Spatially defined multicellular functional units in colorectal cancer revealed from single cell and spatial transcriptomics

Inbal Avraham‐Davidi(Broad Institute), Simon Mages(Broad Institute), Johanna Klughammer(Broad Institute), Noa Moriel(Hebrew University of Jerusalem), Shinya Imada(Koch Institute for Integrative Cancer Research At MIT), Matan Hofree(Broad Institute), Evan Murray(Broad Institute), Jonathan Chen(Broad Institute), Karin Pelka(Broad Institute), Arnav Mehta(Broad Institute), Genevieve M. Boland(Broad Institute), Toni Delorey(Broad Institute), Leah Caplan(Broad Institute), Danielle Dionne(Broad Institute), Ralf Strasser(Ludwig-Maximilians-Universität München), Jana Laláková(Immune Therapy Holdings (Sweden)), Anezka Niesnerova(Immune Therapy Holdings (Sweden)), Hao Xu(Immune Therapy Holdings (Sweden)), Morgane Rouault(Immune Therapy Holdings (Sweden)), Itay Tirosh(Weizmann Institute of Science), Nir Hacohen(Broad Institute), Fei Chen(Broad Institute), Ömer Yılmaz(Massachusetts General Hospital), Jatin Roper(Duke University), Orit Rozenblatt‐Rosen(Broad Institute), Mor Nitzan(Hebrew University of Jerusalem), Aviv Regev(Broad Institute)
bioRxiv (Cold Spring Harbor Laboratory)
October 2, 2022
Cited by 16Open Access
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Abstract

Abstract While advances in single cell genomics have helped to chart the cellular components of tumor ecosystems, it has been more challenging to characterize their specific spatial organization and functional interactions. Here, we combine single cell RNA-seq, spatial transcriptomics by Slide-seq, and in situ multiplex RNA analysis, to create a detailed spatial map of healthy and dysplastic colon cellular ecosystems and their association with disease progression. We profiled inducible genetic CRC mouse models that recapitulate key features of human CRC, assigned cell types and epithelial expression programs to spatial tissue locations in tumors, and computationally used them to identify the regional features spanning different cells in the same spatial niche. We find that tumors were organized in cellular neighborhoods, each with a distinct composition of cell subtypes, expression programs, and local cellular interactions. Comparing to scRNA-seq and Slide-seq data from human CRC, we find that both cell composition and layout features were conserved between the species, with mouse neighborhoods correlating with malignancy and clinical outcome in human patient tumors, highlighting the relevance of our findings to human disease. Our work offers a comprehensive framework that is applicable across various tissues, tumors, and disease conditions, with tools for the extrapolation of findings from experimental mouse models to human diseases.


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