PML-RARα enhances constitutive autophagic activity through inhibiting the Akt/mTOR pathway
Bibliographic record
Abstract
Autophagy is a highly conserved, closely regulated homeostatic cellular activity that allows for the bulk degradation of long-lived proteins and cytoplasmic organelles. Its roles in cancer initiation and progression and in determining the response of tumor cells to anticancer therapy are complicated, and only limited investigation has been conducted on the potential significance of autophagy in the pathogenesis and therapeutic response of acute myeloid leukemia. Here we demonstrate that the inducible or transfected expression of the acute promyelocytic leukemia (APL)-specific PML-RARα, but not PLZF-RARα or NPM-RARα, fusion protein upregulates constitutive autophagy activation in leukemic and nonleukemic cells, as evaluated by hallmarks for autophagy including transmission electron microscopy. The significant increase in autophagic activity is also found in the leukemic cells-infiltrated bone marrow and spleen from PML-RARα-transplanted leukemic mice. The autophagy inhibitor 3-methyladenine significantly abrogates the autophagic events upregulated by PML-RARα, while the autophagic flux assay reveals that the fusion protein induces autophagy by increasing the on-rate of autophagic sequestration. Furthermore, this modulation of autophagy by PML-RARα is possibly mediated by a decreased activation of the Akt/mTOR pathway. Finally, we also show that autophagy contributes to the anti-apoptotic function of the PML-RARα protein. Given the critical role of the PML-RARα oncoprotein in APL pathogenesis, this study suggests an important role of autophagy in the development and treatment of this disease.
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) | 0.001 | 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".