MicroRNA-34a Mediates the Autocrine Signaling of PAR2-Activating Proteinase and Its Role in Colonic Cancer Cell Proliferation
Bibliographic record
Abstract
The tumor microenvironment is replete with proteinases. As a sensor of proteinases, proteinase activated receptor 2 (PAR2) plays critical roles in tumorigenesis. We showed that PAR2 and its activating proteinase were coexpressed in different colon cancer cell lines, including HT29. Inactivating proteinase or knockdown of PAR2 significantly not only reduced cell proliferation in vitro but also inhibited tumorigenicity of HT29 in vivo. In addition, activation of PAR2 promoted DNA synthesis and upregulated Cyclin D1 activity at both transcriptional and post-transcriptional levels. Further studies showed that miRNA-34a mediated PAR2-induced Cyclin D1 upregulation. Inhibition of miR-34a partially abolished the suppression of Cyclin D1 induced by PAR2 deficiency. In addition, we showed that TGF-β contributed to the regulation of miR-34a by PAR2. Finally, in colorectal carcinoma samples, upregulation of PAR2 and downregulation of miR-34a were significantly correlated with grade and lymphomatic metastasis. Our findings provide the first evidence that miRNA mediates autocrine proteinase signaling-mediated cancer cell proliferation.
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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 | 0.001 |
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".