Tracing tumorigenesis in a solid tumor model at single-cell resolution

Samantha D. Praktiknjo (), Benedikt Obermayer, Qionghua Zhu, Liang Fang, Haiyue Liu, Hazel Quinn, Marlon Stoeckius, Christine Kocks, Walter Birchmeier () and Nikolaus Rajewsky ()
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Samantha D. Praktiknjo: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Benedikt Obermayer: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Qionghua Zhu: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Liang Fang: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Haiyue Liu: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Hazel Quinn: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Marlon Stoeckius: New York Genome Center
Christine Kocks: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Walter Birchmeier: Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Nikolaus Rajewsky: Max Delbrück Center for Molecular Medicine in the Helmholtz Association

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Characterizing the complex composition of solid tumors is fundamental for understanding tumor initiation, progression and metastasis. While patient-derived samples provide valuable insight, they are heterogeneous on multiple molecular levels, and often originate from advanced tumor stages. Here, we use single-cell transcriptome and epitope profiling together with pathway and lineage analyses to study tumorigenesis from a developmental perspective in a mouse model of salivary gland squamous cell carcinoma. We provide a comprehensive cell atlas and characterize tumor-specific cells. We find that these cells are connected along a reproducible developmental trajectory: initiated in basal cells exhibiting an epithelial-to-mesenchymal transition signature, tumorigenesis proceeds through Wnt-differential cancer stem cell-like subpopulations before differentiating into luminal-like cells. Our work provides unbiased insights into tumor-specific cellular identities in a whole tissue environment, and emphasizes the power of using defined genetic model systems.

Date: 2020
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DOI: 10.1038/s41467-020-14777-0

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