He Yudong D
Rosetta Impharmatics LLC, A wholly owned subsidiary of Merck & Co., Inc., 401 Terry Avenue North, Seattle, WA 98109, USA.
Cancer Biomark. 2006;2(3-4):103-33. doi: 10.3233/cbm-2006-23-404.
This paper discusses selected activities, issues, and challenges in recent development of analytical methods and applications in biomarker identification and validation using state-of-the-art genomic approaches. Molecular profiling via genomics, proteomics, and metabonomics has opened new windows to study disease states and biological systems. It has also provided exciting opportunities for novel applications in clinical research as well as in drug discovery and development. In the past several years, we have witnessed enormous progress resulting particularly from gene expression profiling of mRNA or transcriptomics. After a brief review on technology advances in gene expression profiling using microarrays, I mainly discuss recent developments of the genomic approaches to biomarker identification and validation in two major types of applications. The first type involves examples in cancer diagnostics and prognostics based on tumor gene expression profiling, whereas the second type involves biomarker applications in drug discovery and development. The focus will be on analytical methods and algorithms that have been developed in recent years facilitating biomarker discovery and application by leveraging genome-wide expression profiles derived from microarrays. Technical issues in experimental design, data processing, error modeling, quality control, figures of merit for performance evaluation, and meta-analysis related to biomarker discovery and application are also discussed. A case study of disease outcome prognosis for breast cancer patients based on tumor expression pattern is presented before closing remarks.
本文讨论了使用最先进的基因组方法在生物标志物鉴定和验证的分析方法及应用的最新发展中的特定活动、问题和挑战。通过基因组学、蛋白质组学和代谢组学进行的分子谱分析为研究疾病状态和生物系统打开了新窗口。它还为临床研究以及药物发现和开发中的新应用提供了令人兴奋的机会。在过去几年中，我们见证了特别是来自mRNA基因表达谱分析或转录组学的巨大进展。在简要回顾使用微阵列进行基因表达谱分析的技术进展之后，我主要讨论在两种主要应用类型中生物标志物鉴定和验证的基因组方法的最新发展。第一种类型涉及基于肿瘤基因表达谱分析的癌症诊断和预后的示例，而第二种类型涉及生物标志物在药物发现和开发中的应用。重点将放在近年来开发的分析方法和算法上，这些方法和算法通过利用从微阵列获得的全基因组表达谱来促进生物标志物的发现和应用。还讨论了实验设计、数据处理、误差建模、质量控制、性能评估的品质因数以及与生物标志物发现和应用相关的荟萃分析中的技术问题。在结束语之前，给出了一个基于肿瘤表达模式对乳腺癌患者疾病结局预后的案例研究。
