Inhibition of lipid metabolism exerts antitumor effects on rhabdomyosarcoma
Bibliographic record
Abstract
Rhabdomyosarcoma exhibits tumor-specific energy metabolic changes that include the Warburg effect. Since targeting cancer metabolism is a promising therapeutic approach, we examined the antitumor effects of suppressing lipid metabolism in rhabdomyosarcoma. We suppressed lipid metabolism in rhabdomyosarcoma cells in vitro by administering an inhibitor of malonyl-CoA decarboxylase, which increases malonyl-CoA and decreases fatty acid oxidation. Suppression of lipid metabolism in rhabdomyosarcoma cells decreased cell proliferation by inducing cell cycle arrest. Metabolomic analysis showed an increase in glycolysis and inactivation of the pentose phosphate pathway. Immunoblotting analysis revealed upregulated expression of the autophagy marker LC3A/B-II due to increased phosphorylation of AMP-activated protein kinase, a nutrient sensor. p21 protein expression level also increased. Inhibition of both lipid metabolism and autophagy suppressed tumor proliferation and increased apoptosis. In vivo studies involved injection of human Rh30 cells into the gastrocnemius muscle of 6-week-old female nude mice, which were divided into normal chow and low-fat diet groups. The mice fed a low-fat diet for 21 days showed reduced tumor growth compared to normal chow diet-fed mice. Suppression of lipid metabolism disrupted the equilibrium of the cancer-specific metabolism in rhabdomyosarcoma, resulting in a tumor growth-inhibition effect. Therefore, the development of treatments focusing on the lipid dependence of rhabdomyosarcoma is highly promising.
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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 | 0.000 | 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) | 0.000 | 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".