Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Cell Biology, Genetics & Heredity, CELL RNA-SEQ, GENE REGULATORY NETWORKS, ACUTE LYMPHOBLASTIC-LEUKEMIA, PARALLEL REPORTER ASSAYS, ENHANCER ACTIVITY MAPS, EMBRYONIC STEM-CELLS, CHROMATIN ACCESSIBILITY, SUPER-ENHANCER, SINGLE CELLS, HUMAN GENOME, REPORTER ASSAYS, STEM-CELLS, MEDIP-SEQ, CHIP-SEQ, GENOME, Binding Sites, Computational Biology, Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, Genomics, Humans, Neoplasms, Promoter Regions, Genetic, Transcription Factors, Transcription, Genetic, 0604 Genetics, Developmental Biology, 3101 Biochemistry and cell biology, 3105 Genetics

Abstract:

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.