Deciphering Cell–Cell Interactions with Integrative Single‐Cell Secretion Profiling

Abstract: Cell–cell interactions are the fundamental behaviors to regulate cellular activities. A comprehensive evaluation of intercellular interactions requires direct profiling of various signaling behaviors simultaneously at the single‐cell level, which remains lacking. Herein, an integrative single‐cell secretion analysis platform is presented to profile different secreted factors (four proteins, three extracellular vesicles (EV) phenotypes), spatial distances, and migration information (distances and direction) simultaneously from high‐throughput paired single cells using an antibody‐barcode microchip. Applying the platform to analyze the tumor–stromal and tumor–immune interactions with the human oral squamous cell carcinoma (OSCC) cell lines and primary OSCC cells reveals that the initial distances between cells would determine their migratory distances and direction to approach stable organization. The cell–cell in close proximity enhances protein secretions while attenuating EV secretions. Migration has a more profound correlation with protein secretions than EV secretions, in which absolute migration distance affects protein secretions significantly but not the direction. These findings highlight the significance of spatial organization in regulating cell signaling behaviors and demonstrate that the integrative single‐cell secretion profiling platform is well‐suited for a comprehensive dissection of intercellular communication and interactions, providing new avenues for understanding cell–cell interaction biology and how different signaling behaviors coordinate within the tumor microenvironment.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Deciphering Cell–Cell Interactions with Integrative Single‐Cell Secretion Profiling ; day:26 ; month:04 ; year:2023 ; extent:9
Advanced science ; (26.04.2023) (gesamt 9)

Creator
Li, Linmei
Su, Haoran
Ji, Yahui
Zhu, Fengjiao
Deng, Jiu
Bai, Xue
Li, Huibing
Liu, Xianming
Luo, Yong
Lin, Bingcheng
Liu, Tingjiao
Lu, Yao

DOI
10.1002/advs.202301018
URN
urn:nbn:de:101:1-2023042615330166041458
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:45 AM CEST

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Associated

  • Li, Linmei
  • Su, Haoran
  • Ji, Yahui
  • Zhu, Fengjiao
  • Deng, Jiu
  • Bai, Xue
  • Li, Huibing
  • Liu, Xianming
  • Luo, Yong
  • Lin, Bingcheng
  • Liu, Tingjiao
  • Lu, Yao

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