Adenovirus‐mediated overexpression of tissue inhibitor of metalloproteinases‐1 in the liver: efficient protection against T‐cell lymphoma and colon carcinoma metastasis
Bibliographic record
Abstract
BACKGROUND: Matrix metalloproteinases (MMPs) are critical for metastasis of tumor cells. Tissue inhibitor of metalloproteinases-1 (TIMP-1), a natural MMP inhibitor, was shown to reduce metastasis in different models. Here, we investigated whether increased TIMP-1 levels in the liver achieved by adenoviral gene transfer will effectively inhibit liver metastasis of two independent tumor cell lines. METHOD: TIMP-1 was transferred with adenoviral vectors into the livers of DBA/2 and Balb/c mice, which were subsequently challenged by hematogenous experimental metastases of the T-cell lymphoma cell line L-CI.5s or the colorectal carcinoma cell line CT-26, respectively. RESULTS: MMP-9 expression in the liver was induced upon metastasis in both tumor types. Adenoviral gene transfer led to high transduction efficacy as indicated by lacZ expression in 60% of hepatocytes. TIMP-1, a key inhibitor of MMP-9, was expressed at 10(5)-fold higher levels by adenoviral gene transfer as compared with levels achieved in TIMP-1 transgenic mice, previously shown to be inefficient to reduce T-cell lymphoma metastasis. High local and systemic (serum) levels of TIMP-1 led to substantial (94%) reduction of T-cell lymphoma and colorectal carcinoma (73%) experimental liver metastasis. CONCLUSIONS: Adenoviral gene transfer led to systemic and local TIMP-1 levels sufficient to inhibit metastasis of a highly aggressive T-cell lymphoma, pointing at the requirement of threshold levels for effective anti-metastatic efficacy. This approach was also efficient in a colon carcinoma solid tumor model. We propose that viral gene transfer of TIMP-1 can provide a suitable defense strategy to prevent metastatic spread to the liver.
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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 | 0.001 | 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 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".