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Updated: Sep 20, 2025

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Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
Published on: June 26, 2018
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Standardization of Suspension and Imaging Mass Cytometry Single-Cell Readouts for Clinical Decision Making
Ruben Casanova1,2, Shuhan Xu1,2, Pierre Bost1,2
1Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Summary
Standardized mass cytometry methods ensure reproducible proteomic analysis for clinical applications. This study validates pipelines for consistent, high-quality data, offering valuable insights into patient tumor biology for oncologists.
Area of Science:
- Biotechnology
- Proteomics
- Cancer Research
Background:
- Mass cytometry, including suspension and imaging techniques, offers single-cell proteomic analysis for tissue characterization.
- Clinical application of mass cytometry requires robust data consistency over time, with limited existing data.
Purpose of the Study:
- To develop and validate experimental and computational pipelines for standardized mass cytometry within a clinical trial setting.
- To assess and correct for batch effects in mass cytometry data over a one-year period.
- To demonstrate the clinical utility of reproducible mass cytometry for guiding cancer treatment decisions.
Main Methods:
- Utilized frozen antibody panels to minimize batch effects between experiments.
- Incorporated well-characterized reference samples for batch effect assessment and correction.
- Systematically evaluated a test tumor sample across multiple runs to confirm batch correction efficacy.
Main Results:
- Developed pipelines within the Tumor Profiler clinical study for advanced cancer patients.
- Batch correction approach consistently reduced signal variations in test tumor samples.
- Demonstrated reproducible and robust proteomic data meeting clinical requirements.
Conclusions:
- Standardized suspension and imaging mass cytometry generate reliable data suitable for clinical use.
- The developed pipelines provide oncologists with critical insights into patient tumor biology.
- These methods support data-driven treatment decisions in advanced cancer care.

