Benchmarking sample preparation and data analysis for clinical proteomics of human biofluids

Liquid biopsies like plasma, cerebrospinal fluid (CSF), or urine are a less invasive and inexpensive alternative to tissue biopsies. Additionally, these body fluids are known to contain a multitude of known and yet to be revealed biomarkers that can be detected using mass spectrometry (MS) based proteomics. There are several distinct advantages of this technology: (I) it gives unbiased access to the biofluid proteome, (II) it is species independent, (III) it can reveal information about isoforms and post-translational modifications and (IV) it does not require availability of antibodies. Furthermore, MS based proteomics has been rapidly evolving over the last years due to the development of new generations of MS instruments such as timsTOF or Thermo Astral, advancements in sample preparation like nanoparticle-based protein enrichment, as well as novel AI based tools for data processing. The continuous progress results in increased depth and throughput of clinical proteomics.

However, this highly dynamic nature of the field can also be a drawback, as applications of mass spectrometry-based proteomics for larger clinical trials is often hindered by a lack of standardization across laboratories and studies. To address this problem and to enhance the integration of MS-based proteomics into medical research the CLINPSECT-M consortium and its MS laboratories conducted a round robin study on clinical specimens such as human plasma and CSF [1].

Here, the data from the round robin study is compared to internal benchmark studies on human biofluids that were performed at Evotec. In addition, while the focus of the round-robin study was to harmonize workflows for undepleted plasma and CSF and track interlaboratory reproducibility, the Evotec study also measured longitudinal platform stability and shows how nanoparticle-based proteomics using the ProteographTM can provide deeper coverage of the plasma proteome and at the same time overcome some of the challenges associated with undepleted workflows.

[1] Multicenter Collaborative Study to Optimize Mass Spectrometry Workflows of Clinical Specimens Oliver Kardell, Christine von Toerne, Juliane Merl-Pham, Ann-Christine König, Marcel Blindert, Teresa K. Barth, Julia Mergner, Christina Ludwig, Johanna Tüshaus, Stephan Eckert, Stephan A. Müller, Stephan Breimann, Pieter Giesbertz, Alexander M. Bernhardt, Lisa Schweizer, Vincent Albrecht, Daniel Teupser, Axel Imhof, Bernhard Kuster, Stefan F. Lichtenthaler, Matthias Mann, Jürgen Cox, and Stefanie M. Hauck, Journal of Proteome Research Article ASAP, DOI: 10.1021/acs.jproteome.3c00473