Spatial proteomics and transcriptomics characterization of tissue and multiple cancer types including decalcified...

Area of Science:

• Spatial biology
• Genomics
• Proteomics
• Tissue processing

Background:

• Emerging spatial imaging technologies offer single-cell resolution for gene and protein expression in FFPE tissues.
• Platforms like Xenium and PhenoCycler-Fusion are powerful but lack systematic methods for tissue quality, marker integrity, and reproducibility.
• Preanalytical challenges hinder the full potential of spatial biology techniques.

Purpose of the Study:

• To optimize technical methods for spatial biology by addressing preanalytical challenges.
• To develop and validate a decalcification protocol for FFPE bone marrow preserving nucleic acids for spatial proteomics and transcriptomics.
• To characterize a multicancer tissue microarray (TMA) for evaluating spatial biology platforms.

Main Methods:

• Developed a multicancer tissue microarray (TMA).
• Processed FFPE bone marrow core samples using a novel molecular- and protein-friendly decalcification protocol.
• Utilized PhenoCycler for high-plex spatial proteomics and Xenium for spatial transcriptomics, with subsequent data analysis using QuPath and custom pipelines.

Main Results:

• PhenoCycler and Xenium platforms showed good marker concordance on TMA sections across various tumor types.
• The optimized decalcification protocol effectively preserved mRNA and protein markers in bone marrow.
• Xenium analysis successfully resolved major cell types in decalcified bone marrow while maintaining morphology.

Conclusions:

• Validated PhenoCycler-Fusion spatial proteomics and Xenium spatial transcriptomics platforms for diverse tumor types, including decalcified bone marrow.
• Demonstrated a robust, molecular-friendly decalcification protocol for FFPE bone marrow core biopsies.
• Established systematic quality assessment methods for spatial proteomic and transcriptomic data, enabling orthogonal confirmation between platforms.