Proteome activity landscapes of tumor cell lines determine drug responses

Martin Frejno, Chen Meng, Benjamin Ruprecht, Thomas Oellerich, Sebastian Scheich, Karin Kleigrewe, Enken Drecoll, Patroklos Samaras, Alexander Hogrebe, Dominic Helm, Julia Mergner, Jana Zecha, Stephanie Heinzlmeir, Mathias Wilhelm, Julia Dorn, Hans-Michael Kvasnicka, Hubert Serve, Wilko Weichert and Bernhard Kuster ()
Additional contact information
Martin Frejno: Technical University of Munich
Chen Meng: Technical University of Munich
Benjamin Ruprecht: Technical University of Munich
Thomas Oellerich: Hematology/Oncology, Goethe-University
Sebastian Scheich: Hematology/Oncology, Goethe-University
Karin Kleigrewe: Technical University of Munich
Enken Drecoll: Technical University of Munich
Patroklos Samaras: Technical University of Munich
Alexander Hogrebe: Technical University of Munich
Dominic Helm: Technical University of Munich
Julia Mergner: Technical University of Munich
Jana Zecha: Technical University of Munich
Stephanie Heinzlmeir: Technical University of Munich
Mathias Wilhelm: Technical University of Munich
Julia Dorn: Technical University of Munich
Hans-Michael Kvasnicka: Goethe University
Hubert Serve: Hematology/Oncology, Goethe-University
Wilko Weichert: German Cancer Consortium (DKTK)
Bernhard Kuster: Technical University of Munich

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: 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.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.nature.com/articles/s41467-020-17336-9 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17336-9

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-17336-9

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().