Abstract
Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action. We extend this paradigm to measuring proteome activity landscapes by acquiring and integrating quantitative data for 10,000 proteins and 55,000 phosphorylation sites (p-sites) from 125 CCLs. These data are used to contextualize proteins and p-sites and predict drug sensitivity. For example, we find that Progesterone Receptor (PGR) phosphorylation is associated with sensitivity to drugs modulating estrogen signaling such as Raloxifene. We also demonstrate that Adenylate kinase isoenzyme 1 (AK1) inactivates antimetabolites like Cytarabine. Consequently, high AK1 levels correlate with poor survival of Cytarabine-treated acute myeloid leukemia patients, qualifying AK1 as a patient stratification marker and possibly as a drug target. We provide an interactive web application termed ATLANTiC (http://atlantic.proteomics.wzw.tum.de), which enables the community to explore the thousands of novel functional associations generated by this work.
Highlights
Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action
We profile the baseline phosphoproteomes of the NCI60 and CRC65 cell line panels (Fig. 1a) to an overall depth of >55,000 p-sites using a consistent and reproducible mass spectrometry workflow (Fig. 1b), in order to further improve our understanding of the molecular mechanisms of action (MoA) of cancer drugs and how the signaling repertoire of cancer cells affects drug response
We show that Adenylate kinase isoenzyme 1 (AK1) is capable of inactivating antimetabolites like Cytarabine and that AK1 protein levels correlate with poor survival of Cytarabine-treated acute myeloid leukemia patients
Summary
Integrated analysis of genomes, transcriptomes, proteomes and drug responses of cancer cell lines (CCLs) is an emerging approach to uncover molecular mechanisms of drug action. Proteomics.wzw.tum.de), which allows users to visualize activity landscapes and protein/p-site abundance information across the entire dataset, to query the results of all drug response modeling analyses and to deconvolute the target space of kinase inhibitors in specific cell lines.
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