An integrated human organ-on-chip ultrasensitive miRNA detection platform for novel biomarker discovery

摘要 循环中的miRNAs已经被认为是疾病状态的特定生物标记物，包括一些最 流行的疾病，如心血管疾病和癌症。然而，使用miRNAs作为生物标志物是非常重要的 尽管最近在高通量miRNA图谱方面取得了进展，但仍具有挑战性。各种检测技术， 方案、连接和提取/纯化方法导致了不同的细胞和 不同条件下的生物流体。最重要的是，所有这些都需要数天的样本到答案的分析时间，因此 排除它们用于检测和监测心肌梗死等危及生命的紧急情况 (Mi)。一种快速、实时、无聚合酶链式反应的miRNA分析设备在精确度方面将是非常有价值的， 未来几年的个性化医疗。然而，即使是开发这样一个平台也是非常困难的 由于测试模型的限制。动物模型往往无法预测人类的反应；研究 不容易允许精确控制疾病事件或疾病事件的时间相关性 疾病状态和生物标记物的表达动态。为了应对这一挑战，在这项研究中，我们将制定一种 具有集成的attomole(AM)级miRNA传感功能的芯片上器官设备，我们将使用该设备 优化实时监测多个miRNAs的波动，以发现新的生物标记物。作为一种 立即应用，我们将从人类芯片上的心肌(MOC)作为临床相关模型和 模仿心脏病发作的过程。我们假设，使用具有超灵敏miRNA检测的MOC，我们 将发现一个独特的信号，表明在心肌梗死治疗期间再灌注损伤的开始。最后，我们会 使用临床血液样本测试传感器设备和miRNA签名。我们的微流控芯片器官 该平台将由四个基本组成部分组成：1)从人类诱导的组织工程化人MOC 多能干细胞(HiPSCs)，2)外体裂解单位，3)裂解RNA的浓缩单位，4) MiRNAs的检测单元。在目标1中，我们将这些组件耦合到完全集成的微流体中 站台。首先，我们将通过与人体组织和血液的比较来验证MOC模型的临床相关性 样本。然后，我们将表征和优化一种新型miRNA检测生物传感器的性能 MOC，并以成熟的miRNA分析技术为基准。在目标2中，我们将重点介绍多路传输 用于实时检测一组miRNA的传感方法，以及1)使用MOC来发现miRNA 签名将被用作捕捉RI起始的新型生物标志物，以及2)优化多路传输 传感器，用于更快的临床翻译。在目标3中，我们将确定诊断和预后能力 我们在AIMS 1和2中使用MOC模型开发的新型生物传感器和miRNA生物标志物签名，具有 心肌梗塞患者的临床标本。我们的长期目标是利用这个综合平台来研究外显体和 它们的RNA含量，以促进目前对它们在人类健康中的作用的理解，并确定它们的潜力 作为疾病状态的生物标志物。

Abstract Circulating miRNAs have proposed as specific biomarkers of disease states, including some of the most prevailing ones such as cardiovascular diseases and cancer. However using miRNAs as biomarkers is very challenging despite recent advances in high-throughput miRNA profiling. Various detection technologies, protocols, ligation and extraction/purification methods have led to varying miRNA profiling results of cells and biofluids under different conditions. Most importantly, all require days long sample-to-answer assay times, thus ruling them out for detection and monitoring of urgent, life threatening conditions such as myocardial infarction (MI). A rapid real-time, PCR-free miRNA-profiling device would be exceedingly valuable for precision, personalized medicine in years to come. However, it is very difficult to start even developing such a platform because of the limitations in testing models. Animal models often fail to predict responses in humans; and studies of human subjects do not readily allow for precise control over the disease events or temporal correlation of the disease state and biomarker expression dynamics. To address this challenge, in this study, we will develop an organ-on-a-chip device with an integrated attomolar (aM)-level miRNA sensing capability, which we will use for optimizing real-time monitoring of fluctuations in multiple miRNAs for novel biomarker discovery. As an immediate application, we will start with a human myocardium-on-chip (MoC) as a clinically relevant model and imitate the course of a heart attack. We hypothesize that using the MoC with ultrasensitive miRNA detection, we will discover a unique signature that indicates the onset of reperfusion injury during MI treatment. Finally, we will test the sensor device and the miRNA signature using clinical blood samples. Our microfluidic organ-on-a-chip platform will consist of four basic components: 1) the tissue engineered human MoC from human induced pluripotent stem cells (hiPSCs), 2) the exosome lysing unit, 3) the concentration unit for the lysed RNAs and 4) the detection unit for the miRNAs. In Aim 1, we will couple these components into a fully integrated microfluidic platform. First we will validate the clinical relevance of the MoC model by comparing with human tissue and blood samples. Then we will characterize and optimize the performance of a novel miRNA detection biosensor using MoC and benchmark it against established miRNA analysis techniques. In Aim 2 we will focus on multiplexing the sensing approach for the real-time detection of a panel of miRNAs, and 1) use the MoC to discover a miRNA signature to be used as a novel biomarker that captures the RI onset, as well as 2) to optimize the multiplexed sensor for faster clinical translation. In Aim 3 we will determine the diagnostic and prognostic capabilities of the novel biosensor and miRNA biomarker signature we developed in Aims 1 and 2 using the MoC model, with clinical samples from MI patients. Our long-term goal is to utilize this integrated platform to study exosomes and their RNA content to advance current understanding of their role in human health and to determine their potential as biomarkers for disease states.