bioRxivJClub
Defining transcriptomic niches in human fibrotic lung with multi-sample spatial transcriptomics analysis using the MAPLE algorithm
bioRxiv · · Preprint · Open access
Jeon, Allen + 14 more
Abstract ↗AI summary
The abstract is read at the publisher; the summary is JClub's.
Multi-sample spatial transcriptomics reveals distinct regional fibrotic programs and cellular niches in human IPF, with 10X Xenium validation confirming key findings.
- Why it matters: Understanding the spatial organization of cell states and fibrotic processes in IPF is crucial for developing targeted therapies, but the spatial context of cellular heterogeneity remains poorly characterized.
- What they did: A comprehensive pipeline utilizing the MAPLE algorithm was developed to analyze multi-sample lung spatial transcriptomics data, identifying cell-spot subpopulations and spatial biomarkers across clinical regions, validated with 10X Xenium ST data.
- The result: Findings show epithelial-to-mesenchymal transitions and region-specific fibrosis, including extracellular matrix changes in upper lobes and immune niches in lower lobes, with senescent cells colocalizing with aberrant niches, advancing understanding of IPF pathology.
The findingWhy it mattersWhat they didThe result
- Open access
- 20 cites