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Title:

Proteome activity landscapes of tumor cell lines determine drug responses

Document type:
Zeitschriftenaufsatz
Author(s):
Frejno, Martin; Meng, Chen; Ruprecht, Benjamin; Oellerich, Thomas; Scheich, Sebastian; Kleigrewe, Karin; Drecoll, Enken; Samaras, Patroklos; Hogrebe, Alexander; Helm, Dominic; Mergner, Julia; Zecha, Jana; Heinzlmeir, Stephanie; Wilhelm, Mathias; Dorn, Julia; Kvasnicka, Hans-Michael; Serve, Hubert; Weichert, Wilko; Kuster, Bernhard
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 Recep...     »
Keywords:
BayBioMS; Cancer models; Cellular signalling networks; Predictive medicine; Proteome informatics; Proteomics
Journal title:
Nature Communications
Year:
2020
Journal volume:
11
Journal issue:
1
Fulltext / DOI:
doi:10.1038/s41467-020-17336-9
Publisher:
Springer Science and Business Media LLC
E-ISSN:
2041-1723
Date of publication:
20.07.2020
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