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Background <p>Formalin-fixed, paraffin-embedded (FFPE) tissue remains the gold standard for extensively archiving biological specimens, providing biobanks with large repositories of retrospective potential. However, while formalin crosslinking is effective at preserving tissue, it poses significant challenges for extracting molecular information, including the proteome. Methods currently proposed to overcome these challenges on the Zeiss PALM Microbeam instrument rely on specialized protocols and custom hardware, that are not necessarily accessible or adaptable for routine use in most laboratories, limiting widespread application and standardization. To address these limitations, we developed an easily adaptable and highly efficient workflow for extracting deep proteomes from low-input materials, such as biopsies used in routine histopathological diagnostics. This streamlined approach not only enhances accessibility and standardization on the Zeiss platform, but also outperforms previous methodologies on this platform in proteomic depth and quality, enabling more comprehensive insights into the molecular complexity of FFPE specimens.</p> Methods <p>We tested different buffers—including guanidinium chloride, hydrogen peroxide, PBS, and TEAB—with and without reducing and alkylating agents. We also evaluated various clean-up approaches, as well as different durations of boiling and sonication. With those results, we then compared the extraction efficiency of pancreatic acinar cells identified in FFPE tissue samples stained with conventional hematoxylin-eosin (H&amp;E) against that of cells isolated from tissue samples immunostained for the epithelial cell adhesion molecule (EpCAM) across material inputs ranging from 1,166 to 800,000&#xa0;μm² (estimated to 2 to 1,310 cells in volume). Cells were isolated using laser capture microdissection and subsequently analyzed using Liquid Chromatography-Tandem Mass Spectrometry.</p> Results <p>From the optimization, we found that the best-performing condition was TEAB without reducing and alkylating agents, no clean-up step, 5&#xa0;min of boiling, and 10 cycles of 30-second on/off sonication. Using this optimized protocol, we achieved comparable protein yields across methods, with EpCAM-positive cells yielding slightly higher results—approximately 1,200 unique protein groups at the lowest input and up to ~ 5,900 at the highest. In cells isolated from H&amp;E-stained tissue, ~ 900 to ~ 5,200 protein groups were identified. We determined that the optimal balance for our workflow, ensuring maximum protein identification while minimizing input material, lies within the range of approximately 50,000 to 100,000&#xa0;μm². With these results, we tested spatial capabilities and biological relevance by isolating cancer cells from biopsies of pancreatic cancer, lung cancer, or glioblastoma, with the first two stained for EpCAM and the latter stained against the tumor-suppressor protein p53. We successfully identified tissue-specific protein expression and observed prominent clustering of all cell populations.</p> Discussion <p>Our results highlight the feasibility of performing spatial proteomics on FFPE tissue using minimal input material. This adaptable methodology opens up possibilities for investigating cell-type-specific biology while preserving spatial and histological information.</p>

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Refining spatial proteomics by mass spectrometry: an efficient workflow tailored for archival tissue

  • 期刊论文

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  • 发表日期：

    2026年4月22日

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  • Rune Daucke,
  • Charlotte V. Rift,
  • Nicolai S. Bager,
  • Kartikey Saxena,
  • Peter R. Koffeldt,
  • Jakob Woessmann,
  • Valdemaras Petrosius,
  • Eric Santoni-Rugiu,
  • Bjarne W. Kristensen,
  • Pia Klausen,
  • Erwin M. Schoof

摘要

Background

Formalin-fixed, paraffin-embedded (FFPE) tissue remains the gold standard for extensively archiving biological specimens, providing biobanks with large repositories of retrospective potential. However, while formalin crosslinking is effective at preserving tissue, it poses significant challenges for extracting molecular information, including the proteome. Methods currently proposed to overcome these challenges on the Zeiss PALM Microbeam instrument rely on specialized protocols and custom hardware, that are not necessarily accessible or adaptable for routine use in most laboratories, limiting widespread application and standardization. To address these limitations, we developed an easily adaptable and highly efficient workflow for extracting deep proteomes from low-input materials, such as biopsies used in routine histopathological diagnostics. This streamlined approach not only enhances accessibility and standardization on the Zeiss platform, but also outperforms previous methodologies on this platform in proteomic depth and quality, enabling more comprehensive insights into the molecular complexity of FFPE specimens.

Methods

We tested different buffers—including guanidinium chloride, hydrogen peroxide, PBS, and TEAB—with and without reducing and alkylating agents. We also evaluated various clean-up approaches, as well as different durations of boiling and sonication. With those results, we then compared the extraction efficiency of pancreatic acinar cells identified in FFPE tissue samples stained with conventional hematoxylin-eosin (H&E) against that of cells isolated from tissue samples immunostained for the epithelial cell adhesion molecule (EpCAM) across material inputs ranging from 1,166 to 800,000 μm² (estimated to 2 to 1,310 cells in volume). Cells were isolated using laser capture microdissection and subsequently analyzed using Liquid Chromatography-Tandem Mass Spectrometry.

Results

From the optimization, we found that the best-performing condition was TEAB without reducing and alkylating agents, no clean-up step, 5 min of boiling, and 10 cycles of 30-second on/off sonication. Using this optimized protocol, we achieved comparable protein yields across methods, with EpCAM-positive cells yielding slightly higher results—approximately 1,200 unique protein groups at the lowest input and up to ~ 5,900 at the highest. In cells isolated from H&E-stained tissue, ~ 900 to ~ 5,200 protein groups were identified. We determined that the optimal balance for our workflow, ensuring maximum protein identification while minimizing input material, lies within the range of approximately 50,000 to 100,000 μm². With these results, we tested spatial capabilities and biological relevance by isolating cancer cells from biopsies of pancreatic cancer, lung cancer, or glioblastoma, with the first two stained for EpCAM and the latter stained against the tumor-suppressor protein p53. We successfully identified tissue-specific protein expression and observed prominent clustering of all cell populations.

Discussion

Our results highlight the feasibility of performing spatial proteomics on FFPE tissue using minimal input material. This adaptable methodology opens up possibilities for investigating cell-type-specific biology while preserving spatial and histological information.