Metabolic features of clear-cell renal cell carcinoma: mechanisms and clinical implications
Bibliographic record
Abstract
Central to the malignant behaviour that endows cancer cells withgrowth advantage is their unique metabolism. Cancer cells canprocess nutrient molecules differently from normal cells and useit to overcome stress imposed on them by various therapies. Thismetabolic conversion is controlled by specific genetic mutationsthat are associated with activation of oncogenes and loss of tumoursuppressor proteins. Understanding these processes is importantas it can lead to the discovery of biomarkers that can predict theaggressiveness of the disease and its response to therapy, and evenmore importantly, to the development of novel therapeutics. A classictumour in this respect is clear-cell renal cell carcinoma (RCC). Inthis review, we will begin with a brief summary of normal cellularbioenergetic pathways, which will be followed by a descriptionof the characteristic metabolism of glucose and lipids in clear-cellRCC cells and its clinical implications. Data relating to the potentialeffect of dietary nutrients on RCC will also be reviewed alongwith potential therapies targeted at interrupting specific metabolicpathways in clear-cell RCC.Le métabolisme unique des cellules cancéreuses est au coeur ducomportement malin qui leur confère un avantage sur le plan de lacroissance. Les cellules cancéreuses peuvent traiter les moléculesde nutriment différemment des cellules normales et utilisent cesmolécules pour surmonter le stress imposé par les différents traitements.La conversion métabolique est contrôlée par des mutationsgénétiques précises associées à l’activation d’oncogènes et à laperte de protéines de suppression tumorale. Il est important debien saisir ces processus, car leur élucidation peut mener à ladécouverte de biomarqueurs permettant de prédire l’agressivité dela maladie et la réponse au traitement et, fait encore plus important,elle peut mener à la mise au point de nouveaux médicaments. À cetégard, l’hypernéphrome à cellules claires représente une tumeurclassique. Dans cet article, nous commençons par résumer brièvementles voies bioénergétiques cellulaires normales, puis nouspoursuivons avec une description du métabolisme caractéristiquedu glucose et des lipides dans les cellules de l’hypernéphrome àcellules claires et ses répercussions cliniques. Les données associéesà l’effet potentiel des nutriments sur l’hypernéphrome à cellulesclaires seront aussi passées en revue, ainsi que les thérapiesciblées potentielles visant l’interruption de voies métaboliquesparticulières dans l’hypernéphrome à cellules claires.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".