Insulin resistance: Influence on cancer risk and cancer prognosis
Notice bibliographique
Résumé
CN08-04 * Hyperinsulinemia is usually associated with reduced insulin signalling in classic target tissues for insulin action, such as liver, muscle, and fat. Intake of energy in excess of requirements often leads to insulin resistance, obesity, and hyperinsulinemia, although this is influenced by genetic factors and varies between individuals in human populations and between mouse strains in laboratory models. * Hyperinsulinemia and obesity are becoming more common in affluent societies, largely due to decreasing physical activity coupled with ample availability of calorie-dense foods. It is important to recognize that hyperinsulinemia is not always associated with obesity: in affluent societies, many individuals meet criteria for characterization as obese, normal weight (MONW). * Recent studies (for example Ma J, Li H, Pollak M, Kurth T, Giovannucci E, Stampfer M, abstract A204, AACR Frontiers in Cancer Prevention, 2006) provide early evidence hyperinsulinemia is associated with poor prognosis for common cancers. These studies are consistent with earlier observations suggesting that obesity (Calle E et al NEJM 1999: 341:1097-1105) and hyperglycemia ( Jee S et al JAMA 2005: 293: 194-202) are associated with increased cancer mortality. While they are many metabolic abnormalities in subjects who are hyperglycemic, hyperinsulinemic, and obese that might be causally associated with the increased cancer mortality observed, one obvious candidate is insulin itself. This involves the hypothesis that in hyperinsulinemic, insulin resistant subjects, neoplastic tissue may not share the insulin resistance present in the normal host tissues, but rather remain insulin sensitive, in a hyperinsulinemic milieu. * As an early step to explore this hypothesis, we have confirmed and extended recent reports from several groups in documenting the presence of insulin receptors on primary human cancers, including those of breast, colon, and prostate. We also recognize that drugs known to lower insulin levels, such as metformin, would be predicted to have antineoplastic activity if this hypothesis is valid. Early population studies ( Bowker S et al Diabetes Care 2006: 29:254-258; Evans J et al BMJ 2005: 330: 1304-1305) are consistent with this possibility. I will describe recent studies with laboratory models that are also consistent with the hypothesis. These models suggest that the in vivo antineoplastic activity of metformin is restricted to hosts rendered insulin resistant by overfeeding; little activity was seen under control dietary conditions. The in vivo activity of the drug is correlated with reduction of insulin receptor activation in neoplastic tissue, suggesting reduction of insulin levels is a contributing mechanism, although the growth inhibition via AMPK activation described in vitro (Zakikhani M, Dowling R, Fantus I, Sonenberg N, Pollak M Cancer Res 2006:10269-73) may also play a role. * Taken together, the ongoing work is consistent with the possibility that excess insulin is a risk factor for poor cancer outcome. As hyperinsulinemia is common and is modifiable by lifestyle and drug therapy, further research is justified. The early results suggest that benefits of interventions in this area may be restricted to metabolically defined subsets of patients, a point which should be taken into account in the design of future intervention trials.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».