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Related Experiment Video

Updated: Mar 30, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Fast and sensitive spatial proteomics using laser capture microdissection and a protein immobilization-based

Lingxiao Weng¹, Wenjia Zhang¹, Guoquan Yan¹

¹Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200438, China.

Analytica Chimica Acta

|March 28, 2026

Summary

We developed a rapid spatial proteomics method using laser capture microdissection and a capillary microreactor. This technique enables sensitive protein analysis from tiny tissue samples, revealing important spatial variations in tumors.

Keywords:

LC-MS/MS Protein immobilization Proteomic sample preparation Spatial proteomics Tumor heterogeneity

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Last Updated: Mar 30, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor

Published on: April 6, 2016

Digital Microfluidics for Automated Proteomic Processing

Digital Microfluidics for Automated Proteomic Processing

Published on: November 6, 2009

Area of Science:

Proteomics
Biotechnology
Cancer Research

Background:

Biological tissues exhibit complex spatial organization with diverse cell functions.
Spatial proteomics aims to analyze protein expression within tissue context.
Current liquid chromatography tandem mass spectrometry (LC-MS/MS) methods lack resolution for microscale samples due to sample loss.

Purpose of the Study:

To develop a high-resolution spatial proteome profiling method.
To overcome sensitivity limitations in analyzing microscale tissue inputs.
To enable rapid and sensitive sample processing for spatial proteomics.

Main Methods:

Developed a protein immobilization-based capillary microreactor (PICR).
Combined PICR with laser capture microdissection (LCM) for sample collection.
Utilized LC-MS/MS for proteomic analysis.

Main Results:

Identified over 1700 proteins from 1.0 × 10⁻⁵ mm³ tumor tissue.
PICR-based sample processing completed in under 1 hour.
Detected significant protein abundance differences and spatial trends within tumor regions, correlating with tumor features.

Conclusions:

The LCM-PICR workflow offers a fast and sensitive strategy for spatial proteomics on micrometer-scale tissue.
This method effectively detects spatially structured protein variations in tumors.
Provides a practical tool for studying intratumoral heterogeneity and spatially resolved disease biology.