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A systems biology approach to discovering pathway signaling dysregulation in metastasis.
Clarke, Robert; Kraikivski, Pavel; Jones, Brandon C; Sevigny, Catherine M; Sengupta, Surojeet; Wang, Yue.
Afiliación
  • Clarke R; Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC, 20057, USA. clarker@umn.edu.
  • Kraikivski P; Hormel Institute and Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Austin, MN, 55912, USA. clarker@umn.edu.
  • Jones BC; Academy of Integrated Science, Division of Systems Biology, Virginia Polytechnic and State University, Blacksburg, VA, 24061, USA.
  • Sevigny CM; Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC, 20057, USA.
  • Sengupta S; Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC, 20057, USA.
  • Wang Y; Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Rd NW, Washington, DC, 20057, USA.
Cancer Metastasis Rev ; 39(3): 903-918, 2020 09.
Article en En | MEDLINE | ID: mdl-32776157
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 high-dimensional 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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología de Sistemas / Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cancer Metastasis Rev Asunto de la revista: NEOPLASIAS Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología de Sistemas / Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cancer Metastasis Rev Asunto de la revista: NEOPLASIAS Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos