Epistatic interaction between the lipase-encoding genes Pnpla2 and Lipe causes liposarcoma in mice
Bibliographic record
Abstract
Liposarcoma is an often fatal cancer of fat cells.Mechanisms of liposarcoma development are incompletely understood.The cleavage of fatty acids from acylglycerols (lipolysis) has been implicated in cancer.We generated mice with adipose tissue deficiency of two major enzymes of lipolysis, adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL), encoded respectively by Pnpla2 and Lipe.Adipocytes from double adipose knockout (DAKO) mice, deficient in both ATGL and HSL, showed near-complete deficiency of lipolysis.All DAKO mice developed liposarcoma between 11 and 14 months of age.No tumors occurred in single knockout or control mice.The transcriptome of DAKO adipose tissue showed marked differences from single knockout and normal controls as early as 3 months.Gpnmb and G0s2 were among the most highly dysregulated genes in premalignant and malignant DAKO adipose tissue, suggesting a potential utility as early markers of the disease.Similar changes of GPNMB and G0S2 expression were present in a human liposarcoma database.These results show that a previously-unknown, fully penetrant epistatic interaction between Pnpla2 and Lipe can cause liposarcoma in mice.DAKO mice provide a promising model for studying early premalignant changes that lead to late-onset malignant disease. Author summaryLiposarcoma is an often fatal adult-onset tumor of fat tissue.Lipolysis, the central pathway of fat tissue metabolism, has been implicated in cancer.We generated mice that were deficient in two key enzymes of lipolysis, adipose triglyceride lipase (ATGL) and hormonesensitive lipase (HSL).Strikingly, all mice with combined ATGL and HSL deficiency developed liposarcoma by 11-14 months of age.No liposarcoma occurred in single
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".