The ERK/MAPK Pathway Regulates the Activity of the Human Tissue Factor Pathway Inhibitor-2 Promoter
Bibliographic record
Abstract
Human tissue factor pathway inhibitor-2 (hTFPI-2) is a 32-kDa serine protease inhibitor that is associated with the extracellular matrix. hTFPI-2 inhibits several extracellular matrix-degrading serine proteases and may play a role in tumor invasion and metastasis. To study the signal transduction pathway that leads to the activation of the hTFPI-2, we cloned the potential promoter region of this gene adjacent to a heterologous luciferase reporter gene. Phorbol 12-myristate 13-acetate (PMA) induced the luciferase reporter gene in HEK293 cells and other epithelial cell lines, such as the human lung carcinoma A549 cells, the breast carcinoma MCF7 cells, and the cervical HeLa cells. This PMA induction was blocked with the MEK inhibitor UO126, suggesting that the PMA-induced activation of the hTFPI-2 promoter is mediated through MEK. Furthermore, epidermal growth factor induced the luciferase reporter gene in HeLa cells. Cotransfection of the luciferase construct with constitutively active components of the Ras/Raf/MEK/ERK pathway in EcR-293 cells lead to a 7- to 92-fold induction of the luciferase reporter gene, indicating that regulation of hTFPI-2 is mediated through this pathway. A series of luciferase reporter gene constructs with progressive deletions of the 5'-flanking region suggested that the minimal basal promoter activity is located between nucleotide positions -89 and -384, whereas the minimal inducible promoter activity is between -89 and -222. We have used the computer program TFSEARCH and mutagenesis to analyze potential transcription factor binding sites. We identified an AP-1 binding site at nucleotide position -156 (inducible activity) and a Sp1 site at position -134 (basal activity) as potential cis-acting elements in the promoter region of the hTFPI-2.
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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".