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Hill SM, Nesser NK, Johnson-Camacho K, Jeffress M, Johnson A, Boniface C, Spencer SEF, Lu Y, Heiser LM, Lawrence Y, Pande NT, Korkola JE, Gray JW, Mills GB, Mukherjee S, Spellman PT. Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. Cell Syst 2016; 4:73-83.e10. [PMID: 28017544 PMCID: PMC5279869 DOI: 10.1016/j.cels.2016.11.013] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 08/06/2016] [Accepted: 11/23/2016] [Indexed: 01/08/2023]
Abstract
Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting. Time-course assays of signaling proteins in cancer cell lines under kinase inhibition Causal conceptual framework for network analysis Data shed light on causal protein networks that are specific to biological context Resource for signaling biology and for benchmarking computational methods
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Affiliation(s)
- Steven M Hill
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
| | - Nicole K Nesser
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA
| | - Katie Johnson-Camacho
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA
| | | | - Aimee Johnson
- Bayer Healthcare North America, Berkeley, CA 94710, USA
| | - Chris Boniface
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA
| | - Simon E F Spencer
- Department of Statistics, University of Warwick, Coventry CV4 7AL, UK
| | - Yiling Lu
- Department of Systems Biology, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Laura M Heiser
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR 97201, USA
| | - Yancey Lawrence
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA
| | - Nupur T Pande
- Department of Obstetrics and Gynecology, Women's Health Research Unit, Oregon Health and Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - James E Korkola
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR 97201, USA
| | - Joe W Gray
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR 97201, USA; Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA; Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, OR 97239, USA
| | - Gordon B Mills
- Department of Systems Biology, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sach Mukherjee
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK; German Center for Neurodegenerative Diseases (DZNE), Bonn 53127, Germany.
| | - Paul T Spellman
- Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA.
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