Department of Physiology, Ajou University School of Medicine, Suwon, Korea.
Mol Carcinog. 2011 Apr;50(4):235-43. doi: 10.1002/mc.20691.
Gene expression profiling using microarray technologies provides a powerful approach to understand complex biological systems and the pathogenesis of diseases. In the field of liver cancer research, a number of genome-wide profiling studies have been published. These studies have provided gene sets, that is, signature, which could classify tumors and predict clinical outcomes such as survival, recurrence, and metastasis. More recently, the application of genomic profiling has been extended to identify molecular targets, pathways, and the cellular origins of the tumors. Systemic and integrative analyses of multiple data sets and emerging new technologies also accelerate the progress of the cancer genomic studies. Here, we review the genomic signatures identified from the genomic profiling studies of hepatocellular carcinoma (HCC), and categorize and characterize them into prediction, phenotype, function, and molecular target signatures according to their utilities and properties. Our classification of the signatures would be helpful to understand and design studies with extended application of genomic profiles.
使用微阵列技术进行基因表达谱分析为理解复杂的生物系统和疾病的发病机制提供了一种强大的方法。在肝癌研究领域,已经发表了许多全基因组分析研究。这些研究提供了基因集,即特征,可以对肿瘤进行分类,并预测生存、复发和转移等临床结局。最近,基因组分析的应用已扩展到确定肿瘤的分子靶标、途径和细胞起源。对多个数据集的系统和综合分析以及新兴新技术也加速了癌症基因组研究的进展。在这里,我们回顾了从肝细胞癌 (HCC) 的基因组分析研究中确定的基因组特征,并根据其用途和特性将其分类为预测、表型、功能和分子靶标特征。我们对特征的分类有助于理解和设计具有基因组特征广泛应用的研究。