Automated High-Dimensional Cytometry Analysis to Elucidate Phenotypic and Functional Modulation in Immuno Cellular Subpopulations

• Activity Number: 260
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Shubing Wang* and An Chi and Yujie Qu
• Companies: Merck and Merck and Merck
• Keywords: Cytometry ; Cell ; inhibitor ; Clustering

Abstract

Immunophenotypic analysis of single cells has become strategically important to Immune-Modeulatory Receptor (IMR) discovery. Being able to simultaneously analyze up to 100 intra-cellular and surface markers,Mass cytometry (CyTOF) addresses immunophenotyping with extended and higher-dimensional single-cell analysis than Flow Cytometry. High-dimensional CyTOF analysis, though extremely attractive in discovery, imposes scalability and subjectivity issues on standard manual gating practice. We developed a CyTOF data analysis platform to automatically identify all the cellular sub-populations using a data-driven hierarchical clustering algorithm. A LASSO-based feature selection procedure is then applied to search for stratifying biomarkers or pathways representing experimental perturbations. As a proof-of-concept we applied this method to automatically identify statistically significant changes among a total of 25 intracelluar and surface markers including (IL22, IL17a and IL17F et al) in whole blood samples from 10+ healthy donors after ex vivo IL23+IL1? stimulation following the treatment of ROR?T-specific inhibitor.