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Type 2 Diabetes and Breast Cancer: The Interplay between Impaired Glucose Metabolism and Oxidant Stress

Metabolic disorders, especially type 2 diabetes and its associated complications, represent a growing public health problem. Epidemiological findings indicate a close relationship between diabetes and many types of cancer (including breast cancer risk), which regards not only the dysmetabolic condit...

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Detalles Bibliográficos
Autores principales: Ferroni, Patrizia, Riondino, Silvia, Buonomo, Oreste, Palmirotta, Raffaele, Guadagni, Fiorella, Roselli, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4480937/
https://www.ncbi.nlm.nih.gov/pubmed/26171112
http://dx.doi.org/10.1155/2015/183928
Descripción
Sumario:Metabolic disorders, especially type 2 diabetes and its associated complications, represent a growing public health problem. Epidemiological findings indicate a close relationship between diabetes and many types of cancer (including breast cancer risk), which regards not only the dysmetabolic condition, but also its underlying risk factors and therapeutic interventions. This review discusses the advances in understanding of the mechanisms linking metabolic disorders and breast cancer. Among the proposed mechanisms to explain such an association, a major role is played by the dysregulated glucose metabolism, which concurs with a chronic proinflammatory condition and an associated oxidative stress to promote tumour initiation and progression. As regards the altered glucose metabolism, hyperinsulinaemia, both endogenous due to insulin-resistance and drug-induced, appears to promote tumour cell growth through the involvement of innate immune activation, platelet activation, increased reactive oxygen species, exposure to protumorigenic and proangiogenic cytokines, and increased substrate availability to neoplastic cells. In this context, understanding the relationship between metabolic disorders and cancer is becoming imperative, and an accurate analysis of these associations could be used to identify biomarkers able to predict disease risk and/or prognosis and to help in the choice of proper evidence-based diagnostic and therapeutic protocols.