Dissecting Lung Spatial-Biological Niches in Early Fibrogenesis

Stanford University, Stanford CA

Investigators

Abstract

PROJECT SUMMARY Interstitial lung diseases (ILDs) represent a global clinical burden that affects >5,000,000 people. Commonly, ILDs have no clinically determinable cause and are diagnosed as idiopathic pulmonary fibrosis (IPF), which presents a median survival time of only 2-4 years after diagnosis. Given the unclear pathogenesis of many ILDs, there is a strong clinical need to elucidate biological mechanisms that contribute to their onset and progression. Interestingly, ILDs often exhibit a heterogeneous distribution of (1) healthy tissue regions, (2) early-fibrogenic foci, and (3) mature-fibrotic tissue, each of which presents a unique cellular/biochemical milieu, tissue architecture, and response to therapy. Traditional biological analyses of ILDs, including single-cell RNA sequencing (scRNA-seq) and other omic-scale methods, have mostly generated composite molecular profiles, which may mask important distinctions between foci such that pathological vs. ameliorative states cannot be directly inferred. This project aims to disaggregate early-fibrogenic microenvironments in an ILD-specific manner, uncovering highly resolved cellular/molecular drivers specific to early scar progression. Further, therapeutic testing for ILDs has similarly centered on (1) in vitro models devoid of spatial-biological context and/or (2) bulk treatment of murine lungs, which may obscure intra-tissue variability in the effects of treatment based on local niche. The overarching goals of this proposal are therefore to spatially profile and recapitulate disease/foci- specific “neighborhoods” that specifically drive early fibrogenesis using spatial biology and biomaterial modeling. Overall, this project seeks to shift current paradigms by utilizing spatial-biological data as an anatomical “blueprint” for disease- and niche-specific modeling of early fibrogenesis, enabling unprecedented detail in dissecting the contributions of in situ tissue context to the initiation of scarring across multiple ILDs. Specialized fibroblast phenotypes play a critical role in the fibrosis of all major organs. Based on prior studies, I hypothesize that fibroblast-centered neighborhoods differentiate healthy vs. early-fibrogenic vs. mature-fibrotic tissue regions across human ILDs. Specific Aim 1 will profile ILD-specific foci by integrating (1) machine learning (ML)-based tissue architecture analysis with (2) high-plex immunofluorescence. Specific Aim 2 will recapitulate fibrogenic cell-matrix interactions by using light-catalyzed bioconjugation chemistry to generate user-defined extracellular protein patterning in two model systems. Specific Aim 3 will dissect fibrogenic cellular crosstalk by using 3D bioprinting to recapitulate niche-associated cell-cell interactions (i.e. endothelial cells with specialized fibroblasts). Ultimately, this project will integrate ML, spatial biology, and biomaterials modeling to elucidate the roles of localized biological niches to the onset of scarring across ILDs.