p38 activation induces production of miR-146a and miR-31 to repress E-selectin expression and inhibit transendothelial migration of colon cancer cells
Bibliographic record
Abstract
Extravasation of circulating cancer cells determines their metastatic potential. This process is initiated by the adhesion of cancer cells to vascular endothelial cells through specific interactions between endothelial adhesion receptors such as E-selectin and their ligands on cancer cells. In the present study, we show that miR-146a and miR-181b impede the expression of E-selectin by repressing the activity of its transcription factor NF-κB, thereby impairing the metastatic potentials of colon cancer cells by decreasing their adhesion to, and migration through, the endothelium. Among the two microRNAs, only miR-146a is activated by IL-1β, through the activation of p38, ERK and JNK MAP kinases, as well as their downstream transcription factors GATA2, c-Fos and c-Jun. Inhibiting p38 MAP kinase increases NF-κB activity, at least partially via miR-146a. Inhibiting p38 also increases the expression of E-selectin at the post-transcriptional level via decreasing miR-31, which targets E-selectin mRNA and also depends on p38 for its expression. In response to IL-1β, p38 MAP kinase hence represses the expression of E-selectin at the transcriptional and the post-transcriptional levels, via miR-146a and miR-31, respectively. These results highlight novel mechanisms by which p38 downregulates the expression of E-selectin through different microRNAs following inflammatory stimuli associated to cancer progression.
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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) | 0.002 | 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".