A novel activating role of SRC and STAT3 on HGF transcription in human breast cancer cells
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Bibliographic record
Abstract
We have previously determined that the HGF promoter can be transactivated by a combination of activated Src and wild-type Stat3 in the mouse breast cell lines HC11 and SP1. To determine if this pathway is of relevance for the human disease, a series of human breast and other human cells lines were examined, and the status of key proteins in these cells determined. All of the human breast cell lines exhibited strong transactivation by a combination of activated Src and Stat3. This activation was dependent on a Stat3 recognition element present at nt-95. The exception was the ErbB2 over-expressing cell line SK-BR-3 where Stat3 alone could transactivate HGF though Src augmented this effect. Increased phosphorylation of Stat3 tyrosine 705 was also observed in this line. Analysis of three ovarian cell lines revealed that Src/Stat3 expression was not able to activate the HGF promoter in two of these lines (SKOV3 and IOSE-80PC). Src/Stat3 expression did activate HGF transcription in OVCAR3 cells, but this effect was not mediated by the Stat3 site at nt-95. Stat3 phosphorylation at tyrosine 705 was observed in IOSE-80PC cells, but was insufficient to allow for activation of the HGF promoter. Human kidney (HEK293) and cervical carcinoma (HeLa) cells were also not Src/Stat3 permissive, despite high levels of Stat3 phospho-Y705. These results suggest that human breast cells are a uniquely permissive environment for HGF transactivation by Src/Stat3 which may allow for the inappropriate activation of HGF transcription during the early stages of breast transformation. This could lead to paracrine or autocrine activation of the Met receptor in breast carcinoma cells.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it