PT - JOURNAL ARTICLE AU - Theodoros I. Roumeliotis AU - Steven Paul Williams AU - Emanuel Gonçalves AU - Fatemeh Zamanzad Ghavidel AU - Nanne Aben AU - Magali Michaut AU - Michael Schubert AU - James C. Wright AU - Mi Yang AU - Clara Alsinet AU - Rodrigo Dienstmann AU - Justin Guinney AU - Pedro Beltrao AU - Alvis Brazma AU - Oliver Stegle AU - David J. Adams AU - Lodewyk Wessels AU - Julio Saez-Rodriguez AU - Ultan McDermott AU - Jyoti S. Choudhary TI - Genomic determinants of protein abundance variation in colorectal cancer cells AID - 10.1101/092767 DP - 2016 Jan 01 TA - bioRxiv PG - 092767 4099 - http://biorxiv.org/content/early/2016/12/09/092767.short 4100 - http://biorxiv.org/content/early/2016/12/09/092767.full AB - Assessing the extent to which genomic alterations compromise the integrity of the proteome is fundamental in identifying the mechanisms that shape cancer heterogeneity. We have used isobaric labelling and tribrid mass spectrometry to characterize the proteomic landscapes of 50 colorectal cancer cell lines and to decipher the relationships between genomic and proteomic variation. The robust quantification of 12,000 proteins and 27,000 phosphopeptides revealed how protein symbiosis translates to a co-variome which is subjected to a hierarchical order and exposes the collateral effects of somatic mutations on protein complexes. Targeted depletion of key chromatin modifiers confirmed the transmission of variation and the directionality as characteristics of protein interactions. Protein level variation was leveraged to build drug response predictive models towards a better understanding of pharmacoproteomic interactions in colorectal cancer. Overall, we provide a deep integrative view of the molecular structure underlying the variation of colorectal cancer cells.HighlightsThe cancer cell functional “co-variome” is a strong attribute of the proteome.Mutations can have a direct impact on protein levels of chromatin modifiers.Transmission of genomic variation is a characteristic of protein interactions.Pharmacoproteomic models are strong predictors of response to DNA damaging agents.COREADColorectal AdenocarcinomaIMACImmobilized Metal ion Affinity ChromatographyROCReceiver Operating CharacteristicAUCArea Under the CurveWGCNAWeighted Correlation Network AnalysisCNACopy Number AlterationSOMSelf-Organizing MapQTLQuantitative Trait LociMSIMicrosatellite InstabilityCPSColorectal Proteomic Subtypes