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Related Experiment Video

Updated: Jan 9, 2026

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Published on: March 29, 2021

3D pathology-guided microdissection.

Huai-Ching Hsieh^1,2, Gan Gao^2,3, Qinghua Han^1,2

¹Department of Bioengineering, Stanford University, Stanford, CA, USA.

Biorxiv : the Preprint Server for Biology

|December 3, 2025

Summary

This summary is machine-generated.

Researchers developed a novel 3D microdissection technique using computer numerical controlled (CNC) milling and light-sheet microscopy. This method allows detailed molecular analysis of complex 3D tissue structures, advancing tumor evolution studies.

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Area of Science:

Biomedical Engineering
Microscopy
Molecular Biology

Background:

Traditional microdissection methods are limited to 2D tissue sections.
3D microscopy is increasingly used, but lacks analogous volumetric dissection tools.
Analyzing complex 3D tissue architectures for molecular insights remains challenging.

Purpose of the Study:

To develop a novel 3D microdissection technique for volumetric tissue analysis.
To enable molecular studies of complex 3D biological structures.
To overcome limitations of 2D methods in studying dynamic processes like tumor evolution.

Main Methods:

Integration of computer numerical controlled (CNC) milling with open-top light-sheet microscopy.
Development of a volumetric microdissection workflow for intact 3D tissues.
Application of the method to analyze 3D branching architectures.

Main Results:

Successful demonstration of 3D microdissection for molecular analysis.
Ability to study tumor evolution along convoluted 3D branching architectures.
Overcoming the spatial limitations of traditional 2D microdissection techniques.

Conclusions:

The developed CNC milling-based 3D microdissection is a powerful tool for volumetric molecular analysis.
This technique opens new avenues for studying complex biological systems in three dimensions.
It significantly advances the capability to investigate processes like tumor evolution in intricate tissue structures.