miR-628-5p promotes growth and migration of osteosarcoma by targeting IFI44L
Bibliographic record
Abstract
This study investigated the role of miR-628-5p and interferon-induced protein 44-like (IFI44L) in osteosarcoma (OS) and determined whether miR-628-5p modulated OS growth by regulating IFI44L. Based on the data downloaded from Gene Expression Omnibus (GEO) database, we revealed that the expression of IFI44L was downregulated in OS and low expression of IFI44L was correlated with better prognosis of patients with OS. Biological prediction of its upstream regulatory miRNAs on the miRWalk website found that miR-628-5p is a possible upstream regulatory miRNA of IFI44L. Luciferase activity assay demonstrated that miR-628-5p could bind to the 3' untranslated region (UTR) of IFI44L, which proved the above prediction. The expression of miR-628-5p is upregulated in OS and high expression of miR-628-5p is correlated with poor prognosis of patients with OS. The results of RT-qPCR showed that the expression of miR-628-5p in MG-63, U2OS, Saos-2, and SW1353 cells was significantly higher than that in the hFOB1.19 cells. Downregulation of miR-628-5p by miR-628-5p inhibitor significantly inhibited the proliferation, migration, and invasion of MG-63 cells. By rescue assay, we found that knockdown of IFI44L rescued the proliferation and motility of miR-628-5p depleted MG-63 cells. Collectively, our present data illustrated that miR-628-5p promoted the growth and motility of OS at least partly by targeting IFI44L. Moreover, miR-628-5p and IFI44L might be proposed as promising biomarkers in OS diagnosis and treatment.
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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 | 0.001 |
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".