Local genomic features predict the distinct and overlapping binding patterns of the bHLH-Zip family oncoproteins MITF and MYC-MAX

Miroslav Hejna, Wooyoung M. Moon, Jeffrey Cheng, Akinori Kawakami, David E. Fisher, Jun S. Song

Research output: Contribution to journalArticle

Abstract

MITF and MYC are well-known oncoproteins and members of the basic helix–loop–helix leucine zipper (bHLH-Zip) family of transcription factors (TFs) recognizing hexamer E-box motifs. MITF and MYC not only share the core binding motif, but are also the two most highly expressed bHLH-Zip transcription factors in melanocytes, raising the possibility that they may compete for the same binding sites in select oncogenic targets. Mechanisms determining the distinct and potentially overlapping binding modes of these critical oncoproteins remain uncharacterized. We introduce computational predictive models using local sequence features, including a boosted convolutional decision tree framework, to distinguish MITF versus MYC-MAX binding sites with up to 80% accuracy genomewide. Select E-box locations that can be bound by both MITF and MYC-MAX form a separate class of MITF binding sites characterized by differential sequence content in the flanking region, diminished interaction with SOX10, higher evolutionary conservation, and less tissue-specific chromatin organization.

Original languageEnglish (US)
Pages (from-to)500-509
Number of pages10
JournalPigment Cell and Melanoma Research
Volume32
Issue number4
DOIs
StatePublished - Jul 2019

Keywords

  • MITF
  • MYC-MAX
  • boosted convolutional decision tree
  • cobinding factors
  • machine learning

ASJC Scopus subject areas

  • Oncology
  • Biochemistry, Genetics and Molecular Biology(all)
  • Dermatology

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