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.

摘要 细胞外囊泡（EV）作为微创检测早期肿瘤的新型生物标志物具有巨大的潜力。 分期肿瘤，因为肿瘤大量分泌EV，这些EV在循环中积累，并且这些EV可以 调节肿瘤发生、发展和转移的转运因子。然而，目前大多数EV分析 这些方法需要在分析之前预先分离EV，并且是低通量的，对于临床应用是不切实际的。我们 最近开发了一种快速，稳健，无分离和廉价的测定，直接定量肿瘤来源的 小体积（1~5 µL）血清或血浆中的EV。在该测定中，结合对两种不同的抗原具有特异性的探针的EV被检测。 EV靶蛋白产生距离调节的纳米等离子体增强散射（nPES）效应， 灵敏检测特定EV。在一项初步研究中，我们使用nPES检测胰腺癌（PC）- 相关的EV标志物，以区分PC病例与非恶性对照（胰腺炎患者和 健康个体）具有高再现性、特异性和灵敏度。该检测也区分PC肿瘤 阶段和肿瘤对新辅助治疗的反应，优于广泛用于PC治疗的生物标志物CA 19 -9 考核我们的nPES检测平台具有研究和临床转化所需的多种功能：1）它 快速、高通量和廉价; 2）它不采用EV隔离，避免了EV的主要来源 测定变异性; 3）其稳健且可重复地定量来自小体积血清、血浆和血浆中的EV生物标志物 或尿，允许其用于人类疾病的小鼠模型的纵向分析;以及4）其可以容易地 适用于诊断和监测表达其他EV生物标志物的癌症。基于我们试点的成功 研究中，我们建议开发和验证一种自动化且高度可重复的nPES EV测定法，以实现快速 和准确的PC诊断。我们假设基于nPES的数字EV读取器将等于 或优于我们当前手动测定的分析性能。我们将建立一个诊断EV检测模型 通过检查据报道在EV表面富集的蛋白质的能力， 来自PC干细胞或PC起始细胞（例如，CD 44、CD 133和EpCAM）诊断早期 并与胰腺癌前病变、遗传性综合征或家族性胰腺癌进行鉴别 PC病史和胰腺正常的个体。具体而言，我们建议：（1）发展和 Chip-nPES平台的制造，以实现单EV分辨率; 2）自动化和完善我们的基于nPES的 数字EV读取器，以提高分析的可靠性和再现性。我们还将选择和验证候选人 用于PC诊断的EV捕获和检测抗体; 3）建立和评估诊断模型， 将EV生物标志物与已知的癌症关联整合;以及4）进行该测定的临床前验证 在第三方实验室。这项工作的成功结果将在以下方面产生重大的转化影响： 癌症管理，通过可靠和可获得的筛查，早期发现胰腺癌。