High-Parameter Immune Profiling with CyTOF

Area of Science:

• Immunology
• Biotechnology
• Computational Biology

Background:

• Mass cytometry (CyTOF) is a powerful tool for high-parameter single-cell analysis.
• Monitoring systemic immune changes is vital for cancer immunotherapy research.
• Standardized protocols are needed for reliable immune cell phenotyping.

Purpose of the Study:

• To present a comprehensive reference panel for identifying major immune cell populations using mass cytometry.
• To describe best practices for minimizing and tracking batch variability in CyTOF experiments.
• To demonstrate automated analysis of CyTOF data using the Astrolabe platform.

Main Methods:

• Development of a flexible reference panel for immune cell identification.
• Implementation of sample barcoding, spiked-in reference cells, and lyophilized antibody cocktails to control batch effects.
• Utilizing cryopreserved peripheral blood mononuclear cells (PBMCs) for sample batching and comparability.
• Application of the Astrolabe platform for automated data analysis.

Main Results:

• A validated reference panel capable of identifying diverse immune cell populations was established.
• The described methods effectively minimized and tracked batch variability in CyTOF data.
• Cryopreserved PBMCs facilitated consistent sample processing and analysis.
• Automated analysis using Astrolabe provided efficient and reproducible results.

Conclusions:

• This protocol provides a robust framework for high-parameter immune cell phenotyping using mass cytometry.
• The presented methods enhance the reliability and comparability of CyTOF data in cancer immunotherapy studies.
• Automated analysis offers a streamlined approach for processing complex CyTOF datasets.