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Spatially-resolved gene expression patterns of fibrosing ILDs [RNA-Seq]

GSE255173 Homo sapiens Expression profiling by high throughput sequencing 7 samples Submitted 2024/09/30 Platform GPL24676
Summary
Fibrosing interstitial lung diseases (ILDs) encompass a diverse range of scarring disorders that lead to progressive lung failure. Previous gene expression profiling studies focused on idiopathic pulmonary fibrosis (IPF) and bulk tissue samples. We employed digital spatial profiling to gain new insights into the spatial resolution of gene expression across distinct lung microenvironments (LMEs) in IPF, chronic hypersensitivity pneumonitis (CHP) and non-specific interstitial pneumonia (NSIP). We identified differentially expressed genes between LMEs within each condition, and across histologically similar regions between conditions. Uninvolved areas in IPF and CHP were remarkably distinct from normal controls, and displayed potential therapeutic targets. Hallmarks LMEs of each condition retained a distinct gene signature, but these could not be reproduced in matched lung tissue samples. Based on these gene expression signatures and unsupervised clustering, we grouped previously unclassified ILD cases into NSIP or CHP. Lastly, we characterized a gene expression pattern associated with poor outcome . Overall, our work uniquely dissects gene expression profiles between LMEs within and across different types of fibrosing ILDs. This new spatial transcriptomics approach has the potential to reclassify unclassifiable cases, to qualify the transcriptional relevance of smaller biopsies for clinical use, and to predict outcome at the time of diagnosis.
Published in
Spatially resolved gene expression profiles of fibrosing interstitial lung diseases
Kim SJ, Cecchini MJ, Woo E et al. · Scientific reports 2024 · PMID 39488596 · doi:10.1038/s41598-024-77469-5
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Direct links to NCBI, no account and no request form: the whole study as GSE255173_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 7 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1073897 and SRA study SRP488468. Searching any of these in the dataset finder brings you back here.

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