Obesity/Type 2 Diabetes-Associated Liver Tumors Are Sensitive to Cyclin D1 Deficiency
Bibliographic record
Abstract
Type 2 diabetes, which is mainly linked to obesity, is associated with increased incidence of liver cancer. We have previously found that in various models of obesity/diabetes, hyperinsulinemia maintains heightened hepatic expression of cyclin D1, suggesting a plausible mechanism linking diabetes and liver cancer progression. Here we show that cyclin D1 is greatly elevated in human livers with diabetes and is among the most significantly upregulated genes in obese/diabetic liver tumors. Liver-specific cyclin D1 deficiency protected obese/diabetic mice against hepatic tumorigenesis, whereas lean/nondiabetic mice developed tumors irrespective of cyclin D1 status. Cyclin D1 dependency positively correlated with liver cancer sensitivity to palbociclib, an FDA-approved CDK4 inhibitor, which was effective in treating orthotopic liver tumors under obese/diabetic conditions. The antidiabetic drug metformin suppressed insulin-induced hepatic cyclin D1 expression and protected against obese/diabetic hepatocarcinogenesis. These results indicate that the cyclin D1-CDK4 complex represents a potential selective therapeutic vulnerability for liver tumors in obese/diabetic patients. SIGNIFICANCE: Obesity/diabetes-associated liver tumors are specifically vulnerable to cyclin D1 deficiency and CDK4 inhibition, suggesting that the obese/diabetic environment confers cancer-selective dependencies that can be therapeutically exploited.
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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 | 0.000 |
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".