Combining spatial transcriptomics and ECM imaging in 3D for mapping cellular interactions the tumor microenvironment
Year: 2024
Type: peer-review
Abstract: !!The data can be interactively explored at https://lung-3d-browser.mdc-berlin.de!! Tumor are complex ecosystems composed by malignant and non-malignant cells embedded in a dynamic extracellular matrix (ECM). In the tumor microenvironment, molecular phenotypes are controlled by cell-cell and ECM interactions in 3D cellular neighborhoods (CN). While their inhibition can impede tumor progression, routine molecular tumor profiling fails to capture cellular interactions. Single-cell spatial transcriptomics (ST) enables receptor-ligand interaction mapping but usually remains limited to 2D tissue sections and lacks ECM readouts. Here, we integrate 3D ST with ECM imaging in serial sections from one clinical lung carcinoma to systematically quantify molecular states, cell-cell interactions, and ECM remodeling in CN. Our integrative analysis pinpointed known immune escape and tumor invasion mechanisms, revealing several druggable drivers of tumor progression in the patient under study. This proof-of-principle study highlights the potential of deep CN profiling in routine clinical samples to inform microenvironment-directed therapies.
Authors: Tancredi Massimo Pentimalli, Simon Schallenberg, Daniel León-Periñán, Ivano Legnini, Ilan Theurillat, Gwendolin Thomas, Anastasiya Boltengagen, Sonja Fritzsche, Jose Nimo, Lukas Ruff, Gabriel Dernbach, Philipp Jurmeister, Sarah Murphy, Mark T. Gregory, Yan Liang, Michelangelo Cordenonsi, Stefano Piccolo, Fabian Coscia, Andrew Woehler, Nikos Karaiskos, Frederick Klauschen, Nikolaus Rajewsky
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6969356439
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