PTPN1/2 inhibition induces highly functional terminal effector CD8 T cells through autocrine IL-10
Bibliographic record
Abstract
Abstract Increased understanding of the modulatory pathways controlling CD8 T cell responses has led to the formulation of successful checkpoint inhibitor-based immunotherapies against cancer. However, their effectiveness is limited to a few tumor types, motivating the search for novel combinatorial strategies. PTPN1 and PTPN2 are two homologous protein tyrosine phosphatases recently proposed as potent intracellular checkpoints. Furthermore, their catalytic domain is a propitious target for small-molecule pharmacological intervention. Herein we investigated the potential effects of conditional genetic deletion of either or both phosphatases in mouse CD8 T cells, one of the main effectors in cancer immunotherapy. Our results demonstrated that hemizygous deletion of PTPN1 in a PTPN2 deficient background heightens the enhanced effector phenotype already observed in PTPN2 defective CD8 T cells. This functional gain is mediated by an autocrine IL-10 positive feedback loop. Pharmacological inhibition with a PTPN1/2 small-molecule inhibitor yielded similar results, highlighting the importance of simultaneously inhibiting both phosphatases. Our study uncovers a novel mechanism by which the downregulation of PTPN1 and PTPN2 act as a powerful tool for potentiating CD8 cytotoxic responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".