Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling.
Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling.
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基于微阵列基因表达分析的跨物种肝癌分析的生物信息学方法。
DOI：
10.1186/1471-2105-6-s2-s6
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发表时间：
2005-07-15
影响因子：
3
通讯作者：
Dragan, YP
中科院分区：
文献类型：
--
作者：
Fang, H;Tong, W;Perkins, R;Shi, L;Hong, H;Cao, X;Xie, Q;Yim, SH;Ward, JM;Pitot, HC;Dragan, YP
人类、小鼠和大鼠基因组测序的完成以及跨物种基因同源性的了解使得能够研究动物模型中差异基因表达。这类研究有可能极大地增强我们对人类肝癌等疾病的了解。跨多个物种共表达的基因最有可能具有保守的功能。我们使用各种生物信息学方法来检查白蛋白 SV40 转基因大鼠中出现的肝脏肿瘤的微阵列表达谱，以阐明可能与人类肝癌相关的基因、染色体畸变和途径。在这项研究中，我们首先通过使用 F 检验比较两个对照、两个腺瘤和两个癌样本的基因表达谱，鉴定了 2223 个差异表达基因。随后使用一种新颖的可视化工具“染色体图”将这些基因映射到大鼠染色体。使用相同的图，我们进一步将重要基因映射到人和小鼠的直系同源染色体位置。大鼠 1q 中表达的许多基因在大鼠肝癌中扩增，映射到人类 10、11 和 19 号染色体以及小鼠 7、17 和 19 号染色体，这些基因与人类和小鼠肝癌的研究有关。使用比较基因组微阵列分析（CGMA），我们确定了人类潜在畸变的区域。最后，根据统计分析和从大鼠数据推断，进行路径分析以预测改变的人类路径。已知所有已确定的途径在人类肝癌的病因学中都很重要，包括细胞周期控制、细胞生长和分化、细胞凋亡、转录调节和蛋白质代谢。该研究表明，白蛋白-SV40转基因大鼠模型的肝脏基因表达谱揭示了与人类肝癌的实验和临床研究一致的基因、通路和染色体改变。本文提出的生物信息学工具对于微阵列数据的跨物种外推和绘图、分析和解释至关重要。
The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation.