Combined analysis of murine and human microarrays and ChIP analysis reveals genes associated with the ability of MYC to maintain tumorigenesis.
Combined analysis of murine and human microarrays and ChIP analysis reveals genes associated with the ability of MYC to maintain tumorigenesis.
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DOI：
10.1371/journal.pgen.1000090
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发表时间：
2008-06-06
期刊：
影响因子：
4.5
通讯作者：
Felsher, Dean W.
中科院分区：
文献类型：
--
作者：
Wu, Chi-Hwa;Sahoo, Debashis;Arvanitis, Constadina;Bradon, Nicole;Dill, David L.;Felsher, Dean W.
MYC癌基因参与了多达数千个基因的调节，这些基因参与了许多细胞程序，包括增殖、生长、分化、自我更新和凋亡。MYC被认为是通过对这些生理程序的过度影响而诱发癌症。这些基因中的哪一个负责MYC启动和/或维持肿瘤发生的能力尚不清楚。以前，我们已经表明，在短暂的MYC失活后，一些肿瘤会持续消退。在这里，我们证明了MYC失活后，通过微阵列分析检测到的基因表达存在全局永久性变化。通过应用StepMiner分析，我们确定了与MYC诱导肿瘤状态的能力相关性最强的基因。值得注意的是，鉴定了在MYC失活后表现出mRNA表达永久变化的基因。重要的是，染色质免疫沉淀（ChIP）可以显示基因表达的永久性变化与MYC结合启动子区域的能力的永久性变化相关。通过将我们的分析与其他已发表的结果进行比较，进一步完善了与肿瘤维持相关的候选基因列表，以生成与MYC诱导的小鼠肿瘤发生相关的基因签名。为了验证与MYC相关的基因签名在人类肿瘤发生中的作用，我们检查了273个已发表的人类淋巴瘤微阵列数据集中人类同源物的表达。这些基因的一个大的功能组包括核糖体结构蛋白。此外，我们还鉴定了一组参与多种细胞功能的基因，包括：BZW 2、H2 AFY、SFRS 3、NAP 1 L1、NOLA 2、UBE 2D 2、CCNG 1、LIFR、FABP 3和EDG 1。因此，通过我们对小鼠肿瘤模型和人类淋巴瘤中基因表达的分析，我们已经确定了一种与MYC维持肿瘤发生能力相关的新基因特征。癌基因的靶向失活可能是一种特异有效的癌症治疗方法。然而，癌基因失活如何导致肿瘤消退尚不清楚。以前，我们已经表明，即使是短暂的MYC癌基因失活，也可以导致至少一些肿瘤的持续消退。为了理解这一机制，我们利用了几种新的基因组分析来确定一组与MYC癌基因维持肿瘤发生的能力密切相关的基因。首先，我们从小鼠肿瘤的微阵列分析中产生了一个新的数据集，我们通过StepMiner分析，以确定MYC癌基因失活或重新激活后基因表达的离散步骤变化。其次，我们利用布尔网络分析进一步确定了人类肿瘤发生中与MYC高度相关的基因子集。第三，我们利用ChIP分析来证明，在许多情况下，我们发现的基因表达的永久性变化与MYC占据启动子位点的能力变化有关。我们的一般策略可以类似地用于其他实验模型系统，以了解特定的癌基因如何有助于维持肿瘤发生。
The MYC oncogene has been implicated in the regulation of up to thousands of genes involved in many cellular programs including proliferation, growth, differentiation, self-renewal, and apoptosis. MYC is thought to induce cancer through an exaggerated effect on these physiologic programs. Which of these genes are responsible for the ability of MYC to initiate and/or maintain tumorigenesis is not clear. Previously, we have shown that upon brief MYC inactivation, some tumors undergo sustained regression. Here we demonstrate that upon MYC inactivation there are global permanent changes in gene expression detected by microarray analysis. By applying StepMiner analysis, we identified genes whose expression most strongly correlated with the ability of MYC to induce a neoplastic state. Notably, genes were identified that exhibited permanent changes in mRNA expression upon MYC inactivation. Importantly, permanent changes in gene expression could be shown by chromatin immunoprecipitation (ChIP) to be associated with permanent changes in the ability of MYC to bind to the promoter regions. Our list of candidate genes associated with tumor maintenance was further refined by comparing our analysis with other published results to generate a gene signature associated with MYC-induced tumorigenesis in mice. To validate the role of gene signatures associated with MYC in human tumorigenesis, we examined the expression of human homologs in 273 published human lymphoma microarray datasets in Affymetrix U133A format. One large functional group of these genes included the ribosomal structural proteins. In addition, we identified a group of genes involved in a diverse array of cellular functions including: BZW2, H2AFY, SFRS3, NAP1L1, NOLA2, UBE2D2, CCNG1, LIFR, FABP3, and EDG1. Hence, through our analysis of gene expression in murine tumor models and human lymphomas, we have identified a novel gene signature correlated with the ability of MYC to maintain tumorigenesis. The targeted inactivation of oncogenes may be a specific and effective treatment of cancer. However, how oncogene inactivation leads to tumor regression is not clear. Previously, we have shown that even the brief inactivation of the MYC oncogene can result in the sustained regression of at least some tumors. To understand the mechanism, we have utilized several novel genomic analyses to define a set of genes that strongly correlate with the ability of the MYC oncogene to maintain tumorigenesis. First, we generated a novel data set from microarray analyses of murine tumors that we analyzed by StepMiner to identify discrete step changes in gene expression after the inactivation or the reactivation of the MYC oncogene. Second, we utilized Boolean Network Analysis to further define the subset of genes highly correlated with MYC in human tumorigenesis. Third, we utilized ChIP analysis to demonstrate that in many cases the permanent changes of gene expression we uncovered were associated with changes in the ability of MYC to occupy the promoter locus. Our general strategy could be similarly utilized in other experimental model systems to understand how specific oncogenes contribute to the maintenance of tumorigenesis.
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