK-3α/β with small interfering RNAs (siRNAs) and small molecule inhibitors (SMIs) specifically down-regulate PD-1 expression for enhanced CD8+ CTL function and clearance of tumours and viral infections. Despite this, it has been unclear whether the GSK-3α/β pathway accounts for CD28 co-stimulation of CD8+ CTL function. In this paper, we show that inactivation of GSK-3α/β through siRNA or by SMIs during priming can substitute CD28 stimulation in the potentiation of cytotoxic CD8+ CTL function. This increased response was observed in the blockade of CD28 co-receptor by CTLA-4-IgG in OT-1 T-cells responding to OVA peptide as presented by the lymphoma cell line EL4. The effect was seen using several GSK-3 SMIs, and was accompanied by an increase in Lamp-1 and GZMB expression. Conversely, CD28 crosslinking obviated the need for GSK-3α/β inhibition in its enhancement of CTL function. Our findings support a model where GSK-3 is the central co-signal for CD28 priming of CD8+ CTLs in anti-PD-1 immunotherapy. □

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.160
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

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

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 head0.040
GPT teacher head0.302
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations63
Published2017
Admission routes1
Has abstractyes

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