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      Decoding transcriptional states in cancer.

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          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.

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          Author and article information

          Journal
          Curr. Opin. Genet. Dev.
          Current opinion in genetics & development
          Elsevier BV
          1879-0380
          0959-437X
          Apr 2017
          : 43
          Affiliations
          [1 ] Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium; Department of Human Genetics, KU Leuven (University of Leuven), Leuven, Belgium.
          [2 ] Laboratory of Computational Biology, VIB Center for Brain & Disease Research, Leuven, Belgium; Department of Human Genetics, KU Leuven (University of Leuven), Leuven, Belgium. Electronic address: stein.aerts@kuleuven.vib.be.
          Article
          S0959-437X(17)30009-6
          10.1016/j.gde.2017.01.003
          28129557
          e2f170c1-081e-4ac2-ad6e-87dc8938f5fc
          History

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