Suppr超能文献

用于生物标志物发现、诊断和治疗的高度多重化蛋白质组学平台。

Highly multiplexed proteomic platform for biomarker discovery, diagnostics, and therapeutics.

机构信息

SomaLogic, Inc., 2945 Wilderness Place, Boulder, CO 80301, USA

出版信息

Adv Exp Med Biol. 2013;735:283-300. doi: 10.1007/978-1-4614-4118-2_20.

Abstract

Progression from health to disease is accompanied by complex changes in protein expression in both the circulation and affected tissues. Large-scale comparative interrogation of the human proteome can offer insights into disease biology as well as lead to the discovery of new biomarkers for diagnostics, new targets for therapeutics, and can identify patients most likely to benefit from treatment. Although genomic studies provide an increasingly sharper understanding of basic biological and pathobiological processes, they ultimately only offer a prediction of relative disease risk, whereas proteins offer an immediate assessment of "real-time" health and disease status. We have recently developed a new proteomic technology, based on modified aptamers, for biomarker discovery that is capable of simultaneously measuring more than a thousand proteins from small volumes of biological samples such as plasma, tissues, or cells. Our technology is enabled by SOMAmers (Slow Off-rate Modified Aptamers), a new class of protein binding reagents that contain chemically modified nucleotides that greatly expand the physicochemical diversity of nucleic acid-based ligands. Such modifications introduce functional groups that are absent in natural nucleic acids but are often found in protein-protein, small molecule-protein, and antibody-antigen interactions. The use of these modifications expands the range of possible targets for SELEX (Systematic Evolution of Ligands by EXponential Enrichment), results in improved binding properties, and facilitates selection of SOMAmers with slow dissociation rates. Our assay works by transforming protein concentrations in a mixture into a corresponding DNA signature, which is then quantified on current commercial DNA microarray platforms. In essence, we take advantage of the dual nature of SOMAmers as both folded binding entities with defined shapes and unique nucleic acid sequences recognizable by specific hybridization probes. Currently, our assay is capable of simultaneously measuring 1,030 proteins, extending to sub-pM detection limits, an average dynamic range of each analyte in the assay of > 3 logs, an overall dynamic range of at least 7 logs, and a throughput of one million analytes per week. Our collection includes SOMAmers that specifically recognize most of the complement cascade proteins. We have used this assay to identify potential biomarkers in a range of diseases such as malignancies, cardiovascular disorders, and inflammatory conditions. In this chapter, we describe the application of our technology to discovering large-scale protein expression changes associated with chronic kidney disease and non-small cell lung cancer. With this new proteomics technology-which is fast, economical, highly scalable, and flexible--we now have a powerful tool that enables whole-proteome proteomics, biomarker discovery, and advancing the next generation of evidence-based, "personalized" diagnostics and therapeutics.

摘要

从健康到疾病的进展伴随着循环和受影响组织中蛋白质表达的复杂变化。对人类蛋白质组的大规模比较研究可以深入了解疾病生物学,并为诊断学发现新的生物标志物、治疗学的新靶点提供依据,还可以识别最有可能从治疗中受益的患者。尽管基因组研究提供了对基本生物学和病理生物学过程的日益精确的理解,但它们最终只能提供相对疾病风险的预测,而蛋白质则可以即时评估“实时”健康和疾病状况。我们最近开发了一种新的基于修饰适体的蛋白质组学技术,用于发现生物标志物,该技术能够从小体积的生物样本(如血浆、组织或细胞)中同时测量一千多种蛋白质。我们的技术是通过 SOMAmers(Slow Off-rate Modified Aptamers,慢释放修饰适体)实现的,这是一种新的蛋白质结合试剂,包含化学修饰的核苷酸,大大扩展了基于核酸的配体的物理化学多样性。这种修饰引入了在天然核酸中不存在但在蛋白质-蛋白质、小分子-蛋白质和抗体-抗原相互作用中经常发现的功能基团。这些修饰的使用扩展了 SELEX(通过指数富集的配体系统进化)的可能目标范围,导致结合性能得到改善,并促进了具有缓慢解离速率的 SOMAmers 的选择。我们的测定方法通过将混合物中的蛋白质浓度转化为相应的 DNA 特征来工作,然后在当前的商业 DNA 微阵列平台上对其进行定量。从本质上讲,我们利用 SOMAmers 的双重性质,即具有特定形状的折叠结合实体和可通过特定杂交探针识别的独特核酸序列。目前,我们的测定方法能够同时测量 1030 种蛋白质,检测限低至亚皮摩尔,测定中每个分析物的平均动态范围大于 3 个对数,总动态范围至少为 7 个对数,每周可处理 100 万个分析物。我们的集合包括专门识别补体级联蛋白的大多数 SOMAmers。我们已经使用该测定法在一系列疾病(如恶性肿瘤、心血管疾病和炎症性疾病)中鉴定潜在的生物标志物。在本章中,我们描述了该技术在发现与慢性肾病和非小细胞肺癌相关的大规模蛋白质表达变化中的应用。通过这项新的蛋白质组学技术——快速、经济、高度可扩展和灵活——我们现在拥有了一种强大的工具,可以实现全蛋白质组蛋白质组学、生物标志物发现,并推进下一代基于证据的“个性化”诊断和治疗。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验