Building risk-on-a-chip models to improve breast cancer risk assessment and prevention.
Building risk-on-a-chip models to improve breast cancer risk assessment and prevention.
复制标题
建立芯片风险模型以改善乳腺癌风险评估和预防。
DOI：
10.1039/c3ib40053k
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Lelièvre,SophieA
中科院分区：
文献类型：
--
作者：
Vidi,Pierre-Alexandre;Leary,JamesF;Lelièvre,SophieA
针对慢性疾病的预防行动有望改善生活并降低医疗保健费用。对于包括乳腺癌在内的几种疾病，流行病学家已经确定了多种风险和保护因素。在生物体、组织、细胞和分子水平上，大多数这些因素的影响尚未得到充分了解。重要的是，外部和内部风险和保护因素的组合涉及协同性，从而协同或拮抗疾病发作。在确定的细胞和微环境条件下，需要模型来机械地破译癌症风险。在这里，我们简要回顾了基于3D细胞培养的乳腺癌风险模型，并提出了利用芯片实验室方法改进风险建模的方法。我们建议上皮组织极性、DNA修复和表观遗传谱作为风险评估模型的终点，并讨论了集成这些终点和一般组织稳态生物传感器的“芯片风险”的发展。芯片上的风险将有助于识别风险的生物标志物，作为癌症预防药物的筛选平台，并提供对风险机制的更好理解，从而导致疾病预防的新发展。
Preventive actions for chronic diseases hold the promise of improving lives and reducing healthcare costs. For several diseases, including breast cancer, multiple risk and protective factors have been identified by epidemiologists. The impact of most of these factors has yet to be fully understood at the organism, tissue, cellular and molecular levels. Importantly, combinations of external and internal risk and protective factors involve cooperativity thus, synergizing or antagonizing disease onset. Models are needed to mechanistically decipher cancer risks under defined cellular and microenvironmental conditions. Here, we briefly review breast cancer risk models based on 3D cell culture and propose to improve risk modeling with lab-on-a-chip approaches. We suggest epithelial tissue polarity, DNA repair and epigenetic profiles as endpoints in risk assessment models and discuss the development of ‘risks-on-chips’ integrating biosensors of these endpoints and of general tissue homeostasis. Risks-on-chips will help identify biomarkers of risk, serve as screening platforms for cancer preventive agents, and provide a better understanding of risk mechanisms, hence resulting in novel developments in disease prevention.
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影响因子：
14
作者：
Norotte, Cyrille;Marga, Francois S.;Niklason, Laura E.;Forgacs, Gabor
通讯作者：
Forgacs, Gabor
DOI：
10.1039/c1ib00043h
发表时间：
2011-09
期刊：
Integrative biology : quantitative biosciences from nano to macro
影响因子：
--
作者：
Lopez JI;Kang I;You WK;McDonald DM;Weaver VM
通讯作者：
Weaver VM
用于培养井操作的微型葡萄糖生物传感器。
影响因子：
12.6
作者：
R. Pemberton;T. Cox;R. Tuffin;I. Sage;G. Drago;N. Biddle;J. Griffiths;R. Pittson;G. Johnson;J. Xu;S. Jackson;G. Kenna;R. Luxton;J. Hart
通讯作者：
J. Hart
DOI：
10.1016/0002-9378(86)90713-1
发表时间：
1986-06-01
影响因子：
9.8
作者：
JENSEN, HM
通讯作者：
JENSEN, HM
影响因子：
16
作者：
Ciccia A;Elledge SJ
通讯作者：
Elledge SJ