Activation of Hepatocyte Growth Factor-Met Autocrine Loop Enhances Tumorigenicity in a Human Lung Adenocarcinoma Cell Line
Bibliographic record
Abstract
Hepatocyte growth factor (HGF) is a multifunctional cytokine with effects on the proliferation, motility, and differentiation of cells that express its receptor Met. The co-expression of HGF and Met is common among nonsmall-cell lung cancers, especially adenocarcinoma. However, the biologic consequences of this putative HGF-Met autocrine signaling remain speculative. We have used retroviral gene transduction technique to express high levels of HGF in the NCI-H358 lung adenocarcinoma cells that have functionally active cell surface Met receptor. The activation of autocrine HGF-Met signaling was confirmed by the induction of spontaneous cell scattering activity. Compared to the parent and control cells transduced with the retroviral vector alone, HGF overexpressing H358 cells show enhanced capacity to colonize soft agar medium and to form xenograft tumors when implanted in the subcutaneous tissue of immune-deficient mice. These effects were not accompanied by changes in their growth rate in monolayer culture condition, or in the expression of vascular endothelial growth factor. The tumors formed by HGF overexpressing cells also showed more prominent glandular cell arrangement and functional activity. This report provides the direct in vivo evidence that autocrine HGF-Met signaling plays significant roles in the growth and differentiation of human lung adenocarcinoma cells.
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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) | 0.000 | 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) | 0.001 | 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".