Parallel analysis of transcript and translation profiles: identification of metastasis-related signal pathways differentially regulated by drug and genetic modifications.
Parallel analysis of transcript and translation profiles: identification of metastasis-related signal pathways differentially regulated by drug and genetic modifications.
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DOI：
10.1021/pr0504283
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发表时间：
2006-07
影响因子：
4.4
通讯作者：
Haiyan Yang;Li-Rong Yu;M. Yi;David A. Lucas;L. Lukes;M. Lancaster;King C. Chan;H. Issaq;R. Stephens;T. Conrads;T. Veenstra;K. Hunter
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文献类型：
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作者：
Haiyan Yang;Li-Rong Yu;M. Yi;David A. Lucas;L. Lukes;M. Lancaster;King C. Chan;H. Issaq;R. Stephens;T. Conrads;T. Veenstra;K. Hunter
肿瘤转移是一个复杂的多步骤过程，通常涉及多个信号转导通路的失调。在这项研究中，我们开发了一种新的方法，通过比较两种不同的转移抑制模型的全局基因和蛋白质表达，有效地确定与转移相关的失调途径。因此，我们确定了两种模型所共有的共同特征，这些特征可能与转移有关。高侵袭性多瘤中T诱导的小鼠乳腺肿瘤的转移效率被长时间的咖啡因暴露或将动物培育成低转移性小鼠品系所抑制。然后推导出两种转移抑制类型的原发性肿瘤的分子谱，以鉴定可能构成转移共同机制的分子和途径。一些差异调节的基因和蛋白质被确定，包括基因编码的基底膜组件，这是负相关的转移效率。此外，分析显示，Stat信号转导途径可能与转移抑制相关，如在遗传和药理学修饰模型中增强的Stat1活化和降低的Stat5磷酸化所证明的。低转移基因型的肿瘤细胞也表现出抗凋亡特性。这些途径在所有转移抑制系统中的共同变化表明它们可能是转移级联反应中的关键组分，至少在该模型系统中是如此。我们的数据表明，在转移相关的背景下，基因和蛋白质的共同变化的分析，大大降低了数据分析的复杂性，并可能作为一个筛选工具，以确定生物学的重要因素，从大规模的数据。
Tumor metastasis is a complex multistep process normally involving dysregulation of multiple signal transduction pathways. In this study, we developed a novel approach to efficiently define dysreguated pathways associated with metastasis by comparing global gene and protein expressions of two distinct metastasis-suppressed models. Consequently, we identified common features shared by the two models which are potentially associated with metastasis. The efficiency of metastasis from the highly aggressive polyoma middle T-induced mouse mammary tumors was suppressed by either prolonged caffeine exposure or by breeding the animal to a low metastatic mouse strain. Molecular profiles of the primary tumors from both metastasis-suppressed classes were then derived to identify molecules and pathways that might underlie a common mechanism of metastasis. A number of differentially regulated genes and proteins were identified, including genes encoding basement membrane components, which were inversely related to metastatic efficiency. In addition, the analysis revealed that the Stat signal transduction pathways were potentially associated with metastasis inhibition, as demonstrated by enhanced Stat1 activation, and decreased Stat5 phosphorylation in both genetic and pharmacological modification models. Tumor cells of low-metastatic genotypes also demonstrated anti-apoptotic properties. The common changes of these pathways in all of the metastasis-suppressed systems suggest that they may be critical components in the metastatic cascade, at least in this model system. Our data demonstrate that analysis of common changes in genes and proteins in a metastatic-related context greatly decrease the complexity of data analysis, and may serve as a screening tool to identify biological important factors from large scale data.