Tumor suppressor function of miR-483-3p on squamous cell carcinomas due to its pro-apoptotic properties
Bibliographic record
Abstract
The frequent alteration of miRNA expression in many cancers, together with our recent reports showing a robust accumulation of miR-483-3p at the final stage of skin wound healing, and targeting of CDC25A leading to an arrest of keratinocyte proliferation, led us to hypothesize that miR-483-3p could also be endowed with antitumoral properties. We tested that hypothesis by documenting the in vitro and in vivo impacts of miR-483-3p in squamous cell carcinoma (SCC) cells. miR-483-3p sensitized SCC cells to serum deprivation- and drug-induced apoptosis, thus exerting potent tumor suppressor activities. Its pro-apoptotic activity was mediated by a direct targeting of several anti-apoptotic genes, such as API5, BIRC5, and RAN. Interestingly, an in vivo delivery of miR-483-3p into subcutaneous SCC xenografts significantly hampered tumor growth. This effect was explained by an inhibition of cell proliferation and an increase of apoptosis. This argues for its further use as an adjuvant in the many instances of cancers characterized by a downregulation of miR-483-3p.
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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) | 0.002 | 0.001 |
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".