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Updated: May 30, 2025
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
Comparison of imaging-based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed,
Nejla Ozirmak Lermi1,2, Max Molina Ayala3,2, Sharia Hernandez Ruiz3
1Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
This study systematically compares three spatial transcriptomics (ST) platforms: CosMx, MERFISH, and Xenium. It reveals critical differences in their performance for tumor microenvironment analysis, guiding future spatial biology research.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Spatial transcriptomics (ST) is crucial for understanding tumor microenvironments.
- Commercial ST platforms lack systematic performance evaluations.
- Tumor heterogeneity necessitates advanced spatial profiling techniques.
Purpose of the Study:
- To rigorously compare the performance of CosMx, MERFISH, and Xenium single-cell ST platforms.
- To evaluate ST platform data against bulk RNA sequencing, multiplex immunofluorescence, and digital spatial profiling.
- To provide insights into optimizing spatial profiling workflows for molecular discovery.
Main Methods:
- Utilized serial sections of formalin-fixed, paraffin-embedded lung adenocarcinoma and mesothelioma.
- Compared CosMx, MERFISH, and Xenium (uni/multi-modal) platforms.
- Integrated data with bulk RNA sequencing, multiplex immunofluorescence, GeoMx DSP, and H&E staining for validation.
Main Results:
- Detailed intricate differences between the evaluated ST platforms.
- Demonstrated the impact of tissue age and probe design on data quality.
- Highlighted the importance of both automatic and manual cell segmentation/phenotyping for pathological relevance.
Conclusions:
- Identified key performance variations among leading single-cell ST platforms.
- Emphasized the need for careful consideration of technical parameters for reliable spatial profiling.
- Suggested optimized workflows for accurate molecular discovery in tumor microenvironments.
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