A systems biology approach to prediction of oncogenes and molecular perturbation targets in B‐cell lymphomas

• DOI: 10.1038/msb.2008.2
• Publication Date: 2008-02-14T13:12:34Z
• Authors: Kartik M Mani; Celine Lefebvre; Kai Wang; Wei Keat Lim; Katia Basso; Riccardo Dalla‐Fa...; Andrea Califano
• Keywords: 0301 basic medicine; Medicine (General); Lymphoma, B-Cell; QH301-705.5; interactome; drug mechanism‐of‐action (MOA); 03 medical and health sciences; R5-920; oncogene; Report; B‐cell lymphoma; Humans; Gene Regulatory Networks; Biology (General); Oligonucleotide Array Sequence Analysis; Models, Genetic; Genome, Human; Gene Expression Profiling; Systems Biology; Computational Biology; Reproducibility of Results; Oncogenes; 3. Good health; Benchmarking; gene network; Algorithms; Metabolic Networks and Pathways

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.