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Record W2886442897 · doi:10.1158/1538-7445.am2018-1696

Abstract 1696: Glycogen synthase kinase (GSK-3) inactivation downregulates PD-1 and synergizes with PD-1/PL1 and CTLA-4 blockade in cancer immunotherapy

2018· article· en· W2886442897 on OpenAlexaff
Christopher E. Rudd

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsGranzyme BGSK-3Cancer researchImmune checkpointChemistryCytotoxic T cellCancer immunotherapyCD8CTLA-4ImmunotherapyImmune systemBiologyImmunologyKinaseBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Abstract Immune checkpoint blockade (ICB) of negative co-receptors on T-cells such as cytotoxic T-cell antigen-4 (CTLA-4) and programmed cell death-1 (PD-1) is a promising approach for the treatment of cancer. Despite this success, the poor prognosis for most patients continues to highlight a need for developing novel clinical interventions. In this context, we identified the enzyme glycogen synthase kinase-3 (GSK-3) as the major regulator of PD-1 expression on T-cells (Taylor et al., 2016 Immunity). We have shown that small molecule inhibitors (SMIs) of GSK-3 are as effective as anti-PD-1 in controlling the growth of B16 melanoma, or EL4 lymphoma, in primary tumor and metastatic settings (Taylor et al., 2017 Can Res; Krueger and Rudd, Immunity 2017). At the same time, the fact that GSK-3 inactivation up-regulates transcription factor T-bet which upregulates interferon gamma (IFNγ) and granzyme B (GZMB) suggested that GSK-3 inactivation might provide extra value beyond of its down-regulation of PD-1. Here, we show that GSK-3 SMIs can synergize with anti-PD-1 and anti-CTLA-4 to eliminate B16 solid tumors that are otherwise resistant to anti-PD-1, or anti-CTLA-4 inhibition alone. At a cellular level, GSK-3 inactivation preferentially down-regulated PD-1 on CD8+ tumor infiltrating T-cells, while at a molecular level, GSK-3 SMIs inhibited PD-1 transcription, increased granzyme B (GZMB)/ interferon-gamma1 (IFNγ) transcription and directly acted upon glycogen synthase to skew metabolism towards greater glycolysis. We further showed that the inactivation of GSK-3α/β through siRNA or by SMIs substituted for CD28 co-stimulation in the potentiation of cytotoxic CD8+ CTL function. This data supports a model where GSK-3 mediates the dependency of anti-PD-1 immunotherapy on the expression of CD28. Overall, our data show that GSK-3 inactivation is an immune-sensitizer which assists the immune system to overcome tumor resistance to immune check-point blockade. Citation Format: Christopher E. Rudd. Glycogen synthase kinase (GSK-3) inactivation downregulates PD-1 and synergizes with PD-1/PL1 and CTLA-4 blockade in cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1696.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.352
Teacher spread0.328 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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