ArticleRespiratory research2025
Spatial transcriptomic and morpho-functional information derived from single mouse FFPE slides allows in-depth fingerprinting of lung fibrosis.
Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Enhancing RNA Capture Efficiency in Spatial Transcriptomics: A Review of Innovative Technologies and Strategies.International journal of molecular sciences · 2025Pooled it
- Multidimensional lung imaging: integrated preclinical platforms enabling the identification of translational biomarkers for pulmonary research.Respiratory research · 2026Review
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11 authors.
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Abstract
backgroundTranscriptome profiling by RNA sequencing (RNAseq) can provide insightful information on the molecular processes underlying disease development and progression. Although fresh tissue represents the preferred source material for RNAseq, here, we investigated the feasibility of applying RNAseq analysis to single 10 μm thick formalin-fixed and paraffin-embedded (FFPE) lung slides from the lungs of control and bleomycin (BLM)-treated mice. This approach aims at providing spatial-oriented transcriptomic data, that can be integrated with in vivo and ex vivo readouts obtained on the same sample, as a way to enhance the mechanistic information and biomarker/target discovery potential of preclinical models of fibrotic lung diseases.
methodsRNAseq analysis was conducted on individual FFPE slides from the lungs of both controls and BLM-treated mice. The results were initially validated by comparison with publicly available bulk data from fresh-frozen (FF) mouse tissues, both untreated and BLM-treated, as well as human idiopathic pulmonary fibrosis (IPF) biopsies. Unsupervised cluster analysis was performed on Differentially Expressed Genes (DEGs) distinguishing untreated and BLM-treated fibrotic lung samples. For each sample, Pearson correlation analysis was used to compare expression levels of individual gene clusters with Ashcroft Scores and aeration compartments quantitatively assessed on the matched 2D micro-CT coronal slice.
resultsOver 90% of annotated genes within the FFPE dataset were shared with gene signatures retrieved from FF bulk datasets. Differentially modulated gene clusters were mainly found to be associated with extracellular matrix (ECM) organization, tissue remodeling, and inflammatory response pathways. For each sample, expression levels of individual gene clusters were highly correlated with 2D histology readouts and aeration compartments determined on matched 2D coronal slices by micro-CT imaging.
conclusionsFFPE lung tissue represents a valuable alternative to fresh tissue for RNAseq analysis, allowing to achieve a more precise, spatially oriented picture of pulmonary disease development. This approach is thus instrumental to a better characterization of the molecular changes associated to each sample. It can also contribute to a more informed interpretation of histology and micro-CT imaging data, paving the way to the identification of translationally relevant biomarkers as well as novel candidate targets for the development of more effective therapeutic interventions.
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