TY - GEN
T1 - Mutational genomics for cancer pathway discovery
AU - De Ridder, Jeroen
AU - Kool, Jaap
AU - Uren, Anthony G.
AU - Bot, Jan
AU - De Jong, Johann
AU - Rust, Alistair G.
AU - Berns, Anton
AU - van Lohuizen, Maarten
AU - Adams, David J.
AU - Wessels, Lodewyk F A
AU - Reinders, Marcel J T
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84880704660&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39159-0-4
DO - 10.1007/978-3-642-39159-0-4
M3 - Conference contribution
AN - SCOPUS:84880704660
SN - 9783642391583
VL - 7986 LNBI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 35
EP - 46
BT - Pattern Recognition in Bioinformatics - 8th IAPR International Conference, PRIB 2013, Proceedings
T2 - 8th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2013
Y2 - 17 June 2013 through 20 June 2013
ER -