FFPE is a specific way to preserve and prepare biopsy specimens that can be used in several ways for example examination, diagnostic and experimental research. While large biobanks offer an invaluable resource for clinical and biomarker research, it has been challenging to integrate FFPE tissue samples with proteomics studies.

Sensitive and reproducible workflows are needed for clinical studies in general, but are even more important for sample types as FFPE, where the biggest issue is to reverse the crosslinks and efficiently extract proteins.

The Küster group at the Technical University of Munich have established a robust workflow to support the analysis of large cohorts of patient samples using FFPE tissue. They focused on finding a reasonable balance between achieving high proteome depth and limiting the overall analysis time. By taking advantage of the Evotip, they compared online gas phase separation by FAIMS to be on par with classic stage-tip based high-pH fractionation but requiring 50% less sample and reducing sample handling.

They carefully characterized the FAIMS settings for maximum coverage of peptides in a complex digest with data-dependent acquisition on a Thermo Scientific Exploris 480 MS. Using a single compensation voltage (CV) resulted in a reduction of peptides independent of LC gradient length, while improving the protein identifications. Combining two CVs increased the number of peptide and protein identifications for all the used Evosep methods. Further analysis showed that one, two and five CVs were the optimal combination for the 60 SPD, 30 SPD and Extended method, respectively.

Quantitative reproducibility is an important measure, which is challenged when using a single CV due to a loss in intensity of both doubly and triply charged peptides. This is partially recovered when the correlation is calculated from protein intensities and particularly when several CVs are combined.

They compared four fractions from basic pH reversed-phase (bRP) chromatography on stage-tips, each analyzed with the 30 samples per day method with online separation by FAIMS with two injections using the Extended method. For this, they loaded 600 ng peptides and analyzed them twice with two sets of 5 CVs per run for a total of 10 CVs per sample.

The four fractions led to the identification of 5247 and 5281 proteins without or with FAIMS respectively, whereas the injections with no bRP fractionation led to 3799 and 5368 proteins without and with FAIMS respectively. This demonstrates that the FAIMS workflow without bRP fractionation can achieve a similar depth, while using 50% less starting material. They applied this to three different tissue types and achieved a similar proteome depth with a dynamic range of nearly seven orders of magnitude.

In conclusion, they have developed a workflow for FFPE tissue analysis, which provides the necessary throughput and robustness needed for analyzing large cohorts of clinical samples.

Read full publication here: https://pubs.acs.org/doi/10.1021/acs.jproteome.1c00695


Here you can see publications available using FFPE featuring Evosep One. For a full overview of publications published using the Evosep One Technology visit our Literature room here

TitleSubjectMaterialYearSummaryEvosep methodMS instrumentationLearn More
A Non-Hazardous Deparaffinization Protocol Enables Quantitative Proteomics of Core Needle Biopsy-Sized Formalin-Fixed and Paraffin-Embedded (FFPE) Tissue Specimens, , 2022

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High-Field Asymmetric Waveform Ion Mobility Spectrometry and Parallel Reaction Monitoring Increases Sensitivity for Clinical Biomarker Quantitation from FormalinFixed, Paraffin-Embedded Tumor Biopsies, , , 2022

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Evaluation of Disposable Trap Column nanoLC–FAIMS–MS/MS for the Proteomic Analysis of FFPE Tissue, , 2021

This publication by the Kuster group presents a robust workflow to support the analysis of large cohorts of patient samples using formalin-fixed paraffin-embedded FFPE tissue. They make use of online fractionation by FAIMS requiring 50% less sample than conventional high pH fractionation.

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