Comparison of imaging-based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed,...

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Imaging-based spatial transcriptomics (ST) is crucial for understanding tumor biology and microenvironments.
• Systematic evaluations of commercially available ST platforms are lacking.

Purpose of the Study:

• To rigorously compare the performance of single-cell ST platforms (CosMx, MERFISH, Xenium).
• To evaluate ST platforms against bulk RNA sequencing, multiplex immunofluorescence, and other spatial profiling methods.
• To provide insights into optimizing spatial profiling workflows.

Main Methods:

• Utilized serial sections of formalin-fixed, paraffin-embedded lung adenocarcinoma and mesothelioma tumor samples.
• Compared CosMx, MERFISH, and Xenium (uni/multi-modal) platforms.
• Validated against bulk RNA sequencing, multiplex immunofluorescence, GeoMx DSP, and H&E staining.
• Performed objective automated and manual pixel-resolution cell segmentation and phenotyping.

Main Results:

• Detailed intricate differences between the evaluated ST platforms.
• Identified tissue age and probe design as critical factors affecting data quality.
• Demonstrated the importance of both automated and manual phenotyping for pathological relevance.

Conclusions:

• The study provides a systematic comparison of leading ST platforms.
• Highlights key parameters influencing spatial transcriptomics data quality and reliability.
• Offers guidance for selecting appropriate workflows for spatial profiling and molecular discovery in cancer research.