Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Shao-Shan Huang, David C. Clarke, Sara J.C. Gosline, Adam Labadorf, Candace R. Chouinard, William Gordon, Douglas A. Lauffenburger, Ernest Fraenkel

Research output: Contribution to journalArticle

Abstract

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118-310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.

Original languageEnglish (US)
Article numbere1002887
JournalPLoS Computational Biology
Volume9
Issue number2
DOIs
StatePublished - Feb 1 2013

Fingerprint

proteomics
oncogenes
Proteomics
Glioblastoma
Oncogenes
Transcriptome
transcriptome
Linking
chromatin
Genes
Chromatin
Cells
Throughput
CREB-Binding Protein
Proteins
Protein
Catenins
Signal transduction
High Throughput
Target

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

Huang, S-S., Clarke, D. C., Gosline, S. J. C., Labadorf, A., Chouinard, C. R., Gordon, W., ... Fraenkel, E. (2013). Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling. PLoS Computational Biology, 9(2), [e1002887]. https://doi.org/10.1371/journal.pcbi.1002887

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling. / Huang, Shao-Shan; Clarke, David C.; Gosline, Sara J.C.; Labadorf, Adam; Chouinard, Candace R.; Gordon, William; Lauffenburger, Douglas A.; Fraenkel, Ernest.

In: PLoS Computational Biology, Vol. 9, No. 2, e1002887, 01.02.2013.

Research output: Contribution to journalArticle

Huang, S-S, Clarke, DC, Gosline, SJC, Labadorf, A, Chouinard, CR, Gordon, W, Lauffenburger, DA & Fraenkel, E 2013, 'Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling', PLoS Computational Biology, vol. 9, no. 2, e1002887. https://doi.org/10.1371/journal.pcbi.1002887
Huang, Shao-Shan ; Clarke, David C. ; Gosline, Sara J.C. ; Labadorf, Adam ; Chouinard, Candace R. ; Gordon, William ; Lauffenburger, Douglas A. ; Fraenkel, Ernest. / Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling. In: PLoS Computational Biology. 2013 ; Vol. 9, No. 2.
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