Metabolic reprogramming in cancer: mechanistic insights from <i>Drosophila</i>
Bibliographic record
Abstract
Cancer cells constantly reprogram their metabolism as the disease progresses. However, our understanding of the metabolic complexity of cancer remains incomplete. Extensive research in the fruit fly Drosophila has established numerous tumor models ranging from hyperplasia to neoplasia. These fly tumor models exhibit a broad range of metabolic profiles and varying nutrient sensitivity. Genetic studies show that fly tumors can use various alternative strategies, such as feedback circuits and nutrient-sensing machinery, to acquire and consolidate distinct metabolic profiles. These studies not only provide fresh insights into the causes and functional relevance of metabolic reprogramming but also identify metabolic vulnerabilities as potential targets for cancer therapy. Here, we review the conceptual advances in cancer metabolism derived from comparing and contrasting the metabolic profiles of fly tumor models, with a particular focus on the Warburg effect, mitochondrial metabolism, and the links between diet and cancer.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".