High-throughput spatial proteomics from cellular to subcellular scales via a hanging droplet workflow

Abstract

Formalin-fixed paraffin-embedded (FFPE) samples are central for clinical research and spatial proteomics (SP), yet liquid chromatography-mass spectrometry (LC-MS) remains challenging due to protein extraction losses, evaporation during decrosslinking, and inefficient sample preparation. Current methods often involve complex protocols or specialized equipment, limiting scalability, throughput, and proteome depth. We present a streamlined micro-FFPE proteomics protocol for laser-capture microdissection (LMD) that enables high-throughput processing in a 96-well format, completing the workflow from tissue lysis to LC-MS-ready tryptic peptides on Evotips in just 2-hours. By integrating whole-slide imaging, LMD, and narrow-window data-independent acquisition mass spectrometry (nDIA-MS), our approach optimizes lysis, decrosslinking, and digestion within nano-wells leveraging the hanging droplet concept. This design minimizes surface adsorption, enhances sample processing efficiency, reduces preparation time by ~30% compared with reference methods, and enables parallel handling of up to 192 samples with standard equipment. This enables the quantification of >5,500 protein groups (PGs) from 50,000 µm² regions (~250 cells), with robust performance down to 1000 µm2 (~5 cells) with ~2,500 PGs identified. Application to breast cancer (BC) tissue resolves BC subtypes and microenvironments via biomarkers (TP53, HER2, PR). Even from ~60 µm² regions of single nuclei identify ~1,800 protein groups, enabling microscale spatial proteomics approaching near-organelle resolution.

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Cite

BibTeX RIS

BibTeX

@article{chen2026highthroughput,
  title = {{High-throughput spatial proteomics from cellular to subcellular scales via a hanging droplet workflow}},
  author = {Hao Chen and Ulises H. Guzman and Jesper V. Olsen},
  journal = {Nature Communications},
  year = {2026},
  month = oct,
  doi = {10.1038/s41467-026-78415-x},
  url = {https://www.nature.com/articles/s41467-026-78415-x},
  note = {CC BY 4.0},
}

RIS

TY  - JOUR
TI  - High-throughput spatial proteomics from cellular to subcellular scales via a hanging droplet workflow
AU  - Hao Chen
AU  - Ulises H. Guzman
AU  - Jesper V. Olsen
PY  - 2026
DA  - 2026/10/09
JO  - Nature Communications
DO  - 10.1038/s41467-026-78415-x
UR  - https://www.nature.com/articles/s41467-026-78415-x
AB  - Formalin-fixed paraffin-embedded (FFPE) samples are central for clinical research and spatial proteomics (SP), yet liquid chromatography-mass spectrometry (LC-MS) remains challenging due to protein extraction losses, evaporation during decrosslinking, and inefficient sample preparation. Current methods often involve complex protocols or specialized equipment, limiting scalability, throughput, and proteome depth. We present a streamlined micro-FFPE proteomics protocol for laser-capture microdissection (LMD) that enables high-throughput processing in a 96-well format, completing the workflow from tissue lysis to LC-MS-ready tryptic peptides on Evotips in just 2-hours. By integrating whole-slide imaging, LMD, and narrow-window data-independent acquisition mass spectrometry (nDIA-MS), our approach optimizes lysis, decrosslinking, and digestion within nano-wells leveraging the hanging droplet concept. This design minimizes surface adsorption, enhances sample processing efficiency, reduces preparation time by ~30% compared with reference methods, and enables parallel handling of up to 192 samples with standard equipment. This enables the quantification of >5,500 protein groups (PGs) from 50,000 µm² regions (~250 cells), with robust performance down to 1000 µm2 (~5 cells) with ~2,500 PGs identified. Application to breast cancer (BC) tissue resolves BC subtypes and microenvironments via biomarkers (TP53, HER2, PR). Even from ~60 µm² regions of single nuclei identify ~1,800 protein groups, enabling microscale spatial proteomics approaching near-organelle resolution.
SN  - 2041-1723
ER  -

Abstract

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