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Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics.

ABSTRACT: 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.

SUBMITTER: Kumar MP

PROVIDER: S-EPMC7009724 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics.

Kumar Manu P MP Du Jinyan J Lagoudas Georgia G Jiao Yang Y Sawyer Andrew A Drummond Daryl C DC Lauffenburger Douglas A DA Raue Andreas A

Cell reports 20181101 6

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 sing ...[more]

PMID: 30404002

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Project description:Branching organs, including the salivary and mammary glands, lung, and kidney, arise as epithelial buds that are morphologically very similar. However, the mesenchyme is known to guide epithelial morphogenesis and to help govern cell fate and eventual organ specificity. We performed single-cell transcriptome analyses of 14,441 cells from embryonic day 12 submandibular and parotid salivary glands to characterize their molecular identities during bud initiation. The mesenchymal cells were considerably more heterogeneous by clustering analysis than the epithelial cells. Nonetheless, distinct clusters were evident among even the epithelial cells, where unique molecular markers separated presumptive bud and duct cells. Mesenchymal cells formed separate, well-defined clusters specific to each gland. Neuronal and muscle cells of the 2 glands in particular showed different markers and localization patterns. Several gland-specific genes were characteristic of different rhombomeres. A muscle cluster was prominent in the parotid, which was not myoepithelial or vascular smooth muscle. Instead, the muscle cluster expressed genes that mediate skeletal muscle differentiation and function. Striated muscle was indeed found later in development surrounding the parotid gland. Distinct spatial localization patterns of neuronal and muscle cells in embryonic stages appear to foreshadow later differences in adult organ function. These findings demonstrate that the establishment of transcriptional identities emerges early in development, primarily in the mesenchyme of developing salivary glands. We present the first comprehensive description of molecular signatures that define specific cellular landmarks for the bud initiation stage, when the neural crest-derived ectomesenchyme predominates in the salivary mesenchyme that immediately surrounds the budding epithelium. We also provide the first transcriptome data for the largely understudied embryonic parotid gland as compared with the submandibular gland, focusing on the mesenchymal cell populations.

Dataset Information

Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics.

Publications

Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics.

Similar Datasets

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