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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Removing intensity effects and identifying significant genes for Affymetrix arrays in macrophage migration inhibitory factor-suppressed neuroblastoma cells.
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Removing intensity effects and identifying significant genes for Affymetrix arrays in macrophage migration inhibitory factor-suppressed neuroblastoma cells.

机译：在巨噬细胞迁移抑制因子抑制的神经母细胞瘤细胞中去除强度效应并鉴定Affymetrix阵列的重要基因。

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A semilinear in-slide model is introduced to remove the intensity effect in the scanning process. It is demonstrated that the intensity effect can be estimated accurately and removed effectively. This normalization step is vital for Affymetrix arrays to reveal relevant biological results when comparing gene expression in multiple arrays. The normalized expression ratios are analyzed further by a modified two-sample t test along with a sieved permutation scheme for computing P values. The improved specificity and sensitivity are demonstrated by using a study on the impact of macrophage migration inhibitory factor (MIF) reduction in neuroblastoma cells. With semilinear in-slide model analysis, expression of 166 genes was altered with a P value no greater than 0.001. Among those genes, 44 were altered >2-fold. MIF-regulated genes associated with tumor development including IL-8 and C-met, which are overexpressed in many tumors, were down-regulated in MIF-reduced cells. On the other hand, some tumor-suppressor genes such as EPHB6, visinin-like protein 1 (VSNL-1), and BLU were up-regulated in MIF-reduced cells. In addition, we demonstrated that down-regulation of MIF expression could result in a reduction in cell proliferation and tumor growth in vitro and in vivo. Our data not only demonstrate that targeting MIF expression is a promising therapeutic strategy in human neuroblastoma therapy but also indicate the MIF target genes for additional study.
机译：引入半线性滑模模型以消除扫描过程中的强度影响。结果表明，强度效应可以准确估计并有效消除。当在多个阵列中比较基因表达时，此归一化步骤对于Affymetrix阵列揭示相关的生物学结果至关重要。通过修改的两样本t检验以及用于计算P值的筛分排列方案，进一步分析了标准化的表达率。通过对神经母细胞瘤细胞中巨噬细胞迁移抑制因子（MIF）减少的影响进行研究，证明了提高的特异性和敏感性。通过半线性滑模模型分析，改变了166个基因的表达，P值不大于0.001。在那些基因中，有44个被改变了> 2倍。在许多肿瘤中过表达的与肿瘤发展相关的MIF调控基因（包括IL-8和C-met）在MIF减少的细胞中被下调。另一方面，一些肿瘤抑制基因，如EPHB6，visinin样蛋白1（VSNL-1）和BLU在MIF减少的细胞中被上调。此外，我们证明了MIF表达的下调可能导致体外和体内细胞增殖和肿瘤生长的减少。我们的数据不仅证明靶向MIF表达在人类成神经细胞瘤治疗中是一种有前途的治疗策略，而且还指出了MIF目标基因有待进一步研究。

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