Targeting of lipid metabolism with a metabolic inhibitor cocktail eradicates peritoneal metastases in ovarian cancer cells
Bibliographic record
Abstract
Ovarian cancer is an intra-abdominal tumor in which the presence of ascites facilitates metastatic dissemination, and associated with poor prognosis. However, the significance of metabolic alterations in ovarian cancer cells in the ascites microenvironment remains unclear. Here we show ovarian cancer cells exhibited increased aggressiveness in ascites microenvironment via reprogramming of lipid metabolism. High lipid metabolic activities are found in ovarian cancer cells when cultured in the ascites microenvironment, indicating a metabolic shift from aerobic glycolysis to β-oxidation and lipogenesis. The reduced AMP-activated protein kinase (AMPK) activity due to the feedback effect of high energy production led to the activation of its downstream signaling, which in turn, enhanced the cancer growth. The combined treatment of low toxic AMPK activators, the transforming growth factor beta-activated kinase 1 (TAK1) and fatty acid synthase (FASN) inhibitors synergistically impair oncogenic augmentation of ovarian cancer. Collectively, targeting lipid metabolism signaling axis impede ovarian cancer peritoneal metastases.
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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) | 0.001 | 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".