Systemic NK4 gene therapy inhibits tumor growth and metastasis of melanoma and lung carcinoma in syngeneic mouse tumor models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hepatocyte growth factor (HGF) promotes malignant development of cancer cells by enhancing invasion and metastasis. NK4, a competitive antagonist for HGF, is a bifunctional molecule that acts as a HGF antagonist and angiogenesis inhibitor. Although successful tumor inhibition by NK4 gene expression in tumor models has been demonstrated, the effects of systemic NK4 gene introduction are yet to be addressed. Here we show that systemic administration of a replication-defective adenovirus expressing NK4 (Ad.NK4) inhibits tumor growth and lung metastasis of B16F10 melanoma and Lewis lung carcinoma in syngeneic mice. Single tail-vein injection of Ad.NK4 achieved therapeutic levels of NK4 in the circulation and in multiple organs. Despite NK4 expression that was highest in the liver, toxicity in the liver was minimal. Ad.NK4-mediated growth inhibition was associated with decreased blood vessel density and increased apoptosis in tumor tissues, which suggests that NK4 suppressed tumor growth as an angiogenesis inhibitor. Metastasis of B16F10 melanoma and Lewis lung carcinoma cells to the lung was potently inhibited by systemic Ad.NK4-administration. Our results demonstrated that the adenovirus-mediated induction of high levels of circulating NK4 significantly inhibited in vivo tumor growth and distant metastasis without obvious side effects. NK4 gene therapy is thus a safe and promising strategy for the treatment of cancer patients, and further validation in clinical trials is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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