High-resolution molecular atlas of a lung tumor in 3D
TM Pentimalli, S Schallenberg, D León-Periñán… - BioRxiv, 2023 - biorxiv.org
TM Pentimalli, S Schallenberg, D León-Periñán, I Legnini, I Theurillat, G Thomas…
BioRxiv, 2023•biorxiv.orgCells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology
and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial
atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ
quantification of 960 cancer-related genes across∼ 340,000 cells with measurements of
tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor
microenvironment into tumor, stromal, and immune multicellular niches. Interestingly …
and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial
atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ
quantification of 960 cancer-related genes across∼ 340,000 cells with measurements of
tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor
microenvironment into tumor, stromal, and immune multicellular niches. Interestingly …
Abstract
Cells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ quantification of 960 cancer-related genes across ∼340,000 cells with measurements of tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor microenvironment into tumor, stromal, and immune multicellular niches. Interestingly, pseudotime analysis suggested that pro-invasive epithelial-to-mesenchymal transition (EMT), detected in stroma-infiltrating tumor cells, already occurred in one region at the tumor surface. There, myofibroblasts and macrophages specifically co-localized with pre-invasive tumor cells and their multicellular molecular signature identified patients with shorter survival. Moreover, cytotoxic T-cells did not infiltrate this niche but colocalized with inhibitory dendritic and regulatory T cells. Importantly, systematic scoring of cell-cell interactions in 3D neighborhoods highlighted niche-specific signaling networks accompanying tumor invasion and immune escape. Compared to 2D, 3D neighborhoods improved the characterization of immune niches by identifying dendritic niches, capturing the 3D extension of T-cell niches and boosting the quantification of niche-specific cell-cell interactions, including druggable immune checkpoints. We believe that 3D communication analyses can improve the design of clinical studies investigating personalized, combination immuno-oncology therapies.
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