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  • 标题:Multiplexed protein profiling reveals spatial subcellular signaling networks
  • 本地全文:下载
  • 作者:Shuangyi Cai ; Thomas Hu ; Mythreye Venkatesan
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:9
  • 页码:1-30
  • DOI:10.1016/j.isci.2022.104980
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryProtein-protein interaction networks are altered in multi-gene dysregulations in many disorders. Image-based protein multiplexing sheds light on signaling pathways to dissect cell-to-cell heterogeneity, previously masked by the bulk assays. Herein, we present a rapid multiplexed immunofluorescence (RapMIF) method measuring up to 25-plex spatial protein maps from cultures and tissues at subcellular resolution, providing combinatorial 272 pairwise and 1,360 tri-protein signaling states across 33 multiplexed pixel-level clusters. The RapMIF pipeline automated staining, bleaching, and imaging of the biospecimens in a single platform. RapMIF showed that WNT/β-catenin signaling upregulated upon the inhibition of the AKT/mTOR pathway. Subcellular protein images demonstrated translocation patterns, spatial receptor discontinuity, and subcellular signaling clusters in single cells. Signaling networks exhibited spatial redistribution of signaling proteins in drug-responsive cultures. Machine learning analysis predicted the phosphorylated β-catenin expression from interconnected signaling protein images. RapMIF is an ideal signaling discovery approach for precision therapy design.Graphical abstractDisplay OmittedHighlights•Pixel clustering maps revealed the neighborhood of signaling proteins•Osimertinib downregulatedp-AKT and inhibited cell proliferation and survival•Multiplexed profiling dissects signaling networks for drug response predictionBiological sciences; Biotechnology; Biological sciences research methodologies; Biology experimental methods
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