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Record W3181341608 · doi:10.1158/1538-7445.am2021-1741

Abstract 1741: Reduced PTPN1/PTPN2 activity synergistically enhanced anti-tumoraleffector functionof CD8 T cells

2021· article· en· W3181341608 on OpenAlexaff
Luis Alberto Perez Quintero, Michel L. Tremblay

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsMcGill University
Fundersnot available
KeywordsCytotoxic T cellCD8ImmunologyImmune systemBiologyAcquired immune systemProinflammatory cytokineT cellCancer researchInflammation

Abstract

fetched live from OpenAlex

Abstract CD8 T cells are the main effectors of the adaptive immune system for T helper (Th) 1 or cytotoxic type of responses. In several types of cancer, CD8 lymphocyte infiltrates correlate with good prognosis. CD8 T cells can destroy directly transformed cells and secrete proinflammatory cytokines as IFN-γ and TNF-α, favoring the recruitment and activity of other effectors of antitumoral immunity such as M1 macrophages and NK cells. Hence, in the past few years the potential for the use of adaptive immune system as a base for immunotherapies has expanded enormously and it has focused in CD8 T cells activity. Chimeric antigen receptor (CAR)-T cell technology is one of those striking findings with remarkable successes in the treatment of refractory and/or relapse (r/r) B cell acute lymphoblastic leukemia (B-ALL) The duration of the event-free survival and the rates of overall survival overpass the previously existent treatments prompting to its proposal as therapy for less advanced stages of disease. Previously our laboratory has already shown that modulation of the JAK-STAT inhibitory protein tyrosine phosphatases (PTPs), PTPN1 and PTPN2, enhance proinflammatory type I interferon signaling while decreases the effects of immunosuppressive cytokines acting through STAT3 signaling. Very recently other groups have linked PTPN2 deficiency has with enhanced CD8 antitumoral responses. Unpublished observations from our laboratory using PTPN1/PTPN2 dual specific small molecule inhibitors suggested a role for both phosphatases in the enhancement of CD8 T cell cytotoxic activity. Following this lead, we decided to develop a genetic model to study the contribution of each enzyme to the CD8 T cell ability to respond to antigenic cues. Indeed, we found that a combined total or partial reduction of these genes increased the cytotoxic activity and IFN-γ secretion of CD8 T cells, underscoring synergistic but non-redundant mechanisms of action. The reduced activity of these phosphatases correlated with an increase in the tonic signals mediated by the JAK-STAT axis, particularly STAT 3 and STAT5a. As consequence, cells are sensitized to respond to type 1 and type 2 interferons. Transcriptomic analysis of these enhanced effector cells correlated their functional state with an increased expression, at transcript and protein level, several CD8 relevant transcription factors including of IRF4, Myb and the Basic leucine zipper transcriptional factor ATF-like 3 (BatF3). Henceforth, our results suggest that pharmacological manipulation of PTP1B and TC-PTP activity could be a powerful therapeutic tool for potentiating CTL cytotoxic responses and CTL based immunotherapies CAR-T cells. Citation Format: Luis Alberto Perez Quintero, Michel L. Tremblay. Reduced PTPN1/PTPN2 activity synergistically enhanced anti-tumoraleffector functionof CD8 T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1741.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.041
GPT teacher head0.367
Teacher spread0.326 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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