A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis

Research output: Contribution to journalJournal articlepeer-review

Standard

A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis. / Coscia, Fabian; Doll, Sophia; Bech, Jacob Mathias; Schweizer, Lisa; Mund, Andreas; Lengyel, Ernst; Lindebjerg, Jan; Madsen, Gunvor Iben; Moreira, José M A; Mann, Matthias.

In: Journal of Pathology, Vol. 251, 2020, p. 110-112.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Coscia, F, Doll, S, Bech, JM, Schweizer, L, Mund, A, Lengyel, E, Lindebjerg, J, Madsen, GI, Moreira, JMA & Mann, M 2020, 'A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis', Journal of Pathology, vol. 251, pp. 110-112. https://doi.org/10.1002/path.5420

APA

Coscia, F., Doll, S., Bech, J. M., Schweizer, L., Mund, A., Lengyel, E., Lindebjerg, J., Madsen, G. I., Moreira, J. M. A., & Mann, M. (2020). A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis. Journal of Pathology, 251, 110-112. https://doi.org/10.1002/path.5420

Vancouver

Coscia F, Doll S, Bech JM, Schweizer L, Mund A, Lengyel E et al. A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis. Journal of Pathology. 2020;251:110-112. https://doi.org/10.1002/path.5420

Author

Coscia, Fabian ; Doll, Sophia ; Bech, Jacob Mathias ; Schweizer, Lisa ; Mund, Andreas ; Lengyel, Ernst ; Lindebjerg, Jan ; Madsen, Gunvor Iben ; Moreira, José M A ; Mann, Matthias. / A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis. In: Journal of Pathology. 2020 ; Vol. 251. pp. 110-112.

Bibtex

@article{4c0fd96c7c5043b6ac3cb2f59713a9f3,
title = "A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis",
abstract = "Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Here, we describe an MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total work up took less than a day. We observed a moderate trend towards lower protein identifications in long-term stored samples (>15 years) but clustering into distinct proteomic subtypes was independent of archival time. Our results underline the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and prove the feasibility of analyzing large tissue cohorts in a robust, timely and streamlined manner. This article is protected by copyright. All rights reserved.",
author = "Fabian Coscia and Sophia Doll and Bech, {Jacob Mathias} and Lisa Schweizer and Andreas Mund and Ernst Lengyel and Jan Lindebjerg and Madsen, {Gunvor Iben} and Moreira, {Jos{\'e} M A} and Matthias Mann",
year = "2020",
doi = "10.1002/path.5420",
language = "English",
volume = "251",
pages = "110--112",
journal = "Journal of Pathology",
issn = "0022-3417",
publisher = "JohnWiley & Sons Ltd",

}

RIS

TY - JOUR

T1 - A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis

AU - Coscia, Fabian

AU - Doll, Sophia

AU - Bech, Jacob Mathias

AU - Schweizer, Lisa

AU - Mund, Andreas

AU - Lengyel, Ernst

AU - Lindebjerg, Jan

AU - Madsen, Gunvor Iben

AU - Moreira, José M A

AU - Mann, Matthias

PY - 2020

Y1 - 2020

N2 - Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Here, we describe an MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total work up took less than a day. We observed a moderate trend towards lower protein identifications in long-term stored samples (>15 years) but clustering into distinct proteomic subtypes was independent of archival time. Our results underline the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and prove the feasibility of analyzing large tissue cohorts in a robust, timely and streamlined manner. This article is protected by copyright. All rights reserved.

AB - Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Here, we describe an MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total work up took less than a day. We observed a moderate trend towards lower protein identifications in long-term stored samples (>15 years) but clustering into distinct proteomic subtypes was independent of archival time. Our results underline the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and prove the feasibility of analyzing large tissue cohorts in a robust, timely and streamlined manner. This article is protected by copyright. All rights reserved.

U2 - 10.1002/path.5420

DO - 10.1002/path.5420

M3 - Journal article

C2 - 32154592

VL - 251

SP - 110

EP - 112

JO - Journal of Pathology

JF - Journal of Pathology

SN - 0022-3417

ER -

ID: 239206071