<scp>PTPN2</scp> Negatively Regulates Macrophage Immune Responses and Cellular Bioenergetics
Bibliographic record
Abstract
PTPN2 is encoded by the protein tyrosine phosphatase N2 (also known as TC-PTP) and is a negative regulator of cytokine signaling and macrophage differentiation. In the past decade, our work and others, including several pharmaceuticals, have emphasized that inhibition of PTPN2 and PTPN1 (also known as PTP1B) may act as a new first-of-class cancer immunotherapeutic. Although the potential roles of these two enzymes in various immune cells have been broadly reported, the specific activity of PTPN2 in regulating macrophage immune and metabolic responses has yet to be fully elucidated. Hence, we sought to investigate the function of PTPN2 in macrophage polarization and on their activities. We used two different mouse models to systematically and specifically inhibit the expression of PTPN2 in macrophages and utilized a chemical inhibitor with a macrophage human cell line to assess their immune and metabolic profiles. We demonstrated that PTPN2 ablation in macrophages alters their immunometabolic transcriptome and enhances their proinflammatory response, as observed by increased IFN-ɣ and nitric oxide production. PTPN2 deficiency also leads to a dysregulation of mitochondrial respiration, as observed by decreased oxygen consumption and ATP production. We establish herein that PTPN2 dampens the proinflammatory response of macrophages while altering their mitochondrial respiration, validating its macrophage inhibition as a contributing factor in the potency of systemic dual inhibition of PTPN1 and PTPN2 against cancer.
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 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".