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

项目摘要/摘要 对于卵巢癌(OvCa)，被诊断为晚期的女性中只有27%的人能存活5年，但超过 90%的患者在早期确诊后仍能存活。因此，迫切需要新的非 能够早期快速诊断卵巢癌的侵入性技术。幸运的是，所有人 细胞(和更大程度上的肿瘤细胞)排出直接反映生物的纳米级小泡。 其父单元格的状态。被称为外体的循环中的EV的一个子集由生物分子组成 跨越脂质、蛋白质、基因和更多的范围，并具有巨大的诊断和 癌症的预后。然而，目前用于根据检测肿瘤相关的生物体液的表型的方法 Exosome(TES)不符合临床标准，不能准确地捕获颗粒到颗粒 异质性。我们建议开发一种基于纳米等离子体的新技术来灵敏地检测 由多路表面增强拉曼光谱实现的与癌症相关的外切体生物特征，即 我们称之为ExoSERS。我们的方法包括三个目标，旨在实现ExoSERS平台。目标1 概述了一类新的拉曼活性配体作为分子条形码的发展。这一目标 包括基于聚炔的配体的设计和合成，旨在提供拉曼光谱 编码并且还启动硅烷涂层以在纳米等离子核心周围形成保护壳。目标2 描述了纳米等离子体核壳结构的合成和优化，该结构将非常适合于 绑定电动汽车。内部的金核结构产生等离子体增强，而外层的二氧化硅外壳允许 长期稳定性和方便的表面，用于外切体和癌症特异性表面的共价修饰 标记物靶标特工。目标3包括验证该平台对人类OvCA患者进行分析的可行性 等离子体，包括使用条形码方法对癌症进行分类的机器学习方法。的端点 平台表征将统计验证外切体检测效率、最小样本量 所需、易于使用和低成本。已经提出了几个量化里程碑来衡量我们的 取得进展，并向更大的诊断和流通生物标志物社区提供交付成果。

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.