A systems biology approach to discovering pathway signaling dysregulation in metastasis
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A systems biology approach to discovering pathway signaling dysregulation in metastasis Robert Clarke 1,2 & Pavel Kraikivski 3 & Brandon C. Jones 1 & Catherine M. Sevigny 1 & Surojeet Sengupta 1 & Yue Wang 4 Received: 11 July 2020 / Accepted: 13 July 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Total metastatic burden is the primary cause of death for many cancer patients. While the process of metastasis has been studied widely, much remains to be understood. Moreover, few agents have been developed that specifically target the major steps of the metastatic cascade. Many individual genes and pathways have been implicated in metastasis but a holistic view of how these interact and cooperate to regulate and execute the process remains somewhat rudimentary. It is unclear whether all of the signaling features that regulate and execute metastasis are yet fully understood. Novel features of a complex system such as metastasis can often be discovered by taking a systems-based approach. We introduce the concepts of systems modeling and define some of the central challenges facing the application of a multidisciplinary systems-based approach to understanding metastasis and finding actionable targets therein. These challenges include appreciating the unique properties of the highdimensional omics data often used for modeling, limitations in knowledge of the system (metastasis), tumor heterogeneity and sampling bias, and some of the issues key to understanding critical features of molecular signaling in the context of metastasis. We also provide a brief introduction to integrative modeling that focuses on both the nodes and edges of molecular signaling networks. Finally, we offer some observations on future directions as they relate to developing a systems-based model of the metastatic cascade. Keywords Systems biology . Multiscale modeling . Metastasis . Signaling . Pathway analysis . Breast cancer . Bioinformatics . Mathematical modeling . Computational modeling
1 Introduction A key goal for many research programs is to identify a gene, pathway, or signaling feature that regulates a critical biological function in a manner that is actionable either as a predictive and/or prognostic biomarker, and/or as a therapeutic target. * Robert Clarke [email protected] 1
Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC 20057, USA
2
Present address: Hormel Institute and Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Austin, MN 55912, USA
3
Academy of Integrated Science, Division of Systems Biology, Virginia Polytechnic and State University, Blacksburg, VA 24061, USA
4
Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA
Increasingly, these signaling features are extracted from high-dimensional omics datasets (genome, transcriptome, proteome, metabolome, and their respective subomes including the epigenome and kinome). Th
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