hupo2017@conferencepartners.ie

Simone Lemmer

Simone Lemmer

Title: Drug resistance assessed by mass spectrometry based omics technologies.

Bio:

Simone Lemeer studied Chemistry at Utrecht University. After graduating she started a PhD in the Biomolecular Mass Spectrometry and Proteomics group of Albert Heck. During her PhD project, a collaboration between Utrecht University and the Hubrecht Institute, she used mass spectrometry to study phosphorylation and signalling during embryonic development in the zebrafish. In 2009 she moved to the Proteomics and Bioanalytics group of Bernhard Kuster at the Technical University Munich, Germany where she became group leader proteomics in 2011. Her work in Munich focused on the development of chemical proteomics and phosphoproteomics methods and their application in cancer research. In January 2014 she returned to Utrecht, where she became assistant professor. In the same year she received a NWO VIDI grant. Her work focusses on resistance mechanisms in cancer cells studied by chemical and phosphoproteomics. In 2017 she became associate professor at Utrecht University.

Abstract:

Targeted therapies against oncogenic receptor tyrosine kinases are showing promising results in the clinic. However, despite the initial response, most patients become resistant. How are cells able to survive initial treatment? A multi-omics approach was used, including mass spectrometry based proteomics, phospho-proteomics, kinomics and metabolomics, to gain more insight in regulated processes during early TKI treatment. Our findings demonstrate how this multi-omics approach contributes to a better understanding of the molecular pathways underlying immediate drug tolerance and elucidates new potential targets that can be co-inhibited to prevent resistance development. In addition to this, I will present a universal and optimized phosphoproteomic workflow that enables comprehensive analysis of signaling pathways, yielding 60% gain in identifications without additional analysis time compared to previous workflows.

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