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Applying single-cell highly multiplexed secretome proteomics to characterize immunotherapeutic products and predict clinical responses.
Ni, Weiming; Han, Edward X; Cyr, Matthew; Mackay, Sean; Zhou, Jing.
Afiliação
  • Ni W; IsoPlexis Corporation, Branford, Connecticut, USA.
  • Han EX; IsoPlexis Corporation, Branford, Connecticut, USA.
  • Cyr M; IsoPlexis Corporation, Branford, Connecticut, USA.
  • Mackay S; IsoPlexis Corporation, Branford, Connecticut, USA.
  • Zhou J; IsoPlexis Corporation, Branford, Connecticut, USA.
Proteomics ; 23(13-14): e2200242, 2023 07.
Article em En | MEDLINE | ID: mdl-36786585
ABSTRACT
Genetically and phenotypically identical immune cell populations can be highly heterogenous in terms of their immune functions and protein secretion profiles. The microfluidic chip-based single-cell highly multiplexed secretome proteomics enables characterization of cellular heterogeneity of immune responses at different cellular and molecular layers. Increasing evidence has demonstrated that polyfunctional T cells that simultaneously produce 2+ proteins per cell at the single-cell level are key effector cells that contribute to the development of potent and durable cellular immunity against pathogens and cancers. The functional proteomic technology offers a wide spectrum of cellular function assessment and can uniquely define highly polyfunctional cell subsets with cytokine signatures from live individual cells. This high-dimensional single-cell analysis provides deep dissection into functional heterogeneity and helps identify predictive biomarkers and potential correlates that are crucial for immunotherapeutic product design optimization and personalized immunotherapy development to achieve better clinical outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica / Secretoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica / Secretoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article