Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.
Ann N Y Acad Sci. 2010 Oct;1210:34-44. doi: 10.1111/j.1749-6632.2010.05776.x.
Despite rapid progress in annotating the human genome, progress in biomarker discovery has been limited, in part, due to the restricted adoption of biomarker analysis in clinical trials. In this short review we present a roadmap to drive progress in the field of personalized cancer management and patient stratification. We suggest that improved understanding of disease biology and drug response in advance of clinical trial design would enable novel biomarkers to be identified and prospectively evaluated during early phase trials; there will also be value in banked material from completed clinical trials to identify and validate biomarkers. Such progress requires standardized tissue collection protocols, novel bioinformatics strategies integrated with functional genomics analysis, and next generation sequencing technologies. We argue that the failure to adopt these methods rapidly into clinical trial design will increase late stage drug attrition, waste trial resources, and risk patient harm within unselected cohorts.
尽管人类基因组注释取得了快速进展，但生物标志物的发现进展有限，部分原因是生物标志物分析在临床试验中的应用受到限制。在这篇简短的综述中，我们提出了一个推动个性化癌症管理和患者分层领域进展的路线图。我们建议，在临床试验设计之前，通过提高对疾病生物学和药物反应的理解，能够在早期临床试验中确定和前瞻性评估新的生物标志物；在已完成的临床试验中保存的材料也将有助于识别和验证生物标志物。此类进展需要标准化的组织采集协议、与功能基因组学分析相结合的新型生物信息学策略，以及下一代测序技术。我们认为，如果不能迅速将这些方法应用于临床试验设计，将会增加晚期药物淘汰率、浪费试验资源，并使未经选择的患者群体面临风险。
