Towards routine proteome profiling of FFPE tissue: insights from a 1,220-case pan-cancer study

Johanna Tüshaus, Stephan Eckert, Marius Schliemann, Yuxiang Zhou, Pauline Pfeiffer, Christiane Halves, Federico Fusco, Johannes Weigel, Lisa Hönikl, Vicki Butenschön, Rumyana Todorova, Hilka Rauert-Wunderlich, Matthew The, Andreas Rosenwald, Volker Heinemann, Julian Holch, Katja Steiger, Claire Delbridge, Bernhard Meyer, Wilko WeichertCarolin Mogler, Peer Hendrik Kuhn, Bernhard Kuster

Research output: Contribution to journalArticlepeer-review

Abstract

Proteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performance of experimental workflows. In this study, we analyze 1220 tumors from six cancer entities processed over the course of three years. Key findings include the need for a new normalization method ensuring equal and reproducible sample loading for LC-MS/MS analysis across cohorts, showing that tumors can, on average, be profiled to a depth of >4000 proteins and discovering that current software fails to process such large ion mobility-based online fractionated datasets. We report the first comprehensive pan-cancer proteome expression resource for FFPE material comprising 11,000 proteins which is of immediate utility to the scientific community, and can be explored via a web resource. It enables a range of analyses including quantitative comparisons of proteins between patients and cohorts, the discovery of protein fingerprints representing the tissue of origin or proteins enriched in certain cancer entities.

Original languageEnglish
Article number5707
Pages (from-to)304-329
Number of pages26
JournalEMBO Journal
Volume44
Issue number1
DOIs
StatePublished - 2 Jan 2025

Keywords

  • Clinical Proteomics
  • Mass Spectrometry
  • Pan-cancer
  • Public Pan-cancer FFPE Resource
  • TIC Normalization

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