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Name: Kuster Lab

Type: Organization

Bio: The Kuster Lab comprises an international research team with a focus on proteomics, chemical biology and biomarker discovery

Location: Technical University of Munich

Blog: proteomics.wzw.tum.de

Kuster Lab's Projects

atlantic icon atlantic

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.

gem_synergy icon gem_synergy

Code to analyze and plot data from S. Hoefer et al. 2024.

iapi icon iapi

Instrument Application Programming Interface

ipsa icon ipsa

The Interactive Peptide Spectral Annotator

picked_group_fdr icon picked_group_fdr

Scalable, accurate and sensitive protein group FDRs for large-scale mass spectrometry experiments

prosit icon prosit

Prosit offers high quality MS2 predicted spectra for any organism and protease as well as iRT prediction. When using Prosit is helpful for your research, please cite "Gessulat, Schmidt et al. 2019" DOI 10.1038/s41592-019-0426-7

psite_annotation icon psite_annotation

Python module for annotating a pandas dataframe with phosphosites, e.g. PhosphoSitePlus annotations, kinase-substrate relations, domain information, etc.

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