A Roadmap to Successful Clinical Proteomics.
A Roadmap to Successful Clinical Proteomics.
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DOI：
10.1373/clinchem.2016.254664
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发表时间：
2017
影响因子：
9.3
通讯作者：
Ian Wright;J. V. Van Eyk
中科院分区：
文献类型：
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作者：
Ian Wright;J. V. Van Eyk
临床蛋白质组学已经取得了长足的进步，目前的专业知识、技术、分析方法和知识已经足够成熟，可以开始实现个性化和精准医疗。尽管传统的实验室医学似乎有点墨守陈规，但该领域现在开始利用一些必要的方法来监测一个人的健康或疾病的动态状态。不幸的是，这些定量方法通常是基于一种“静态”诊断模型，这种模型关注于描述已经发生的一些基本蛋白质变化，或者可能描述未来可能发生的情况的基因组标记。静态标志物是定义单一疾病实体或用于单一临床诊断的生物标志物，通常是有限的；我们可以做得更好。蛋白质组学有可能决定个人健康的“动态”，这是我们需要前进的理解水平。这需要对蛋白质组中重要的蛋白质修饰形式（蛋白质形式）有深入的了解和精确的定量，并认识到蛋白质形式是动态的，对个体的表型很重要，对决定当前和潜在的未来治疗反应至关重要。如果我们不能完全描述和理解我们正在测量的东西，我们可能会误诊或失去对特定疾病有更好选择性的生物标志物的机会。伴随诊断也是如此。除非这些检测方法能够捕捉到药物的机制（这通常发生在蛋白质组水平），否则这些检测方法可能无法指导良好的药物开发，并导致有希望的治疗方法在后期失败，这是大型制药公司面临的一个日益严重的问题。我们需要更全面地绘制我们正在测量的蛋白质，并在临床中利用它们的修饰形式。
Clinical proteomics has come a long way and is at a point where the expertise, technology, assays, and knowledge have matured sufficiently to begin enabling personalized and precision medicine. Although traditional laboratory medicine seems to be stuck in a bit of a rut, the field is now starting to take advantage of some of the approaches needed to monitor a person's dynamic state of health or disease. Unfortunately, these quantitative approaches have often been based on a “static” diagnostic model that focuses on a few basic protein changes describing what has happened, or genomic markers that might describe what possibly could happen in the future. Static markers are biomarkers that define a single disease entity or are used for a single clinical diagnosis are often limited; we can do better. Proteomics has the potential to determine the “dynamics” of an individual's health and this is the level of understanding we need to move toward. This requires an intimate knowledge and precise quantification of the important modified forms of proteins (proteoforms) within a proteome, and the recognition that proteoforms are dynamic and important to an individual's phenotype and crucial in determining the immediate present and potential future response to therapies. If we don't fully characterize and understand what we are measuring we could misdiagnose or lose an opportunity to have a biomarker(s) with a better selectivity toward a particular disease. This is also true for companion diagnostics. Unless the assays can capture the mechanism of the drug, which occurs most often at the proteome level, the assays could fail to guide good drug development and cause late stage failures of promising therapeutics, an increasingly acute problem for big pharmaceutical companies. We need to more fully map the proteins we are measuring and take advantage of their modified forms in our clinical …