Wouters Jasper, Kalender Atak Zeynep, Aerts Stein
Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium; Department of Human Genetics, KU Leuven (University of Leuven), Leuven, Belgium.
Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium; Department of Human Genetics, KU Leuven (University of Leuven), Leuven, Belgium.
Curr Opin Genet Dev. 2017 Apr;43:82-92. doi: 10.1016/j.gde.2017.01.003. Epub 2017 Jan 24.
Gene regulatory networks determine cellular identity. In cancer, aberrations of gene networks are caused by driver mutations that often affect transcription factors and chromatin modifiers. Nevertheless, gene transcription in cancer follows the same cis-regulatory rules as normal cells, and cancer cells have served as convenient model systems to study transcriptional regulation. Tumours often show regulatory heterogeneity, with subpopulations of cells in different transcriptional states, which has important therapeutic implications. Here, we review recent experimental and computational techniques to reverse engineer cancer gene networks using transcriptome and epigenome data. New algorithms, data integration strategies, and increasing amounts of single cell genomics data provide exciting opportunities to model dynamic regulatory states at unprecedented resolution.
基因调控网络决定细胞身份。在癌症中，基因网络的畸变是由驱动突变引起的，这些突变通常会影响转录因子和染色质修饰因子。然而，癌症中的基因转录遵循与正常细胞相同的顺式调控规则，癌细胞已成为研究转录调控的便捷模型系统。肿瘤通常表现出调控异质性，存在处于不同转录状态的细胞亚群，这具有重要的治疗意义。在这里，我们综述了最近利用转录组和表观基因组数据对癌症基因网络进行反向工程的实验和计算技术。新的算法、数据整合策略以及越来越多的单细胞基因组学数据，为以前所未有的分辨率模拟动态调控状态提供了令人兴奋的机会。
