Single-cell deconvolution reveals high lineage- and location-dependent heterogeneity in mesenchymal multivisceral stage 4 colorectal cancer
Christopher Berlin, Bernhard Mauerer, Pierre Cauchy, Jost Luenstedt, Roman Sankowski, Lisa Marx, Reinhild Feuerstein, Luisa Schaefer, Florian R. Greten, Marina Pesic, Olaf Groß, Marco Prinz, Naomi Ruehl, Laura Miketiuk, Dominik Jauch, Claudia Laessle, Andreas Jud, Esther A. Biesel, Hannes Neeff, Stefan Fichtner-Feigl, Philipp A. Holzner, Rebecca Kesselring
Christopher Berlin, Bernhard Mauerer, Pierre Cauchy, Jost Luenstedt, Roman Sankowski, Lisa Marx, Reinhild Feuerstein, Luisa Schaefer, Florian R. Greten, Marina Pesic, Olaf Groß, Marco Prinz, Naomi Ruehl, Laura Miketiuk, Dominik Jauch, Claudia Laessle, Andreas Jud, Esther A. Biesel, Hannes Neeff, Stefan Fichtner-Feigl, Philipp A. Holzner, Rebecca Kesselring
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Research Article Cell biology Oncology

Single-cell deconvolution reveals high lineage- and location-dependent heterogeneity in mesenchymal multivisceral stage 4 colorectal cancer

Abstract

Metastasized colorectal cancer (CRC) is associated with a poor prognosis and rapid disease progression. Besides hepatic metastasis, peritoneal carcinomatosis is the major cause of death in Union for International Cancer Control (UICC) stage IV CRC patients. Insights into differential site-specific reconstitution of tumor cells and the corresponding tumor microenvironment are still missing. Here, we analyzed the transcriptome of single cells derived from murine multivisceral CRC and delineated the intermetastatic cellular heterogeneity regarding tumor epithelium, stroma, and immune cells. Interestingly, we found an intercellular site-specific network of cancer-associated fibroblasts and tumor epithelium during peritoneal metastasis as well as an autologous feed-forward loop in cancer stem cells. We furthermore deciphered a metastatic dysfunctional adaptive immunity by a loss of B cell–dependent antigen presentation and consecutive effector T cell exhaustion. Furthermore, we demonstrated major similarities of this murine metastatic CRC model with human disease and — based on the results of our analysis — provided an auspicious site-specific immunomodulatory treatment approach for stage IV CRC by intraperitoneal checkpoint inhibition.

Authors

Christopher Berlin, Bernhard Mauerer, Pierre Cauchy, Jost Luenstedt, Roman Sankowski, Lisa Marx, Reinhild Feuerstein, Luisa Schaefer, Florian R. Greten, Marina Pesic, Olaf Groß, Marco Prinz, Naomi Ruehl, Laura Miketiuk, Dominik Jauch, Claudia Laessle, Andreas Jud, Esther A. Biesel, Hannes Neeff, Stefan Fichtner-Feigl, Philipp A. Holzner, Rebecca Kesselring

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Figure 1

A distinct cellular and functional landscape of murine primary CRC, LM, and PC.

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A distinct cellular and functional landscape of murine primary CRC, LM, ...
(A) Exemplary screenshot during murine laparoscopy after 8 weeks. White dashed lines mark interenteric and abdominal wall peritoneal tumors as well as LMs. (B) Overview of murine metastasized stage IV CRC upon animal sacrifice (left panel). Quantification of location-dependent macroscopic tumor mass as percentages. Locations: PT, LN, LM, PM, and PC (right panel). (C) UMAP plot of 8,094 cells identified by joint application of RCA and CCA and color coded by cell type (upper panel). Proportions of all cell types in PT, LM, and PC (left lower panel) or of the TME (right lower panel) on average are shown. (D) Canonical marker gene expression for multiple cell types centered to the average expression of each gene across all cells. The dot size represents the proportion of expressing cells in each cluster. PE, percentage expressed; AE, average expression. (E) UMAP plot of 5,533 tumor cells identified by joint application of RCA and CCA and color coded by cell subtype (upper panel). Proportions of all cell types in PT, LM, and PC (lower panel) on average are shown. (F) Canonical marker gene expression for epithelial cell subtypes centered to the average expression of each gene across all cells. Dot size represents the proportion of expressing cells in each cluster.