Liver-Specific Inactivation of the Proprotein Convertase FURIN Leads to Increased Hepatocellular Carcinoma Growth
Bibliographic record
Abstract
Proprotein convertases are subtilisin-like serine endoproteases that cleave and hence activate a variety of proproteins, including growth factors, receptors, metalloproteases, and extracellular matrix proteins. Therefore, it has been suggested that inhibition of the ubiquitously expressed proprotein convertase FURIN might be a good therapeutic strategy for several tumor types. Whether this is also the case for hepatocellular carcinoma (HCC) is currently not clear. In a mouse model for HCC expression of Furin was not altered in the tumors, while those of PC7, PC5/6, and PACE4 significantly decreased, at least at some time points. To investigate the impact of Furin inhibition on the development and progression of HCC in this model, Furin was genetically ablated in the liver. Furin inactivation resulted in an increased tumor mass after 5 weeks. This was not caused by decreased apoptosis, since no differences in the apoptosis index could be observed. However, it could at least partially be explained by increased hepatocyte proliferation at 5 weeks. The tumors of the Furin knockout mice were histologically similar to those in wild type mice. In conclusion, liver-specific Furin inhibition in HCC enhances the tumor formation and will not be a good therapeutic strategy for this tumor type.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".