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Mass Cytometry: Protocol for Daily Tuning and Running Cell Samples on a CyTOF Mass Cytometer
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High-Parameter Immune Profiling with CyTOF.

Bita Sahaf1, Adeeb Rahman2, Holden T Maecker3

  • 1PICI Cancer Correlative Science Unit, Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|September 11, 2019
PubMed
Summary
This summary is machine-generated.

Mass cytometry (CyTOF) enables high-parameter single-cell analysis of immune cells, crucial for tracking cancer immunotherapy responses. This study provides a reference panel and best practices to minimize batch variability for robust immune monitoring.

Keywords:
Differential analysisMass cytometryMultiplexedPhenotypic markersSubpopulation

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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.