Poster Presentation 35th Lorne Cancer Conference 2023

A Semi-Automated Workflow for High-Throughput Phosphoproteomics Analysis of Clinical Samples (#228)

Terry Lim Kam Sian 1 2 , Stoyan Stoychev 3 , Justin Jordaan 3 , Ralf B Schittenhelm 2 , Pouya Faridi 1 2
  1. School of Clinical Sciences, Department of Medicine, Monash University, Clayton, VIC, Australia
  2. Monash Proteomics and Metabolomics Facility, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
  3. ReSyn Biosciences (Pty) Ltd, Edenvale, Gauteng, South Africa

In an era of precision medicine guided by multi-omics approaches, mass spectrometry based (phospho)proteomics profiling has become an important tool for the discovery of proteins and pathways that are involved in diseases. This is particularly true for the field of oncology, where a variety of cancers are strongly associated with dysregulation of protein kinases, the enzymes responsible for the phosphorylation reaction. The compounding effect of the heterogeneity of many cancers, plus our lack of our understanding of a large proportion of kinases, make it impossible to design a “one size fit all” therapy and harder to predict therapeutic targets. Therefore, for personalised medicine approaches it remains critical to profile the phosphoproteome to grant a better understanding of the function of kinases as well as to help in predicting better targets for immunotherapies and precision therapies. 

A major bottleneck with current phospho-enrichment methods remain the high amount of starting material required to achieve reasonable coverage of phosphorylated peptides. Moreover, most workflows are not adapted to cover the large number clinical samples required to give proper statistical power for targeted therapy approaches. Therefore, we sought to develop a workflow that would allow for high-throughput as well as deeper coverage of the phosphoproteome on small clinical samples. 

To achieve this goal, we used the Thermo Kingfisher platform coupled with a Zr-IMAC patented highly porous magnetic microparticles (MagReSyn®). The new workflow has resulted in a ~50% increase in phosphosite identification whilst simultaneously halving the starting material. Moreover, detection of > 1000 phosphosites could be achieved with down to 10 ug of protein lysate, which is equivalent to small cancer biopsies, a level of sensitivity never reported previously. 

In summary, our pioneering approach will facilitate more accurate clinical phosphoproteomics profiling in small sample types, which will aid to monitor the activities of therapeutic kinases and, ultimately, can be a useful tool for the development of precision medicine approaches.