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.