Dennis Jayne L, Oien Karin A
Department of Cancer Medicine, Imperial College of Science, Technology and Medicine at Hammersmith Hospital, London, UK.
J Pathol. 2005 Jan;205(2):236-47. doi: 10.1002/path.1702.
In 1995, two methods of genome-wide expression profiling were first described: expression microarrays and serial analysis of gene expression (SAGE). In the subsequent 10 years, many hundreds of papers have been published describing the application of these technologies to a wide spectrum of biological and clinical questions. Common to all of this research is a basic process of data gathering and analysis. The techniques and statistical and bio-informatic tools involved in this process are reviewed. The processes of class discovery (using clustering and self-organizing maps), class prediction (weighted voting, k nearest neighbour, support vector machines, and artificial neural networks), target identification (fold change, discriminant analysis, and principal component analysis), and target validation (RT-PCR and tissue microarrays) are described. Finally, the diagnostic problem of adenocarcinomas that present as metastases of unknown origin is reviewed, and it is demonstrated how integration of expression profiling techniques promises to throw new light on this important clinical challenge.
1995年,首次描述了两种全基因组表达谱分析方法:表达微阵列和基因表达序列分析(SAGE)。在随后的10年里,发表了数百篇论文,描述了这些技术在广泛的生物学和临床问题中的应用。所有这些研究的共同之处在于一个基本的数据收集和分析过程。本文回顾了该过程中涉及的技术以及统计和生物信息学工具。描述了类别发现(使用聚类和自组织映射)、类别预测(加权投票、k近邻、支持向量机和人工神经网络)、目标识别(倍数变化、判别分析和主成分分析)以及目标验证(逆转录聚合酶链反应和组织微阵列)的过程。最后,对表现为不明来源转移灶的腺癌的诊断问题进行了回顾,并展示了表达谱分析技术的整合如何有望为这一重要的临床挑战带来新的启示。