Decoding transcriptional states in cancer. (April 2017)

• Record Type: Journal Article
• Authors: Wouters, Jasper; Kalender Atak, Zeynep; Aerts, Stein
• Is Part Of: Current opinion in genetics & development. Volume 43(2017)
• Page Start: 82
• Page End: 92
• Publication Date: 2017-04
• Subjects: Genetics -- Periodicals; Developmental biology -- Periodicals; Developmental genetics -- Periodicals; 576.5
• DOI: 10.1016/j.gde.2017.01.003
• Languages: English
• ISSNs: 0959-437X

Abstract

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.