García-Escudero Ramón, Paramio Jesús M
Molecular Oncology Unit, Division of Biomedicine, CIEMAT, Madrid, Spain.
Mol Carcinog. 2008 Aug;47(8):573-9. doi: 10.1002/mc.20430.
The sequentiation of the human genome, together with the development of high throughput technologies, particularly gene-expression profiling, is giving us the opportunity to describe biological features in a quantitative manner. Here we review the use of global gene expression analyses in cancer research. Microarray analyses of tumor samples have allowed researchers the development of profiles that can distinguish, identify and classify discrete subsets of disease, predict the disease outcome, or the response to therapy. Profiling of experimental models with activation of certain oncogenic pathways could also be used to ascertain the molecular events involved in the establishment and development of tumors and, consequently, these models could be validated as tools for preclinical therapy. Furthermore, the detailed analysis of gene expression deregulation after response to the therapies in such models would allow us to predict the response to specific drugs, and to target the therapies to patients in search for individualized management of the disease.
人类基因组测序，以及高通量技术的发展，尤其是基因表达谱分析，使我们有机会以定量方式描述生物学特征。在此，我们综述全球基因表达分析在癌症研究中的应用。肿瘤样本的微阵列分析使研究人员能够开发出可区分、识别和分类疾病离散亚群、预测疾病结果或治疗反应的图谱。对具有某些致癌途径激活的实验模型进行分析，也可用于确定肿瘤发生和发展过程中涉及的分子事件，因此，这些模型可作为临床前治疗工具得到验证。此外，对此类模型中治疗反应后基因表达失调的详细分析，将使我们能够预测对特定药物的反应，并针对寻求疾病个体化管理的患者进行治疗。
