TIMP3 controls cell fate to confer hepatocellular carcinoma resistance
Bibliographic record
Abstract
Inflammation enables human cancers and is a critical promoter of hepatocellular carcinoma (HCC). TIMP3 (Tissue inhibitor of metalloproteinase 3), a natural metalloproteinase inhibitor, controls cytokine and growth factor bioavailability to keep inflammation in check and regulate cell survival in the liver. TIMP3 is also found silenced in human cancers. We therefore tested whether Timp3 affects HCC predisposition. Remarkably, genetic loss of Timp3 protected from carcinogen-induced HCC through the immediate engagement of several tumor suppressor pathways, while tumor necrosis factor (TNF) signaling was dispensable for this protection. All wild-type mice developed HCC by 12 months, whereas HCC incidence was reduced to 33% at 12 months and 57% at 15 months in Timp3 null mice. Upon acute carcinogen treatment the deficient livers exhibited greater cytokine expression, but lower cell death and higher hepatocyte senescence. We found that precocious activation of p53, p38 and Notch preceded senescence and hepatic cell differentiation, and these events were conserved throughout tumorigenesis. Timp3-deficient mouse embryo fibroblasts also responded to carcinogen by favoring senescence over apoptosis. We conclude that Timp3 status determines p53, p38 and Notch coactivation to instruct hepatic cell fate and transformation and uncover mechanisms that are protective even within a pro-inflammatory microenvironment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".