Review A systems biology view of cancer Reinhard Laubenbacher a,f, ⁎, Valerie Hower b , Abdul Jarrah a , Suzy V.Torti c,d , Vladimir Shulaev a,f , Pedro Mendes a,e,f , Frank M.Torti d,f , Steven Akman d,f a Virginia Bioinformatics Institute, Washington St. (0477),Blacksburg, VA 24061, USA b School of Mathematics, Georgia Institute of Technology, Atlanta,GA 30332-0160, USA c Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA d Comprehensive Cancer Center, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA e School of Computer Science, University of Manchester, Manchester, England f Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA a b s t r a c t a r t i c l e i n f o Article history: Received 20 December 2008 Received in revised form 20 May 2009 Accepted 1 June 2009 Available online 6 June 2009 Keywords: Systems biology Cancer Mathematical modeling In order to understand how a cancer cell is functionally different from a normal cell it is necessary to assess the complex network of pathways involving gene regulation, signaling,and cell metabolism,and the alterations in its dynamics caused by the several different types of mutations leading to malignancy. Since the network is typically complex, with multiple connections between pathways and important feedback loops, it is crucial to represent it in the form of a computational model that can be used for a rigorous analysis. This is the approach of systems biology, made possible by new -omics data generation technologies. The goal of this review is to illustrate this approach and its utility for our understanding of cancer. After a discussion of recent progress using a network-centric approach, three case studies related to diagnostics, therapy,and drug development are presented in detail. They focus on breast cancer, B-cell lymphomas, and colorectal cancer. The discussion is centered on key mathematical and computationaltools common to a systems biology approach. © 2009 Elsevier B.V. All rights reserved. Contents 1. Introduction .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 2. Cancer is a systems biology disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 3. The systems biology approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 4. A systems biology view of the hallmarks of cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 4.1. Independence from external growth signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 4.2. Insensitivity to antigrowth signaling and evasion of apoptosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 4.3. Limitless replicative potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 4.4. Sustained angiogenesis and metastasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 5. Case studies .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 5.1. Network-based classification of breast cancer metastasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 5.2. Prediction of oncogenes and molecular perturbation targets in B-cell lymphomas . . . . . . . . . . . . . . . . . . . . . . . . . . 136 5.2.1. The BCI interactome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 5.3. A multi-scale mathematical model of cancer, and its use in designing radiation therapies . . . . . . . . . . . . . . . . . . . . . . 137 Biochimica et Biophysica Acta 1796 (2009) 129–139 Contents lists available at ScienceDirect Biochimica et Biophysica Acta j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / b b a c a n