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
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.
Interactive Visualization of Signaling Pathways
Analysis platform for large-scale dose-dependent data
Code to analyze and plot data from S. Hoefer et al. 2024.
Instrument Application Programming Interface
The Interactive Peptide Spectral Annotator
Download and Convert Pathways from KEGG and WikiPathways
Scalable, accurate and sensitive protein group FDRs for large-scale mass spectrometry experiments
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
The Proteomics Experimental Design file format: Standard for experimental design annotation
Python module for annotating a pandas dataframe with phosphosites, e.g. PhosphoSitePlus annotations, kinase-substrate relations, domain information, etc.
Similarity-based Isobaric MS2 Identification Transfer