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

项目总结/摘要 对于卵巢癌（OvCa），只有27%的晚期诊断女性存活5年，但超过20%的女性存活5年。 90%的患者在早期诊断时存活。因此，迫切需要新的非... 能够在早期阶段快速诊断卵巢癌（OvCa）的侵入性技术。幸运的是，所有 细胞（以及更大程度上的肿瘤细胞）排出直接反映生物学特性的纳米级囊泡。 它们的母细胞的状态。称为外泌体的循环EV的子集由生物分子组成 跨越脂质，蛋白质，基因等的范围，并具有诊断和治疗的巨大潜力。 癌症的预后。然而，目前根据肿瘤相关性的检测对生物流体进行表型分型的方法并不多见。 外泌体（TEX）不符合临床标准并且不能精确地捕获颗粒到颗粒 异质性我们建议开发一种新的基于纳米等离子体的技术，用于灵敏地检测 通过多路复用表面增强拉曼光谱学实现的癌症相关外泌体生物特征， 我们称之为ExoSERS。我们的方法包括为实现ExoSERS平台而设计的三个目标。要求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 包括设计和合成基于多炔的配体，所述配体被设计为赋予拉曼光谱 编码并且还引发硅烷涂层以在纳米等离子体核心周围形成保护壳。目的2 描述了纳米等离子体核壳结构的合成和优化， 绑定EV。内部的金核结构产生等离子体增强，而外部的二氧化硅壳允许 长期稳定性和用于与外来体和癌症特异性表面共价修饰的方便表面 标记靶向剂。目的3包括验证该平台对人类OvCa患者进行特征分析的可行性 血浆，包括使用条形码方法对癌症进行分型的机器学习方法。的端点 平台表征将是外泌体检测效率的统计学验证，最小样品体积 需要，易于使用和低成本。已经提出了几个量化的里程碑来衡量我们的 取得进展，并为更大的诊断和循环生物标志物社区提供可交付成果。

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.