A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas.
The computational identification of oncogenic lesions is still a key open problem in cancer biology. Although several methods have been proposed, they fail to model how such events are mediated by the network of molecular interactions in the cell. In this paper, we introduce a systems biology approach, based on the analysis of molecular interactions that become dysregulated in specific tumor phenotypes. Such a strategy provides important insights into tumorigenesis, effectively extending and complementing existing methods. Furthermore, we show that the same approach is highly effective in identifying the targets of molecular perturbations in a human cellular context, a task virtually unaddressed by existing computational methods. To identify interactions that are dysregulated in three distinct non-Hodgkin's lymphomas and in samples perturbed with CD40 ligand, we use the B-cell interactome (BCI), a genome-wide compendium of human B-cell molecular interactions, in combination with a large set of microarray expression profiles. The method consistently ranked the known gene in the top 20 (0.3%), outperforming conventional approaches in 3 of 4 cases.
Mani
Kartik M
KM
Department of Biomedical Informatics (DBMI), Columbia University, New York, NY 10032, USA. kartik.mani@dbmi.columbia.edu
Lefebvre
Celine
C
Wang
Kai
K
Lim
Wei Keat
WK
Basso
Katia
K
Dalla-Favera
Riccardo
R
Califano
Andrea
A
D000465:Algorithms; D019985:Benchmarking; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks / Q000235:genetics*; D015894:Genome, Human; D006801:Humans; D016393:Lymphoma, B-Cell / Q000145:classification / Q000235:genetics*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D009857:Oncogenes; D015203:Reproducibility of Results; D049490:Systems Biology