Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis
Nature Communications(2023)
Abstract
Although advances in spatial transcriptomics (ST) enlarge to unveil spatial landscape of tissues, it remains challenging to delineate pathology-relevant and cellular localizations, and interactions exclusive to a spatial niche (e.g., tumor boundary). Here, we develop Cottrazm, integrating ST with hematoxylin and eosin histological image, and single-cell transcriptomics to delineate the tumor boundary connecting malignant and non-malignant cell spots in tumor tissues, deconvolute cell-type composition at spatial location, and reconstruct cell type-specific gene expression profiles at sub-spot level. We validate the performance of Cottrazm along the malignant-boundary-nonmalignant spatial axis. We identify specific macrophage and fibroblast subtypes localized around tumor boundary that interacted with tumor cells to generate a structural boundary, which limits T cell infiltration and promotes immune exclusion in tumor microenvironment. In this work, Cottrazm provides an integrated tool framework to dissect the tumor spatial microenvironment and facilitates the discovery of functional biological insights, thereby identifying therapeutic targets in oncologic ST datasets. Delineating the cellular composition of tumour boundaries in spatial transcriptomics (ST) data is challenging. Here, the authors develop Cottrazm to integrate ST with histological imaging and single-cell data, identify the malignant and non-malignant tissue boundaries, deconvolute cell-type composition, and reconstruct cell type-specific gene expression profiles.
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Key words
Cancer genomics,Cancer microenvironment,Computational models,Transcriptomics,Science,Humanities and Social Sciences,multidisciplinary
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