Advanced Cell Mapping Visualizations for Single Cell Functional Proteomics Enabling Patient Stratification. Issue 13 (6th July 2020)

• Record Type: Journal Article
• Authors: Bowman, Nick; Liu, Dong; Paczkowski, Patrick; Chen, Jon; Rossi, John; Mackay, Sean; Bot, Adrian; Zhou, Jing
• Other Names: Fan Rong guestEditor.; Wei Wei guestEditor.
• Is Part Of: Proteomics. Volume 20:Issue 13(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-06
• Subjects: data visualization -- IsoCode chip -- single‐cell proteomics -- t‐distributed stochastic neighbor embedding -- uniform manifold approximation and projection; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201900270
• Languages: English
• ISSNs: 1615-9853

Abstract

Abstract: Highly multiplexed single‐cell functional proteomics has emerged as one of the next‐generation toolkits for a deeper understanding of functional heterogeneity in cell. Different from the conventional population‐based bulk and single‐cell RNA‐Seq assays, the microchip‐based proteomics at the single‐cell resolution enables a unique identification of highly polyfunctional cell subsets that co‐secrete many proteins from live single cells and most importantly correlate with patient response to a therapy. The 32‐plex IsoCode chip technology has defined a polyfunctional strength index (PSI) of pre‐infusion anti‐CD19 chimeric antigen receptor (CAR)‐T products, that is significantly associated with patient response to the CAR‐T cell therapy. To complement the clinical relevance of the PSI, a comprehensive visualization toolkit of 3D uniform manifold approximation and projection (UMAP) and t‐distributed stochastic neighbor embedding (t‐SNE) in a proteomic analysis pipeline is developed, providing more advanced analytical algorithms for more intuitive data visualizations. The UMAP and t‐SNE of anti‐CD19 CAR‐T products reveal distinct cytokine profiles between nonresponders and responders and demonstrate a marked upregulation of antitumor‐associated cytokine signatures in CAR‐T cells from responding patients. Using this powerful while user‐friendly analytical tool, the multi‐dimensional single‐cell data can be dissected from complex immune responses and uncover underlying mechanisms, which can promote correlative biomarker discovery, improved bioprocessing, and personalized treatment development.