Department of Pharmacology, Medical School, University of Athens, Athens, Greece.
Pharmacogenomics J. 2012 Jun;12(3):185-96. doi: 10.1038/tpj.2011.53. Epub 2012 Jan 17.
The advent of microarrays over the past decade has transformed the way genome-wide studies are designed and conducted, leading to an unprecedented speed of acquisition and amount of new knowledge. Microarray data have led to the identification of molecular subclasses of solid tumors characterized by distinct oncogenic pathways, as well as the development of multigene prognostic or predictive models equivalent or superior to those of established clinical parameters. In the field of molecular-targeted therapy for cancer, in particular, the application of array-based methodologies has enabled the identification of molecular targets with 'key' roles in neoplastic transformation or tumor progression and the subsequent development of targeted agents, which are most likely to be active in the specific molecular setting. Herein, we present a summary of the main applications of whole-genome expression microarrays in the field of molecular-targeted therapies for solid tumors and we discuss their potential in the clinical setting. An emphasis is given on deciphering the molecular mechanisms of drug action, identifying novel therapeutic targets and suitable agents to target them with, and discovering molecular markers/signatures that predict response to therapy or optimal drug dose for each patient.
过去十年中,微阵列的出现改变了全基因组研究的设计和实施方式,使得新知识的获取速度和数量达到了前所未有的水平。微阵列数据已经确定了具有不同致癌途径的实体瘤的分子亚型,并开发了多基因预后或预测模型,这些模型与既定的临床参数相当或优于这些模型。在癌症的分子靶向治疗领域,特别是基于阵列的方法的应用使得能够鉴定在肿瘤转化或肿瘤进展中具有“关键”作用的分子靶标,并随后开发靶向药物,这些药物最有可能在特定的分子环境中发挥作用。在此,我们总结了全基因组表达微阵列在实体瘤分子靶向治疗领域的主要应用,并讨论了它们在临床环境中的潜力。重点是破译药物作用的分子机制,确定新的治疗靶点和合适的药物来靶向它们,并发现预测治疗反应或每个患者最佳药物剂量的分子标志物/特征。