Daily Quantification of Cancer-Associated Exosomal miRNA in Patient Blood by Photonic Crystal-Enhanced Quantum Dot Emission

摘要 这项提案的首要目标是开发一种新技术，可以让患者反复测量 基于核酸的癌症生物标志物从一滴血的基础上每天。该检测方法正在开发中 用于特定的临床应用，以确定药物治疗效果，预测生存率，并监测治疗后 通过评估从肿瘤脱落到癌症患者血液中的候选核酸来进行治疗干预。 我们专注于检测microRNA，因为我们的团队最近发现， 用于转移性前列腺癌患者。我们假设，通过测量 这些标志物在患者治疗过程中频繁出现的基础上，我们可以精确地调整治疗 个体患者的治疗方案。然而，准确测量血液中的microRNA需要极高的 由于低浓度、宽浓度范围内的检测和高序列， 特异性，目前不可能用于常规筛查手指针刺血样的属性， 标准检测方法，如PCR。为此，我们的临床需求激发了一种新的形式， 通过在显微镜中直接进行分子计数来测量血液中的核酸的测定。现在这已经成为可能 因为我们已经开发出了新的方法来放大来自单个分子的信号， 协同技术，包括发光量子点，电场增强光子晶体， 微RNA的单步序列特异性酶促生长。我们现在将联合收割机结合这些技术， 使用已经在临床诊断中可用的低成本设备测量微小RNA的阶段 实验室，以尽量减少临床采用的转化障碍。为了实现这些目标，我们的研究人员 团队在单分子成像探针（Andrew Smith）、低分子光学检测、 成本设备（Brian Cunningham），临床肿瘤学（Manish Kohli），生物标志物发现（Liang Wang），以及 流行病学/生物统计学（丽贝卡·史密斯）。我们将优化我们的平台，使用合成和 临床血液标本，并彻底分析我们的检测序列的选择性，特别是侧重于 microRNA变异，并密切比较我们的结果与定量PCR检测。在年底前 在授予期间，我们预计将开发出第一个用于人类样本的直接读出microRNA检测 与低成本设备兼容，优化了量子点之间的协同整合， 光子晶体，并首次测量了血液中microRNA的精确（数字）浓度 前瞻性入组100例受试者，在标准治疗期间各随访6天以上 目前在转移性前列腺癌的治疗中不存在预测或预后生物标志物的治疗 癌如果成功，这项工作的结果将填补如何匹配和 精细地调整治疗以适应个体的分子分布。

ABSTRACT The primary goal of this proposal is to develop a new technology that can allow patients to repeatedly measure nucleic acid-based cancer biomarkers from a single drop of blood on a daily basis. This assay is being developed for specific clinical applications to determine drug treatment efficacies, prognosticate survival, and monitor post- treatment intervention by evaluating candidate nucleic acids shed from the tumor into blood of a cancer patient. We are focusing on detecting microRNA due to a very strong correlation with survival that our team has recently identified for patients with metastatic prostate cancer. We hypothesize that by measuring the concentrations of these markers in patients on a frequent basis during the course of therapy, we can precisely adjust therapeutic regimens for individual patients. However, accurately measuring microRNA in blood requires an extremely high limit of detection due to low concentrations, detection over a broad range of concentrations, and high sequence- specificity, attributes that are not currently possible for routine screening of fingerstick blood samples using standard methods of detection, such as PCR. Toward this end, our clinical needs have inspired a new form of assay to measure nucleic acids in blood through direct molecular counting in a microscope. This is now possible because we have developed novel ways to amplify the signals from individual molecules through a series of synergistic technologies, including light-emitting quantum dots, electric field-enhancing photonic crystals, and single-step sequence-specific enzymatic growth of microRNA. We now will combine these technologies to set the stage for measurement of microRNA using low-cost equipment that is already available in clinical diagnostic laboratories to minimize translational barriers to clinical adoption. To achieve these goals, our multi-investigator team has extensive expertise in probes for single-molecule imaging (Andrew Smith), optical detection in low- cost devices (Brian Cunningham), clinical oncology (Manish Kohli), biomarker discovery (Liang Wang), and epidemiology/biostatistics (Rebecca Smith). We will optimize our platform using a combination of synthetic and clinical blood specimens and thoroughly analyze the sequence selectivity of our assay, particularly focusing on microRNA variants, and closely compare our results with those from quantitative PCR assays. By the end of this award period, we expect to have developed the first direct-readout microRNA assay for use in human samples that is compatible with low-cost equipment, optimized the synergistic integration between quantum dots and photonic crystals, and measured, for the first time, the precise (digital) concentrations of microRNA in the blood of 100 subjects, prospectively enrolled and followed over 6 days each during the course of standard of care treatments for which no predictive or prognostic biomarkers currently exist in the treatment of metastatic prostate cancer. If successful, the outcome of this work will fill a major clinical gap in knowledge of how to match and finely tune treatments to individual molecular profiles.