miR-202-3p negatively regulates MMP-1 to inhibit the proliferation, migration and invasion of lung adenocarcinoma cells
Bibliographic record
Abstract
Lung adenocarcinoma (LUAD) is one of the common cancers. Studies show that MMP-1 is involved in tumor progression, yet relevant regulatory mechanism in LUAD remains to be further elucidated. Here, we demonstrated from bioinformatics analysis for GEO data that MMP-1 was differentially up-regulated in LUAD. miR-202-3p, identified as the upstream regulator of MMP-1 by both bioinformatics and dual-luciferase assays, was differentially down-regulated in LUAD and presented a negative correlation with MMP-1. Following cell biological experiments proved that knocking down the expression of MMP-1 inhibited the proliferation, migration and invasion of LUAD cells, while overexpressed miR-202-3p posed a similar suppressive effect on cancer progression. Additionally, rescue assay further identified that overexpression of MMP-1 attenuated the suppressive effect of up-regulated miR-202-3p on malignant progression of LUAD cells. In all, this research suggests a mechanism by which MMP-1 under the regulation of miR-202-3p modulates the proliferation, migration and invasion of LUAD cells, which may contribute to the development of new therapeutic strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".