Spatially resolved deconvolution of the fibrotic niche in lung fibrosis

A defining pathological feature of human lung fibrosis is localized tissue heterogeneity, which challenges the interpretation of transcriptomic studies that typically lose spatial information. Here we investigate spatial gene expression in diagnostic tissue using digital profiling technology. We identify distinct, region-specific gene expression signatures as well as shared gene signatures. By integration with single-cell data, we spatially map the cellular composition within and distant from the fibrotic niche, demonstrating discrete changes in homeostatic and pathologic cell populations even in morphologically preserved lung, while through ligand-receptor analysis, we investigate cellular cross-talk within the fibrotic niche. We confirm findings through bioinformatic, tissue, and in vitro analyses, identifying that loss of NFKB inhibitorzeta in alveolar epithelial cells dysregulates the TGF beta/IL-6 signaling axis, which may impair homeostatic responses to environmental stress. Thus, spatially resolved deconvolution advances understanding of cell composition and microenvironment in human lung fibrogenesis.

Automated summary

This study investigates spatial gene expression in human lung fibrosis using digital profiling technology and identifies distinct gene expression signatures in different regions. Through integration with single-cell data, the study maps the cellular composition and cellular cross-talk within the fibrotic niche. The findings reveal cell dysregulation and impaired response to environmental stress in fibrotic lung.