Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
CPT Pharmacometrics Syst Pharmacol. 2013 Mar 27;2(3):e35. doi: 10.1038/psp.2013.11.
Genome-wide expression data from tumors and cell lines in breast cancer, together with drug response of cell lines, open prospects for integrative analyses that can lead to better personalized therapy. Drug responses and expression data collected from cell lines and tumors were used to generate tripartite networks connecting clusters of patients to cell lines and cell lines to drugs, to connect drugs to patients. Various approaches were applied to connect cell lines to tumor clusters: a standard method that uses a biomarker gene set, and new methods that compute metasignatures for transcription factors and histone modifications given upregulated genes in cell lines or tumors. The results from the metasignature analysis identify two major clusters of patients: one enriched for active histone marks and one for repressive marks. The tumors enriched for activation marks are correlated with poor prognosis. Overall, the analyses suggest new patient clustering, discover dysregulated pathways, and recommend individualized use of drugs to treat subsets of patients.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e35; doi:10.1038/psp.2013.11; advance online publication 27 March 2013.
乳腺癌肿瘤和细胞系的全基因组表达数据,以及细胞系的药物反应,为能够实现更好的个体化治疗的综合分析开辟了前景。从细胞系和肿瘤中收集的药物反应和表达数据用于生成连接患者簇与细胞系以及细胞系与药物的三方网络,以将药物与患者连接起来。应用各种方法将细胞系连接到肿瘤簇:一种使用生物标志物基因集的标准方法,以及一种在细胞系或肿瘤中上调基因的情况下计算转录因子和组蛋白修饰元签名的新方法。元签名分析的结果确定了两个主要的患者簇:一个富含活性组蛋白标记,另一个富含抑制性标记。富含激活标记的肿瘤与预后不良相关。总体而言,这些分析表明了新的患者聚类,发现了失调的途径,并建议对某些患者亚群使用个体化药物治疗。CPT:药物代谢动力学和系统药理学(2013 年)2,e35;doi:10.1038/psp.2013.11;2013 年 3 月 27 日在线提前发布。