Meso-plex miRNA and protein profiling for cancer diagnostics using chip-integrate

描述（由申请人提供）：随着对疾病发生和发展的复杂生物分子机制的日益清晰的了解，临床肿瘤学正准备通过应用多种分析工具来改进诊断、预后和治疗能力，实现个性化医疗的承诺。然而，总的来说，缺乏合适的技术来支持临床中的多路分析，特别是在疾病相关的miRNA和蛋白质组的分析方面，尽管它们具有明确的实用性。癌症发生和发展的复杂和异常机制只能通过测量多种生物标志物特征来揭示，并且在miRNA和蛋白质水平上，已经确定了大量假定的生物标志物，当与其他标志物组合在一起考虑时，它们显示出增强的预测价值。然而，许多发现技术并不适用于临床。对于mirna， qRT-PCR检测非常敏感，相对快速，成本效益高，但每次检测只能定量单个靶标的表达。相反，微阵列是容易复用的，但相当缓慢和昂贵。因此，迫切需要中位复合物诊断能力，从而可以使用快速，经济高效和高度可扩展的技术同时询问10个mirna的集中面板。再一次，在分析能力方面存在显著的差距，这限制了多重蛋白质组学在临床中的翻译。金标准酶联免疫吸附测定（ELISA）通常非常敏感，选择性和成本效益高，尽管大多数情况下是单组分。蛋白质微阵列是高度可复用的，但通常远不敏感，选择性较差，不适合临床环境。新兴的多路分析方法提供了一些改进，但尚未找到广泛的临床应用。芯片集成的硅光子传感器阵列最近作为一种固有的可扩展和可复用的生物分子分析技术出现，该应用旨在强大地验证这种强大的技术用于中膜肿瘤诊断。硅光子微环谐振器阵列具有多达128个唯一可寻址的传感器元件，以前已用于定量检测多路分析格式的核酸和蛋白质特征，并从复杂的临床相关样品矩阵中进行检测。重要的是，该技术起源于成熟的半导体处理方法，传感器阵列芯片可以大规模制造，以允许低成本分析（< 1美元/测量）。此外，这种方法的分子通用性将被用于同时分析来自同一临床样本的微rna （miRNA）和蛋白质表达-一种转化能力。虽然适用于任何癌症，但致命的多形性脑癌胶质母细胞瘤将是实验室和临床的模型。胶质母细胞瘤存在成熟的miRNA和蛋白质生物标志物，因此使所提出的努力完全处于技术验证阶段。

DESCRIPTION (provided by applicant): Armed with an increasingly clear picture of the complex biomolecular mechanisms of disease onset and progression, clinical oncology is poised to realize the promise of personalized medicine by applying multiplexed analytical tools for improved diagnostic, prognostic, and theranostic capabilities. However, there are, in general, a lack of suitable technologies to support multiplexed analyses in the clinic-particularly with respect to the analysis of disease-relevant miRNA and protein panels, despite their clearly established utility. Complex and aberrant mechanisms underlying cancer onset and progression can only be unraveled through the measurement of multiple biomarker signatures and at both the miRNA and protein level, a wealth of putative biomarkers have been identified that show enhanced predictive value when considered together with panels of other markers. However, many discovery technologies are not amenable to the clinic. For miRNAs, qRT-PCR assays are incredibly sensitive, relatively rapid, and cost effective, yet are only able to quantitte expression of a single target per assay. Conversely, microarrays are readily multiplexable, yet quite slow and expensive. Thus, there exists a pressing need for meso-plex diagnostic capabilities whereby focused panels of 10s of miRNAs can be simultaneously interrogated using rapid, cost effective, and highly scalable technologies. Again, there is a striking gap in analyticl capabilities that limit the translation of multiplexed proteomics into the clinic. The gold standar enzyme-linked immunosorbent assay (ELISA), is typically very sensitive, selective, and cost effective, though most often single-plex. Protein microarrays are highly multiplexable, but generally far less sensitive, less selective, and not amenable to the clinical setting. Emerging multiplexed analysis methodologies offer some improvements but have yet to find widespread clinical utility. Chip-integrated silicon photonic sensor arrays have recently emerged as an inherently scalable and multiplexable biomolecular analysis technology, and this application aims to robustly validate this powerful technology for meso-plex cancer diagnostics. Silicon photonic microring resonator arrays, having up to 128 uniquely address-able sensor elements, have been previously utilized to quantitatively detect nucleic acid and protein signatures in multiplexed assay formats and from within complex, clinically-relevant sample matrices. Importantly, the technology has its origin in well-established methods of semiconductor processing and sensor array chips can be scalably fabricated to allow low cost assays (<$1/measurement). Furthermore, the molecular generality of this methodology will be utilized to simultaneous profile micro-RNA (miRNA) and protein expression from the same clinical sample-a transformative capability. Although applicable to any cancer, the lethal brain cancer glioblastoma multiforme will be the laboratory and clinical model. Well-established miRNA and protein biomarkers exist for glioblastoma, thus keeping the proposed efforts entirely on technology validation.