Caroli Jimmy, Dori Martina, Bicciato Silvio
Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Front Oncol. 2020 Feb 27;10:185. doi: 10.3389/fonc.2020.00185. eCollection 2020.
Since the pioneering NCI-60 panel of the late'80's, several major screenings of genetic profiling and drug testing in cancer cell lines have been conducted to investigate how genetic backgrounds and transcriptional patterns shape cancer's response to therapy and to identify disease-specific genes associated with drug response. Historically, pharmacogenomics screenings have been largely heterogeneous in terms of investigated cell lines, assay technologies, number of compounds, type and quality of genomic data, and methods for their computational analysis. The analysis of this enormous and heterogeneous amount of data required the development of computational methods for the integration of genomic profiles with drug responses across multiple screenings. Here, we will review the computational tools that have been developed to integrate cancer cell lines' genomic profiles and sensitivity to small molecule perturbations obtained from different screenings.
自20世纪80年代末开创性的NCI-60细胞系筛选以来，已经进行了几次癌细胞系基因谱分析和药物测试的大规模筛选，以研究基因背景和转录模式如何影响癌症对治疗的反应，并识别与药物反应相关的疾病特异性基因。从历史上看，药物基因组学筛选在研究的细胞系、检测技术、化合物数量、基因组数据的类型和质量以及计算分析方法等方面存在很大差异。对如此大量且异质的数据进行分析需要开发计算方法，以整合来自多个筛选的基因组谱与药物反应。在此，我们将回顾已开发的计算工具，这些工具用于整合癌细胞系的基因组谱以及对不同筛选中获得的小分子扰动的敏感性。
