AMPK-dependent Parkin activation suppresses macrophage antigen presentation to promote tumor progression
Bibliographic record
Abstract
The constrained cross-talk between myeloid cells and T cells in the tumor immune microenvironment (TIME) restricts cancer immunotherapy efficacy, whereas the underlying mechanism remains elusive. Parkin, an E3 ubiquitin ligase renowned for mitochondrial quality control, has emerged as a regulator of immune response. Here, we show that both systemic and macrophage-specific ablations of Parkin in mice lead to attenuated tumor progression and prolonged mouse survival. By single-cell RNA-seq and flow cytometry, we demonstrate that Parkin deficiency reshapes the TIME through activating both innate and adaptive immunities to control tumor progression and recurrence. Mechanistically, Parkin activation by AMP-activated protein kinase rather than PTEN-induced kinase 1 mediated major histocompatibility complex I down-regulation on macrophages via Autophagy related 5–dependent autophagy. Furthermore, Parkin deletion synergizes with immune checkpoint blockade treatment and Park2 −/− signature aids in predicting the prognosis of patients with solid tumor. Our findings uncover Parkin’s involvement in suppressing macrophage antigen presentation for coordinating the cross-talk between macrophages and T cells.
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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) | 0.001 | 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".