Digital Nanoplasmonic Quantification of Tumor-derived Extracellular Vesicles in Plasma Microsamples

血浆微样品中肿瘤源性细胞外囊泡的数字纳米等离子体定量

• 批准号: 10037327
• 负责人: Hua Lu
• 金额: $ 63.1万
• 依托单位: TULANE UNIVERSITY OF LOUISIANA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-25 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10037327
• 关键词: Address; Affect; Antibodies; Benign; Binding; Biological Assay; Biological Markers; Blood Circulation; Blood specimen; CA-19-9 Antigen; CD44 gene; CLIA certified; Cancer Detection; Cells; Clinical; Complex; Detection; Development; Diagnosis; Diagnostic; Disease; Early Diagnosis; Early treatment; Excision; Exhibits; Family history of; Guidelines; Image; Individual; Inherited; Institutes; Laboratories; Lesion; Longitudinal Studies; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of pancreas; Manuals; Methods; Microfabrication; Modeling; Monitor; Mus; Neoadjuvant Therapy; Neoplasm Metastasis; Non-Malignant; Operative Surgical Procedures; Pancreas; Pancreatitis; Patients; Performance; Pilot Projects; Plasma; Procedures; Proteins; Protocols documentation; Reader; Reagent; Regimen; Reporting; Reproducibility; Research; Resectable; Resistance; Resolution; Sampling; Sensitivity and Specificity; Serum; Source; Specificity; Surface; Syndrome; TACSTD1 gene; Therapeutic; Time; Treatment outcome; Tumor stage; Tumor-Derived; Urine; Validation; Variant; Vesicle; Work; advanced disease; base; cancer diagnosis; cancer stem cell; cancer therapy; clinical translation; cohort; design; digital; disorder control; early screening; extracellular vesicles; human disease; human model; improved; improved outcome; longitudinal analysis; minimally invasive; mouse model; nanoparticle; nanoplasmonic; novel; novel marker; pancreatic cancer model; pancreatic cancer patients; pre-clinical; predictive modeling; premalignant; response; sample collection; success; translational impact; treatment response; tumor; tumor initiation

ABSTRACT Extracellular vesicles (EVs) hold great potential as novel biomarkers for minimally invasive detection of early stage tumors, since tumors abundantly secrete EVs that accumulate in the circulation and these EVs can transport factors that regulate tumor initiation, progression, and metastasis. However, most current EV analysis methods require pre-isolation of EVs prior to analysis and are low-throughput and impractical for clinical use. We recently developed a rapid, robust, isolation-free and inexpensive assay that directly quantifies tumor-derived EVs in small volumes (1~5 µL) of serum or plasma. In this assay, EVs that bind probes specific for two different EV target proteins produce a distance-regulated nanoplasmon-enhanced scattering (nPES) effect that allows sensitive detection of specific EVs. In a pilot study we used a nPES assay for a pancreatic cancer (PC)- associated EV marker to distinguish PC cases from non-malignant controls (patients with pancreatitis and healthy individuals) with high reproducibility, specificity, and sensitivity. This assay also differentiated PC tumor stages and tumor responses to neoadjuvant, outperforming CA19-9, a biomarker widely used for PC therapy assessment. Our nPES assay platform has multiple features required for research and clinical translation: 1) It is rapid, high-throughput, and inexpensive; 2) it does not employ EV isolation, avoiding a major source of EV assay variation; 3) it robustly and reproducibly quantifies EV biomarkers from small volumes of serum, plasma or urine, allowing its use in longitudinal analysis of mouse models of human disease; and 4) it can be readily adapted to diagnose and monitor cancers that express other EV biomarkers. Based on the success of our pilot study, we propose to develop and validate an automated and highly reproducible nPES EV assay to allow rapid and accurate PC diagnosis in clinical settings. We hypothesize that a nPES-based digital EV reader will equal or outperform the analytical performance of our current manual assay. We will build a diagnostic EV assay model for early PC detection by examining the ability of proteins reported to be enriched on the surface of EVs derived from PC stem cells or PC-initiating cells (e.g., CD44, CD133 and EpCAM) to diagnose patients with early stage PC and to differentiate them from patients with pre-malignant pancreatic lesions, hereditary syndromes or family history of PC, and individuals with normal pancreases. Specifically, we propose to: 1) Development and fabrication of Chip-nPES platform to achieve single EV resolution; 2) automate and refine our nPES-based digital EV reader to enhance assay reliability and reproducibility. We will also select and validate candidate EV capture and detection antibodies for PC diagnosis; 3) establish and evaluate a diagnostic model that integrates EV biomarkers with known cancer-associations; and 4) perform a pre-clinical validation of this assay in a third-party laboratory. The successful results of this work would have a significant translational impact in cancer management, through reliable and accessible screens for early detection of pancreatic cancer.

抽象的 细胞外蔬菜（EVS）具有巨大的潜力，作为新型生物标志物，以微创检测到早期 阶段肿瘤，因为肿瘤绝对是在循环中积累的秘密电动汽车，这些电动汽车可以 调节肿瘤倡议，进展和转移的转运因子。但是，大多数当前的电动汽车分析 方法需要在分析之前预先隔离电动汽车，并且是低通量和不切实际的临床用途。我们 最近开发了一种快速，健壮，无隔离和廉价的测定法，该测定直接量化肿瘤的衍生 小体积（1-5 µL）血清或血浆中的电动汽车。在此测定中，绑定针对两个不同不同问题的EVS EV靶蛋白产生了远距离调节的纳米碎片增强散射（NPES）效应，允许 对特定电动汽车的敏感检测。在一项试点研究中，我们使用NPES分析进行胰腺癌（PC） - 相关的EV标记以将PC病例与非恶性对照区分开（胰腺炎患者和 健康个体）具有高可重现，特异性和灵敏度。该测定也区分了PC肿瘤 对新辅助的阶段和肿瘤反应，超过CA19-9，这是一种广泛用于PC治疗的生物标志物 评估。我们的NPE评估平台具有研究和临床翻译所需的多个功能：1） 快速，高通量和便宜； 2）它不采用电动汽车隔离，避免了电动汽车的主要来源 测定变化； 3）它可以从小体积，血浆中稳健且可重复地量化EV生物标志物 或尿液，允许其在人类疾病小鼠模型的纵向分析中使用； 4）很容易 适用于表达其他EV生物标志物的诊断和监测癌症。基于我们的飞行员的成功 研究，我们建议开发和验证自动化和高度再现的NPE EV分析，以允许快速 并在临床环境中进行准确的PC诊断。我们假设基于NPE的数字电动汽车读取器将等于 或超越当前手动测定的分析性能。我们将建立一个诊断EV分析模型 通过检查据报道富集在衍生的电动汽车表面的蛋白质的能力，以提早检测 从PC干细胞或PC发射细胞（例如CD44，CD133和EPCAM）诊断早期患者 PC并将其与恶性胰腺病变，遗传综合征或家族的患者区分开 PC的历史，胰腺正常的人。具体而言，我们建议：1）开发和 制造芯片-NPES平台以实现单个EV分辨率； 2）自动化和完善我们的基于NPE的 数字电动汽车读取器增强评估可靠性和可重复性。我们还将选择并验证候选人 电动汽车捕获和检测PC诊断的抗体； 3）建立和评估一个诊断模型 具有已知癌症促成的综合EV生物标志物； 4）对此测定法进行临床前验证 在第三方实验室。这项工作的成功结果将对 癌症管理，通过可靠且可访问的筛查，用于早期检测胰腺癌。