Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling

Steven M. Hill, Nicole K. Nesser, Katie Johnson-Camacho, Mara Jeffress, Aimee Johnson, Chris Boniface, Simon E F Spencer, Yiling Lu, Laura Heiser, Yancey Lawrence, Nupur T. Pande, James Korkola, Joe Gray, Gordon Mills, Sach Mukherjee, Paul Spellman

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)73-83.e10
JournalCell Systems
Volume4
Issue number1
DOIs
StatePublished - Jan 25 2017

Fingerprint

Phosphoproteins
Protein Array Analysis
Receptor Protein-Tyrosine Kinases
Proteins
Phosphotransferases
Learning
Breast Neoplasms
Cell Line
Inhibition (Psychology)

Keywords

  • breast cancer cell lines
  • casual networks
  • computational systems biology
  • context-specific networks
  • data resource
  • empirical assessment
  • network inference
  • protein signaling networks
  • reverse-phase protein array data

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Histology
  • Cell Biology

Cite this

Hill, S. M., Nesser, N. K., Johnson-Camacho, K., Jeffress, M., Johnson, A., Boniface, C., ... Spellman, P. (2017). Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. Cell Systems, 4(1), 73-83.e10. https://doi.org/10.1016/j.cels.2016.11.013

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. / Hill, Steven M.; Nesser, Nicole K.; Johnson-Camacho, Katie; Jeffress, Mara; Johnson, Aimee; Boniface, Chris; Spencer, Simon E F; Lu, Yiling; Heiser, Laura; Lawrence, Yancey; Pande, Nupur T.; Korkola, James; Gray, Joe; Mills, Gordon; Mukherjee, Sach; Spellman, Paul.

In: Cell Systems, Vol. 4, No. 1, 25.01.2017, p. 73-83.e10.

Research output: Contribution to journalArticle

Hill, SM, Nesser, NK, Johnson-Camacho, K, Jeffress, M, Johnson, A, Boniface, C, Spencer, SEF, Lu, Y, Heiser, L, Lawrence, Y, Pande, NT, Korkola, J, Gray, J, Mills, G, Mukherjee, S & Spellman, P 2017, 'Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling', Cell Systems, vol. 4, no. 1, pp. 73-83.e10. https://doi.org/10.1016/j.cels.2016.11.013
Hill SM, Nesser NK, Johnson-Camacho K, Jeffress M, Johnson A, Boniface C et al. Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. Cell Systems. 2017 Jan 25;4(1):73-83.e10. https://doi.org/10.1016/j.cels.2016.11.013
Hill, Steven M. ; Nesser, Nicole K. ; Johnson-Camacho, Katie ; Jeffress, Mara ; Johnson, Aimee ; Boniface, Chris ; Spencer, Simon E F ; Lu, Yiling ; Heiser, Laura ; Lawrence, Yancey ; Pande, Nupur T. ; Korkola, James ; Gray, Joe ; Mills, Gordon ; Mukherjee, Sach ; Spellman, Paul. / Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling. In: Cell Systems. 2017 ; Vol. 4, No. 1. pp. 73-83.e10.
@article{8e3b174db43b4be7b715766f568eec88,
title = "Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling",
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.",
keywords = "breast cancer cell lines, casual networks, computational systems biology, context-specific networks, data resource, empirical assessment, network inference, protein signaling networks, reverse-phase protein array data",
author = "Hill, {Steven M.} and Nesser, {Nicole K.} and Katie Johnson-Camacho and Mara Jeffress and Aimee Johnson and Chris Boniface and Spencer, {Simon E F} and Yiling Lu and Laura Heiser and Yancey Lawrence and Pande, {Nupur T.} and James Korkola and Joe Gray and Gordon Mills and Sach Mukherjee and Paul Spellman",
year = "2017",
month = "1",
day = "25",
doi = "10.1016/j.cels.2016.11.013",
language = "English (US)",
volume = "4",
pages = "73--83.e10",
journal = "Cell Systems",
issn = "2405-4712",
publisher = "Cell Press",
number = "1",

}

TY - JOUR

T1 - Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling

AU - Hill, Steven M.

AU - Nesser, Nicole K.

AU - Johnson-Camacho, Katie

AU - Jeffress, Mara

AU - Johnson, Aimee

AU - Boniface, Chris

AU - Spencer, Simon E F

AU - Lu, Yiling

AU - Heiser, Laura

AU - Lawrence, Yancey

AU - Pande, Nupur T.

AU - Korkola, James

AU - Gray, Joe

AU - Mills, Gordon

AU - Mukherjee, Sach

AU - Spellman, Paul

PY - 2017/1/25

Y1 - 2017/1/25

N2 - 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.

AB - 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.

KW - breast cancer cell lines

KW - casual networks

KW - computational systems biology

KW - context-specific networks

KW - data resource

KW - empirical assessment

KW - network inference

KW - protein signaling networks

KW - reverse-phase protein array data

UR - http://www.scopus.com/inward/record.url?scp=85010685970&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85010685970&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2016.11.013

DO - 10.1016/j.cels.2016.11.013

M3 - Article

VL - 4

SP - 73-83.e10

JO - Cell Systems

JF - Cell Systems

SN - 2405-4712

IS - 1

ER -