Fan Jianqing, Tam Paul, Vande Woude George, Ren Yi
Department of Operation Research and Financial Engineering, Princeton University, Princeton, NJ 08544, USA.
Proc Natl Acad Sci U S A. 2004 Feb 3;101(5):1135-40. doi: 10.1073/pnas.0307557100. Epub 2004 Jan 22.
The quantitative comparison of two or more microarrays can reveal, for example, the distinct patterns of gene expression that define different cellular phenotypes or the genes that are induced in the cellular response to certain stimulations. Normalization of the measured intensities is a prerequisite of such comparisons. However, a fundamental problem in cDNA microarray analysis is the lack of a common standard to compare the expression levels of different samples. Several normalization protocols have been proposed to overcome the variabilities inherent in this technology. We have developed a normalization procedure based on within-array replications via a semilinear in-slide model, which adjusts objectively experimental variations without making critical biological assumptions. The significant analysis of gene expressions is based on a weighted t statistic, which accounts for the heteroscedasticity of the observed log ratios of expressions, and a balanced sign permutation test. We illustrated the use of the techniques in a comparison of the expression profiles of neuroblastoma cells that were stimulated with a growth factor, macrophage migration inhibitory factor (MIF). The analysis of expression changes at mRNA levels showed that approximately 99 genes were up-regulated and 24 were reduced significantly (P <0.001) in MIF-stimulated neuroblastoma cells. The regulated genes included several oncogenes, growth-related genes, tumor metastatic genes, and immuno-related genes. The findings provide clues as to the molecular mechanisms of MIF-mediated tumor progression and supply therapeutic targets for neuroblastoma treatment.
对两个或更多微阵列进行定量比较,例如,可以揭示定义不同细胞表型的独特基因表达模式,或细胞对某些刺激作出反应时诱导表达的基因。测量强度的标准化是此类比较的先决条件。然而,cDNA微阵列分析中的一个基本问题是缺乏用于比较不同样品表达水平的通用标准。已经提出了几种标准化方案来克服该技术固有的变异性。我们通过半线性载玻片内模型,基于阵列内重复开发了一种标准化程序,该程序可客观地调整实验变化,而无需做出关键的生物学假设。基因表达的显著性分析基于加权t统计量和平衡符号置换检验,其中加权t统计量考虑了观察到的表达对数比值的异方差性。我们通过比较用生长因子巨噬细胞迁移抑制因子(MIF)刺激的神经母细胞瘤细胞的表达谱,说明了这些技术的用途。mRNA水平表达变化分析表明,在MIF刺激的神经母细胞瘤细胞中,约99个基因上调,24个基因显著下调(P<0.001)。上调的基因包括几种癌基因、生长相关基因、肿瘤转移基因和免疫相关基因。这些发现为MIF介导的肿瘤进展的分子机制提供了线索,并为神经母细胞瘤治疗提供了治疗靶点。