Thorgeirsson Snorri S, Lee Ju-Seog, Grisham Joe W
Laboratory of Experimental Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Hepatology. 2006 Feb;43(2 Suppl 1):S145-50. doi: 10.1002/hep.21063.
The majority of DNA-microarray based gene expression profiling studies on human hepatocellular carcinoma (HCC) has focused on identifying genes associated with clinicopathological features of HCC patients. Although notable success has been achieved, this approach still faces significant challenges due to the heterogeneous nature of HCC (and other cancers) as well as the many confounding factors embedded in gene expression profile data. However, these limitations are being overcome by improved bioinformatics and sophisticated analyses. Also, application of cross comparison of multiple gene expression data sets from human tumors and animal models are facilitating the identification of critical regulatory modules in the expression profiles. The success of this new experimental approach, comparative functional genomics, suggests that integration of independent data sets will enhance our ability to identify key regulatory elements in tumor development. Furthermore, integrating gene expression profiles with data from DNA sequence information in promoters, array-based CGH, and expression of non-coding genes (i.e., microRNAs) will further increase the reliability and significance of the biological and clinical inferences drawn from the data. The pace of current progress in the cancer profiling field, combined with the advances in high-throughput technologies in genomics and proteomics, as well as in bioinformatics, promises to yield unprecedented biological insights from the integrative (or systems) analysis of the combined cancer genomics database. The predicted beneficial impact of this "new integrative biology" on diagnosis, treatment and prevention of liver cancer and indeed cancer in general is enormous.
大多数基于DNA微阵列的人类肝细胞癌（HCC）基因表达谱研究都集中在识别与HCC患者临床病理特征相关的基因。尽管已取得显著成功，但由于HCC（以及其他癌症）的异质性以及基因表达谱数据中存在的许多混杂因素，这种方法仍然面临重大挑战。然而，通过改进的生物信息学和复杂的分析，这些局限性正在被克服。此外，对来自人类肿瘤和动物模型的多个基因表达数据集进行交叉比较，有助于识别表达谱中的关键调控模块。这种新的实验方法——比较功能基因组学的成功表明，整合独立数据集将增强我们识别肿瘤发生过程中关键调控元件的能力。此外，将基因表达谱与启动子中的DNA序列信息、基于阵列的比较基因组杂交以及非编码基因（即微小RNA）的表达数据相结合，将进一步提高从这些数据得出的生物学和临床推断的可靠性和重要性。癌症谱分析领域当前的进展速度，再加上基因组学、蛋白质组学以及生物信息学高通量技术的进步，有望从综合（或系统）分析联合癌症基因组数据库中获得前所未有的生物学见解。这种“新的整合生物学”对肝癌乃至一般癌症的诊断、治疗和预防预计将产生巨大的有益影响。
