Literature DB >> 32108428

Advanced Cell Mapping Visualizations for Single Cell Functional Proteomics Enabling Patient Stratification.

Nick Bowman1, Dong Liu1, Patrick Paczkowski1, Jon Chen1, John Rossi2, Sean Mackay1, Adrian Bot2, Jing Zhou1.   

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.
© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  IsoCode chip; data visualization; single-cell proteomics; t-distributed stochastic neighbor embedding; uniform manifold approximation and projection

Mesh:

Substances:

Year:  2020        PMID: 32108428     DOI: 10.1002/pmic.201900270

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   5.393


  3 in total

1.  Systematic Identification of Key Functional Modules and Genes in Gastric Cancer.

Authors:  Rui Wu; Jin-Yu Sun; Li-Li Zhao; Zhi-Ning Fan; Cheng Yang
Journal:  Biomed Res Int       Date:  2020-11-16       Impact factor: 3.411

2.  Single-cell polyfunctional proteomics of CD4 cells from patients with AML predicts responses to anti-PD-1-based therapy.

Authors:  Hussein A Abbas; Zoe Alaniz; Sean Mackay; Matthew Cyr; Jing Zhou; Ghayas C Issa; Mansour Alfayez; Jairo Matthews; Steven M Kornblau; Elias Jabbour; Guillermo Garcia-Manero; Marina Konopleva; Michael Andreeff; Naval Daver
Journal:  Blood Adv       Date:  2021-11-23

3.  Tumor-derived NKG2D ligand sMIC reprograms NK cells to an inflammatory phenotype through CBM signalosome activation.

Authors:  Payal Dhar; Fahmin Basher; Zhe Ji; Lei Huang; Si Qin; Derek A Wainwright; Jerid Robinson; Shaye Hagler; Jing Zhou; Sean MacKay; Jennifer D Wu
Journal:  Commun Biol       Date:  2021-07-22
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.