Introduction: Fibrotic lung diseases are a major cause of morbidity and mortality whose importance has further increased due to the COVID-19 pandemic. Our understanding of the core determinants underlying the initiation and progression of fibrosis remains limited. To address this gap there is a need to better understand and model the lung fibrosis-specific microenvironment i.e. the fibrotic niche.

Aims and Objectives: To apply spatial transcriptomic approaches to characterise the fibrotic niche, and to then compare identified expression patterns with in vitro modelling approaches to identify models with most disease relevance.

Methods: We spatially profiled the fibrotic niche using GeoMX digital spatial profiling and laser-capture microdissection RNA sequencing, and through integration with single cell data mapped the cellular composition. Focussing upon sites of active fibrogenesis - fibroblastic foci - we then compared 3 primary human cell culture model approaches (a 3D tissue engineered long term model, Scar-in-a-Jar, and standard plasticware culture) at the whole transcriptome level with the spatial transcriptome.

Results: Transcriptomic analysis of the fibrotic niche identified a distinct gene signature within fibroblastic foci with evidence of increased glycolysis, a bone morphogenesis signature and the presence of multiple mesenchymal cell populations including HAS1hi fibroblasts. A human cell based 3D tissue engineered long term model best resembled the transcriptome of fibroblastic foci.

Conclusions: Spatial transcriptomic profiling identifies distinct gene expression profiles within the fibrotic niche which can be used to inform human based cell modelling approaches for mechanistic and therapeutic targeting studies.