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Building risk-on-a-chip models to improve breast cancer risk assessment and prevention

机译:建立单芯片风险模型以改善乳腺癌风险评估和预防

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摘要

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.
机译:预防慢性病具有改善生活和降低医疗费用的希望。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。这些因素大多数的影响尚未在生物,组织,细胞和分子水平上得到充分理解。重要的是,外部和内部风险与保护因素的组合涉及协同作用,因此协同或拮抗疾病发作。需要模型来在确定的细胞和微环境条件下以机械方式破译癌症风险。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,并提出使用芯片实验室方法来改进风险建模。我们建议上皮组织极性,DNA修复和表观遗传学谱作为风险评估模型中的终点,并讨论整合这些终点生物传感器和一般组织动态平衡的“芯片风险”的发展。芯片风险将帮助识别风险的生物标志物,充当癌症预防剂的筛选平台,并提供对风险机制的更好理解,从而带来疾病预防方面的新进展。

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