Sci Transl Med. 2010 Aug 25;2(46):46ps42. doi: 10.1126/scitranslmed.3001249.
Clinical proteomics has yielded some early positive results-the identification of potential disease biomarkers-indicating the promise for this analytical approach to improve the current state of the art in clinical practice. However, the inability to verify some candidate molecules in subsequent studies has led to skepticism among many clinicians and regulatory bodies, and it has become evident that commonly encountered shortcomings in fundamental aspects of experimental design mainly during biomarker discovery must be addressed in order to provide robust data. In this Perspective, we assert that successful studies generally use suitable statistical approaches for biomarker definition and confirm results in independent test sets; in addition, we describe a brief set of practical and feasible recommendations that we have developed for investigators to properly identify and qualify proteomic biomarkers, which could also be used as reporting requirements. Such recommendations should help put proteomic biomarker discovery on the solid ground needed for turning the old promise into a new reality.
临床蛋白质组学已经取得了一些初步的积极成果——鉴定出了有潜力的疾病生物标志物，这表明这种分析方法有望提高临床实践的现有水平。然而，在后续研究中无法验证一些候选分子，这导致许多临床医生和监管机构持怀疑态度，很明显，在生物标志物发现过程中，实验设计的基本方面通常会遇到的缺陷必须得到解决，以便提供可靠的数据。在本观点中，我们断言，成功的研究通常使用合适的统计方法来定义生物标志物，并在独立的测试集中确认结果；此外，我们还描述了一套简短的实用且可行的建议，供研究人员正确地识别和定性蛋白质组生物标志物，这些建议也可以作为报告要求。这些建议应该有助于将蛋白质组生物标志物的发现置于坚实的基础之上，从而将旧的承诺转化为新的现实。
