The role of hepatocyte growth factor (scatter factor) in epithelialmesenchymal transition and breast cancer
Bibliographic record
Abstract
North American women have a one in eight lifetime risk of developing breast cancer, and approximately one in three women with breast cancer will die of metastases. We, and others, have recently shown that high levels of expression of hepatocyte growth factor (HGF) and its receptor Met are associated with invasive human breast cancer and may be causally linked to metastasis. This high level of HGF and Met expression has been considered as a possible indicator of earlier recurrence and shortened survival in breast cancer patients. In contrast, HGF expression (but not Met) is strongly suppressed in normal breast epithelial cells. HGF and Met are therefore candidate targets for therapeutic intervention in the treatment of breast cancer. We have recently demonstrated that sustained activation or hyper-activation of c-Src and Stat3, which occurs in invasive breast cancer, can stimulate strong expression of HGF in carcinoma cells. In contrast, transient induction of Stat3 occurs in normal epithelium and promotes mammary tubulogenesis. We hypothesize that increased autocrine HGF-Met signaling is a critical downstream function of c-Src-Stat3 activation in mammary tumorigenesis. Future studies will identify novel Stat3 consensus sites that regulate HGF promoter activity and HGF expression preferentially in carcinoma cells and could lead to novel therapeutic drugs that specifically block HGF expression in mammary carcinoma cells, and which could be used in combined treatments to abrogate metastasis.
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How this classification was reachedexpand
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".