Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells

Journal Article (2017)
Authors

Theodoros I. Roumeliotis (Wellcome Trust Sanger Institute)

Steven P. Williams (Wellcome Trust Sanger Institute)

Emanuel Gonçalves (European Molecular Biology Laboratory)

Clara Alsinet (Wellcome Trust Sanger Institute)

Martin Del Castillo Velasco-Herrera (Wellcome Trust Sanger Institute)

N.N. Aben (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)

Fatemeh Zamanzad Ghavidel (European Molecular Biology Laboratory)

Magali Michaut (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)

Michael Schubert (European Molecular Biology Laboratory)

Stacey Price (Wellcome Trust Sanger Institute)

L. F.A. Wessels (TU Delft - Pattern Recognition and Bioinformatics, Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)

G.B. More authors (External organisation)

Research Group
Pattern Recognition and Bioinformatics
Copyright
© 2017 Theodoros I. Roumeliotis, Steven P. Williams, Emanuel Gonçalves, Clara Alsinet, Martin Del Castillo Velasco-Herrera, N.N. Aben, Fatemeh Zamanzad Ghavidel, Magali Michaut, Michael Schubert, Stacey Price, L.F.A. Wessels, More Authors
To reference this document use:
https://doi.org/10.1016/j.celrep.2017.08.010
More Info
expand_more
Publication Year
2017
Language
English
Copyright
© 2017 Theodoros I. Roumeliotis, Steven P. Williams, Emanuel Gonçalves, Clara Alsinet, Martin Del Castillo Velasco-Herrera, N.N. Aben, Fatemeh Zamanzad Ghavidel, Magali Michaut, Michael Schubert, Stacey Price, L.F.A. Wessels, More Authors
Research Group
Pattern Recognition and Bioinformatics
Issue number
9
Volume number
20
Pages (from-to)
2201-2214
DOI:
https://doi.org/10.1016/j.celrep.2017.08.010
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Assessing the impact of genomic alterations on protein networks is fundamental in identifying the mechanisms that shape cancer heterogeneity. We have used isobaric labeling to characterize the proteomic landscapes of 50 colorectal cancer cell lines and to decipher the functional consequences of somatic genomic variants. The robust quantification of over 9,000 proteins and 11,000 phosphopeptides on average enabled the de novo construction of a functional protein correlation network, which ultimately exposed the collateral effects of mutations on protein complexes. CRISPR-cas9 deletion of key chromatin modifiers confirmed that the consequences of genomic alterations can propagate through protein interactions in a transcript-independent manner. Lastly, we leveraged the quantified proteome to perform unsupervised classification of the cell lines and to build predictive models of drug response in colorectal cancer. Overall, we provide a deep integrative view of the functional network and the molecular structure underlying the heterogeneity of colorectal cancer cells.