Abdullah-Sayani Ambreen, Bueno-de-Mesquita Jolien M, van de Vijver Marc J
Department of Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Nat Clin Pract Oncol. 2006 Sep;3(9):501-16. doi: 10.1038/ncponc0587.
Scientific advances in the field of genetics and gene-expression profiling have revolutionized the concept of patient-tailored treatment. Analysis of differential gene-expression patterns across thousands of biological samples in a single experiment (as opposed to hundreds to thousands of experiments measuring the expression of one gene at a time), and extrapolation of these data to answer clinically pertinent questions such as those relating to tumor metastatic potential, can help define the best therapeutic regimens for particular patient subgroups. The use of microarrays provides a powerful technology, allowing in-depth analysis of gene-expression profiles. Currently, microarray technology is in a transition phase whereby scientific information is beginning to guide clinical practice decisions. Before microarrays qualify as a useful clinical tool, however, they must demonstrate reliability and reproducibility. The high-throughput nature of microarray experiments imposes numerous limitations, which apply to simple issues such as sample acquisition and data mining, to more controversial issues that relate to the methods of biostatistical analysis required to analyze the enormous quantities of data obtained. Methods for validating proposed gene-expression profiles and those for improving trial designs represent some of the recommendations that have been suggested. This Review focuses on the limitations of microarray analysis that are continuously being recognized, and discusses how these limitations are being addressed.
遗传学和基因表达谱领域的科学进展彻底改变了患者个性化治疗的概念。在单个实验中分析数千个生物样本的差异基因表达模式（与一次测量一个基因表达的数百至数千个实验相反），并推断这些数据以回答临床相关问题，如与肿瘤转移潜能相关的问题，有助于为特定患者亚组确定最佳治疗方案。微阵列的使用提供了一种强大的技术，能够对基因表达谱进行深入分析。目前，微阵列技术正处于一个过渡阶段，在此阶段科学信息开始指导临床实践决策。然而，在微阵列成为一种有用的临床工具之前，它们必须证明可靠性和可重复性。微阵列实验的高通量特性带来了许多限制，这些限制适用于诸如样本采集和数据挖掘等简单问题，也适用于与分析所获大量数据所需的生物统计分析方法相关的更具争议性的问题。验证提议的基因表达谱的方法以及改进试验设计的方法是已提出的一些建议。本综述重点关注不断被认识到的微阵列分析的局限性，并讨论如何应对这些局限性。
