SERS diagnostics platform for liquid bioapsy analysis of tumor-associated exosomes

用于肿瘤相关外泌体液体活检分析的 SERS 诊断平台

• 批准号: 9973569
• 负责人: Randy Carney
• 金额: $ 56.46万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9973569
• 关键词: Address; Antibodies; Architecture; Area; Bar Codes; Binding; Biocompatible Materials; Biological; Biological Assay; Biological Markers; Blood; Blood Circulation; CA-125 Antigen; Cancer Detection; Cancer Patient; Cancer Prognosis; Cells; Chemicals; Clinical; Communities; Coupling; Detection; Development; Diagnosis; Diagnostic; Diagnostic Neoplasm Staging; Disease; Disease Management; Early Diagnosis; Engineering; Enzyme-Linked Immunosorbent Assay; Extinction (Psychology); Fingerprint; Genes; Goals; Gold; Heterogeneity; Human; Hybrids; Immune system; Libraries; Ligands; Lipids; Liquid substance; Literature; Logic; Machine Learning; Malignant Neoplasms; Malignant neoplasm of ovary; Mediating; Methods; Modality; Modeling; Molecular; Monitor; Multivariate Analysis; Nanostructures; Neoplasm Metastasis; Optics; Outcome; Parents; Pathology; Pathway interactions; Patients; Peptides; Phenotype; Physicians; Plasma; Play; Population; Process; Property; Proteins; Raman Spectrum Analysis; Recurrence; Reporting; Reproducibility; Research; Residual Tumors; Resolution; Role; Sampling; Sensitivity and Specificity; Series; Shapes; Silanes; Silicon Dioxide; Solid; Standardization; Structure; Study Subject; Surface; Techniques; Technology; Testing; Thick; Time; Training; Tumor Antigens; Untranslated RNA; Validation; Vesicle; Width; Woman; antigen binding; base; biomarker evaluation; biomaterial compatibility; cancer biomarkers; cancer cell; cancer drug resistance; cancer type; chemical fingerprinting; circulating biomarkers; clinical application; cost; design; diagnostic biomarker; early screening; exosome; experimental study; extracellular vesicles; improved; innovation; liquid biopsy; minimally invasive; multiplex detection; multiplexed imaging; nanoparticle; nanoplasmonic; nanoscale; nanosized; neoplastic cell; new technology; next generation; novel; particle; plasmonics; rapid diagnosis; recruit; small molecule; targeted agent; tumor; tumor growth; vesicle transport; vesicular release

Project Summary/Abstract For ovarian cancer (OvCa), only 27% of women diagnosed at advanced stages survive 5 years, yet more than 90% of patients survive when diagnosed at an earlier stage. Therefore, there is an urgent need for new non- invasive technologies capable of rapidly diagnosing ovarian cancers (OvCa) in early stage. Fortuitously, all cells (and tumor cells to a greater extent) expel nanoscale vesicles that are directly reflective of the biological state of their parent cells. A subset of circulating EVs known as exosomes are composed of biomolecules spanning the range of lipids, proteins, genes, and more, and hold great potential for the diagnosis and prognosis of cancer. Yet current methods for phenotyping biofluids according to detection of tumor-associated exosomes (TEXs) are not meeting clinical standards and fail to precisely capture particle to particle heterogeneity. We propose to develop a new nanoplasmonics-based technology for sensitive detection of cancer-related exosome bio-signatures enabled by multiplexed surface-enhanced Raman spectroscopy, that we call ExoSERS. Our approach encompasses three aims devised to realize the ExoSERS platform. Aim 1 outlines development of a new class of Raman-active ligands to serve as the molecular barcodes. This aim encompasses the design and synthesis of polyyne-based ligands designed to confer Raman spectroscopic encoding and also initiate a silane coating to form a protecting shell around a nanoplasmonic core. Aim 2 describes the synthesis and optimization of nanoplasmonic core-shell structures that will be well-suited to binding EVs. An inner gold core structure yields plasmonic enhancement, while the outer silica shell permits long-term stability and a convenient surface for covalent decoration with exosome and cancer-specific surface marker targeting agents. Aim 3 comprises validation of the platform’s feasibility to profile human OvCa patient plasma, including machine learning approaches to type cancers using the barcoded approach. Endpoints of platform characterization will be statistical validation of exosome detection efficiency, minimal sample volume needed, ease of utilization, and low cost. Several quantitative milestones have been proposed to gauge our progress and provide deliverables to the larger diagnostic and circulating biomarker communities.

项目概要/摘要 对于卵巢癌 (OvCa)，只有 27% 的晚期诊断女性能存活 5 年，但超过 90%的患者在早期诊断时可以存活，因此迫切需要新的非治疗药物。 幸运的是，能够在早期快速诊断卵巢癌（OvCa）的侵入性技术。 细胞（以及更大程度上的肿瘤细胞）排出纳米级囊泡，这些囊泡直接反映了生物 循环 EV 的一个子集（称为外泌体）由生物分子组成。 涵盖脂质、蛋白质、基因等范围，在诊断和诊断方面具有巨大的潜力 目前根据肿瘤相关检测对生物体液进行表型分析的方法。 外泌体（TEX）不符合临床标准，无法精确捕获颗粒 我们建议开发一种新的基于纳米等离子体技术的灵敏检测。 通过多重表面增强拉曼光谱实现与癌症相关的外泌体生物特征， 我们称之为 ExoSERS。我们的方法包含旨在实现 ExoSERS 平台的三个目标。 概述了作为分子条形码的新型拉曼活性配体的开发。 包括设计和合成基于聚炔的配体，旨在赋予拉曼光谱 编码并引发硅烷涂层以在纳米等离子体核心周围形成保护壳 Aim 2。 描述了纳米等离子体核壳结构的合成和优化，该结构非常适合 内部金核结构产生等离子体增强，而外部二氧化硅壳允许 长期稳定性和方便的外泌体共价修饰表面和癌症特异性表面 目标 3 包括验证该平台分析人类 OvCa 患者的可行性。 等离子，包括使用条形码端点对癌症进行分类的机器学习方法。 平台表征将是外泌体检测效率、最小样本量的统计验证 已经提出了几个量化里程碑来衡量我们的需求、易用性和低成本。 取得进展并为更大的诊断和循环生物标志物社区提供成果。