Multitargeting activity of miR-24 inhibits long-term melatonin anticancer effects
Bibliographic record
Abstract
// Federica Mori 1, * , Maria Ferraiuolo 1, 2, * , Raffaela Santoro 1, * , Andrea Sacconi 2 , Frauke Goeman 2 , Matteo Pallocca 3 , Claudio Pulito 1 , Etleva Korita 1 , Maurizio Fanciulli 3 , Paola Muti 4 , Giovanni Blandino 2, 4 , Sabrina Strano 1, 4 1 Molecular Chemoprevention Unit, Molecular Medicine Area, Regina Elena National Cancer Institute, 00144 Rome, Italy 2 Translational Oncogenomics Unit, Molecular Medicine Area, Regina Elena National Cancer Institute, 00144 Rome, Italy 3 Department of Research, Advanced Diagnostics and Technological Innovation, Translational Research Area, Regina Elena National Cancer Institute, 00144 Rome, Italy 4 Department of Oncology, Juravinski Cancer Center-McMaster University, Hamilton, ON L8V 5C2, Ontario, Canada * These authors contributed equally to this work Correspondence to: Giovanni Blandino, e-mail: blandino@ifo.it Sabrina Strano, e-mail: strano@ifo.it Keywords: melatonin, miR-24, RNA-Seq, p53, PML Received: November 19, 2015 Accepted: February 11, 2016 Published: March 08, 2016 ABSTRACT We have previously shown that melatonin exerts tumor suppressor activities by inducing the p38-p53 axis. This occurred within a few hours while no data are available on how melatonin pathway can be sustained on the long term. Here we show that miR-24, which has been demonstrated to target genes involved in the DNA repair process, targets p38, p53, PML and H2AX simultaneously. We show that long-term treatment with melatonin can decrease miR-24 levels post-transcriptionally, which pairs with a long-wave regulation of genes involved in cell proliferation, DNA damage, RNA metabolism and cell shape and transformation. Moreover, we show that melatonin can inhibit cell proliferation and migration, at least in part, by downregulating miR-24. Furthermore, we propose the involvement of hnRNP A1, which is downregulated by melatonin and involved in miRNA processing, in the regulation of miR-24 levels by melatonin. We conclude showing that miR-24 is upregulated in colon, breast and head and neck datasets and its levels negatively correlate with overall survival.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".