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Cell Rep. 2017 Aug 29;20(9):2201-2214. doi: 10.1016/j.celrep.2017.08.010.

Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells.

Author information

1
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK. Electronic address: tr6@sanger.ac.uk.
2
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK.
3
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK.
4
Division of Molecular Carcinogenesis, Computational Cancer Biology, the Netherlands Cancer Institute, Amsterdam 1066, the Netherlands.
5
Faculty of Medicine, Joint Research Center for Computational Biomedicine, RWTH Aachen University, Aachen 52057, Germany.
6
Computational Oncology, Sage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA; Oncology Data Science Group, Vall d'Hebron Institute of Oncology, Barcelona 08035, Spain.
7
Computational Oncology, Sage Bionetworks, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA.
8
Division of Molecular Carcinogenesis, Computational Cancer Biology, the Netherlands Cancer Institute, Amsterdam 1066, the Netherlands; Faculty of EEMCS, Delft University of Technology, Delft 2628, the Netherlands.
9
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK; Faculty of Medicine, Joint Research Center for Computational Biomedicine, RWTH Aachen University, Aachen 52057, Germany.
10
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Functional Proteomics Group, Chester Beatty Laboratories, The Institute of Cancer Research, London SW3 6JB, UK. Electronic address: jc4@sanger.ac.uk.

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.

KEYWORDS:

CRISPR/cas9; TMT; cell lines; colorectal cancer; drug response; mutations; networks; phosphorylation; protein complexes; proteomics

PMID:
28854368
PMCID:
PMC5583477
DOI:
10.1016/j.celrep.2017.08.010
[Indexed for MEDLINE]
Free PMC Article

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