Cell Reports
Volume 25, Issue 6, 6 November 2018, Pages 1458-1468.e4
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Article
Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics

https://doi.org/10.1016/j.celrep.2018.10.047Get rights and content
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Highlights

  • Ligand-receptor interactions in tumors were investigated using single-cell RNA-seq

  • Identified interactions were regressed against phenotypic measurements of tumors

  • The approach provides a tool for studying cell-cell interactions and their variability

Summary

Tumor ecosystems are composed of multiple cell types that communicate by ligand-receptor interactions. Targeting ligand-receptor interactions (for instance, with immune checkpoint inhibitors) can provide significant benefits for patients. However, our knowledge of which interactions occur in a tumor and how these interactions affect outcome is still limited. We present an approach to characterize communication by ligand-receptor interactions across all cell types in a microenvironment using single-cell RNA sequencing. We apply this approach to identify and compare the ligand-receptor interactions present in six syngeneic mouse tumor models. To identify interactions potentially associated with outcome, we regress interactions against phenotypic measurements of tumor growth rate. In addition, we quantify ligand-receptor interactions between T cell subsets and their relation to immune infiltration using a publicly available human melanoma dataset. Overall, this approach provides a tool for studying cell-cell interactions, their variability across tumors, and their relationship to outcome.

Keywords

computational analysis
single-cell RNA sequencing
cell-cell communication
ligand-receptor interaction
tumor microenvironment
syngeneic mouse models
cancer patient samples

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