Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by progressive and irreversible scarring of the lung tissue. Development of new efficacious and safe treatments is hampered by limited understanding of disease pathogenesis, lack of predictive preclinical models, and narrow therapeutic index of candidate drugs targeting complex biologies. Here, we tackle these aspects by generating spatially resolved transcriptomic maps of fibrotic lungs from clinical samples and a preclinical mouse model. We utilized the Visium platform to study parenchyma biopsies from four healthy lungs and regions of varying fibrotic severity from four IPF patient lungs. By mapping single cell RNA-seq data spatially, we were able to detect distinct fibroblast populations in different regions of the lesioned IPF lung, as well as the presence of various immune cell populations. To study lung fibrosis preclinically in vivo, the bleomycin mouse model is the most widely used alternative, although its translatability to human disease is disputed. Visium data from mouse lungs collected at two time points following bleomycin administration were generated, which allowed us to characterize the fibrotic lesions and inflammatory areas in their spatiotemporal context. In addition, mass spectrometry imaging was performed on adjacent tissue sections to provide paired spatial metabolomics. Herein, we have generated spatial maps of the lung fibrosis transcriptome from IPF lung biopsies and bleomycin-injured mouse lungs, providing an extensive resource to probe disease pathogenesis and animal model translatability.
Footnotes
Cite this article as Eur Respir J 2022; 60: Suppl. 66, 4609.
This article was presented at the 2022 ERS International Congress, in session “-”.
This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).
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