Imaging mass cytometry-derived single cell extraction, transformation and phenotyping to analyze immune tumor...

Area of Science:

• Spatial biology and proteomics
• Computational pathology and bioinformatics

Background:

• Spatial technologies enable deep investigation of cellular interactions within intact tissues.
• Conventional single-cell methods lack spatial context.
• Imaging mass cytometry (IMC) is a powerful spatial proteomics platform.

Purpose of the Study:

• To provide a practical guide for extracting single-cell data and spatial information from IMC images.
• To assist basic scientists in performing spatial analyses and cell clustering on IMC data.
• To overcome technical challenges in analyzing multiplex IMC images.

Main Methods:

• Detailed step-by-step protocol for single-cell data extraction from IMC multiplex images.
• Methodology for obtaining spatial information from intact tissue samples analyzed by IMC.
• Guidance on cell clustering and spatial analysis techniques for IMC datasets.

Main Results:

• Successful extraction of single-cell data and spatial information from complex IMC images.
• Demonstration of effective cell clustering and spatial analysis workflows.
• Simplified approach to analyzing spatial proteomics data for basic scientists.

Conclusions:

• This chapter demystifies the analysis of imaging mass cytometry data.
• Enables researchers without extensive bioinformatics expertise to perform advanced spatial analyses.
• Facilitates deeper understanding of cellular spatial interactions in tissues.