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Updated: Jul 18, 2025

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

Spatial Transcriptomic Technologies.

Tsai-Ying Chen^1,2,3, Li You^1,2,3, Jose Angelito U Hardillo^2,4

¹Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.

|August 26, 2023

Summary

This summary is machine-generated.

Spatial transcriptomics measures gene expression across tissues, advancing understanding of cellular interactions and diseases like cancer. This review covers current technologies, emerging methods, and data integration for deeper biological insights.

Keywords:

NGS-based spatial profiling image-guided spatially resolved single cell sequencing imaging-based spatial profiling probe-based spatial profiling spatial omics technologies

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Last Updated: Jul 18, 2025

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Spatial transcriptomics allows gene expression measurement within tissue context.
Understanding cellular organization and interactions is crucial in biology and disease.

Purpose of the Study:

To review key spatial transcriptomic technologies and their applications.
To discuss emerging technologies addressing current limitations.
To explore integration of spatial transcriptomics with other omics data.

Main Methods:

Review of existing spatial transcriptomic technologies.
Analysis of technological advancements and limitations.
Discussion of multi-omics data integration strategies.

Main Results:

Various spatial transcriptomic technologies exist with differing capabilities.
New technologies are emerging to overcome current limitations.
Integration with other omics data enhances biological insights.

Conclusions:

Spatial transcriptomics is a powerful tool for studying tissue organization and cellular phenotypes.
Emerging technologies and data integration promise deeper understanding in various biological fields.
This technology offers novel insights into neuroscience, developmental biology, and cancer research.