p63, a key regulator of Ago2, links to the microRNA-144 cluster
Bibliographic record
Abstract
As a key component of the RNA-induced silencing complex (RISC), Argonaute2 (Ago2) exhibits a dual function regulatory role in tumor progression. However, the mechanistic basis of differential regulation remains elusive. p63 is a homolog of the tumor suppressor p53. p63 isoforms play a critical role in tumorigenesis and metastasis. Herein, we show that p63 isoforms physically interact with and stabilize Ago2. Expression of p63 isoforms increases the levels of Ago2 protein, while depletion of p63 isoforms by shRNA decreases Ago2 protein levels. p63 strongly guides Ago2 dual functions in vitro and in vivo. Ectopic expression of the miR-144/451 cluster increases p63 protein levels; TAp63 transactivates the miR-144/451 cluster, forming a positive feedback loop. Notably, miR-144 activates p63 by directly targeting Itch, an E3 ligase of p63. Ectopic expression of miR-144 induces apoptosis in H1299 cells. miR-144 enhances TAp63 tumor suppressor function and inhibits cell invasion. Our findings uncover a novel function of p63 linking the miRNA-144 cluster and the Ago2 pathway. FACTS AND QUESTIONS: Identification of Ago2 as a p63 target. Ago2 exhibits a dual function regulatory role in tumor progression; however, the molecular mechanism of Ago2 regulation remains unknown. p63 strongly guides Ago2 dual functions in vitro and in vivo. Unraveling a novel function of p63 links the miRNA-144 cluster and the Ago2 pathway.
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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 | 0.000 |
| 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".