IAPR International Conference on Pattern Recognition in Bioinformatics

PRIB 2013: Pattern Recognition in Bioinformatics pp 35-46

Mutational Genomics for Cancer Pathway Discovery

  • Jeroen de Ridder
  • Jaap Kool
  • Anthony G. Uren
  • Jan Bot
  • Johann de Jong
  • Alistair G. Rust
  • Anton Berns
  • Maarten van Lohuizen
  • David J. Adams
  • Lodewyk Wessels
  • Marcel Reinders
Conference paper

DOI: 10.1007/978-3-642-39159-0_4

Volume 7986 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
de Ridder J. et al. (2013) Mutational Genomics for Cancer Pathway Discovery. In: Ngom A., Formenti E., Hao JK., Zhao XM., van Laarhoven T. (eds) Pattern Recognition in Bioinformatics. PRIB 2013. Lecture Notes in Computer Science, vol 7986. Springer, Berlin, Heidelberg

Abstract

We propose mutational genomics as an approach for identifying putative cancer pathways. This approach relies on expression profiling tumors that are induced by retroviral insertional mutagenesis. Akin to genetical genomics, this provides the opportunity to search for associations between tumor-initiating events (the viral insertion sites) and the consequent transcription changes, thus revealing putative regulatory interactions. An important advantage is that in mutational genomics the selective pressure exerted by the tumor growth is exploited to yield a relatively small number of loci that are likely to be causal for tumor formation. This is unlike genetical genomics which relies on the natural occurring genetic variation between samples to reveal the effects of a locus on gene expression.

We performed mutational genomics using a set of 97 lymphoma from mice presenting with splenomegaly. This identified several known as well as novel interactions, including many known targets of Notch1 and Gfi1. In addition to direct one-to-one associations, many multilocus networks of association were found. This is indicative of the fact that a cell has many parallel possibilities in which it can reach a state of uncontrolled proliferation. One of the identified networks suggests that Zmiz1 functions upstream of Notch1. Taken together, our results illustrate the potential of mutational genomics as a powerful approach to dissect the regulatory pathways of cancer.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jeroen de Ridder
    • 1
    • 2
    • 3
  • Jaap Kool
    • 4
    • 6
  • Anthony G. Uren
    • 5
    • 6
  • Jan Bot
    • 1
    • 3
  • Johann de Jong
    • 2
  • Alistair G. Rust
    • 7
  • Anton Berns
    • 6
  • Maarten van Lohuizen
    • 6
  • David J. Adams
    • 7
  • Lodewyk Wessels
    • 1
    • 2
    • 3
  • Marcel Reinders
    • 1
    • 3
  1. 1.Delft Bioinformatics LabDelft University of TechnologyThe Netherlands
  2. 2.Bioinformatics and Statistics, Dept. Molecular Biology, Netherlands Cancer InstituteThe Netherlands
  3. 3.Netherlands Bioinformatics CentreThe Netherlands
  4. 4.MSD Animal Health, Merck/Intervet B.V.The Netherlands
  5. 5.MRC Clinical Sciences CentreImperial College Faculty of MedicineUK
  6. 6.Dept. Molecular GeneticsNetherlands Cancer InstituteThe Netherlands
  7. 7.Experimental Cancer GeneticsWellcome Trust Sanger InstituteUK