Clinical proteomics

The Clinical Proteomics team together with the team at NNF-CPR (Centre for Proteomics Research in Copenhagen) develops and applies proteomic methods for the unbiased and system-wide analysis of blood and tissues. We aim to systematically profile health and disease states at the protein level to uncover novel protein biomarkers for prognostic and predictive purposes. To address clinical needs and translate state-of-the-art MS methods into biomedical research, we have established a network of collaborations with multiple clinics and clinical research groups around the world, including the medical laboratory of the (Klinikum Grosshadern in Munich), the University of Chicago, Steno Diabetes Center, Rigshospitalet Copenhagen and many more.

Recently, we have developed an automated, robust and highly reproducible blood plasma proteomics pipeline – called ‘Plasma Proteome Profiling’ – to yield a proteomic reflection of an individual’s phenotype from only 1 µl of plasma (Geyer et al., Cell Syst., 2016). Using robotic assistance, hundreds of samples can now be prepared in 3 hours. We routinely quantify more than 100 FDA-approved biomarkers and many proteins involved in important biological processes, such as proteins of the inflammation or the lipid homeostasis system. Due to its high throughput and unbiased nature, Plasma Proteome Profiling allows a paradigm shift towards a ‘rectangular’ strategy of biomarker research, in which the proteome patterns of large cohorts are correlated with their phenotypes in physiological states ( Geyer et al., MSB, 2017 ).

We have already measured thousands of plasma proteomes and aim to establish a large knowledge base containing global correlation profiles for a deeper understanding of human health and disease states.

The Clinical Proteomics Team has also pioneered the proteomic analysis of archived biobank specimens including formalin-fixed and paraffin-embedded (FFPE) tissues (Ostasiewicz et al., J Proteome Res., 2010, Wiśniewski et al., J Proteome Res., 2011). This has recently led to the discovery of a novel prognostic biomarker in metastatic ovarian cancer linked to increased chemosensitivity and long-term patient survival (Coscia et al., Cell, 2018). Furthermore, we have provided proof-of-concept on how a rapid and reproducible proteomic workflow can assist clinical decision-making in end-stage cancer patient (Doll et al., Mol. Oncol., 2018). We are currently developing novel concepts for high-throughput and in-depth analysis of biobank tissues with the goal to process hundreds of tissue specimens simultaneously. This also includes advanced laser-capture microdissection workflows for automated and single-cell based sample collection. Ultimately, our vision is to bring proteomics into the clinic to improve individual health by monitoring, diagnosis and treatment and – even more importantly – into daily life so that individuals stay healthy in the first place.

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