A Human iPSC-Based Lung Organoid with Stromal and Macrophage Components for Pulmonary Fibrosis Modelling and Pharmacological Response Assessment

Abstract Background Pulmonary fibrosis (PF) involves epithelial, stromal, and immune responses that are incompletely represented in conventional culture systems. We therefore sought to engineer a reconstructable human multicellular lung organoid model for PF modelling and pharmacological response assessment. Methods The hiLOFM model was assembled by combining human induced pluripotent stem cell-derived lung organoids (hiLOs), human fibroblasts (HFs), and hiPSC-derived macrophages (hiMacs) at a defined starting ratio of 1:2:0.5. Whole-culture responses were evaluated after sequential LPS/TGF-β1 induction, bleomycin (BLM) exposure, and sequential BLM/TGF-β1 treatment. Responses to pirfenidone, nintedanib, and DS-8201 were assessed using morphological, molecular, immunostaining, and cytokine analyses. Results The hiLOFM model exhibited increased myofibroblast activation, extracellular matrix deposition, and inflammatory signalling following co-culture with HFs and LPS/TGF-β1-based induction. Macrophage incorporation differentially modulated selected fibrosis- and inflammation-associated readouts. Passaged hiLOs retained selected pulmonary lineage-associated populations and marker expression, and remained capable of supporting reconstruction of the fibrosis-responsive multicellular model. Beyond the LPS/TGF-β1-based condition, BLM alone or combined with TGF-β1 elicited distinct epithelial, fibrotic, and inflammatory responses. For therapeutic assessment, pirfenidone and nintedanib, alone or in combination, attenuated selected induced responses. For drug-associated pulmonary response assessment, DS-8201 produced concentration- and endpoint-dependent alterations in epithelial, inflammatory, and profibrotic readouts. Conclusions We established a repeatedly reconstructable human multicellular model combining expandable hiPSC-derived lung organoids with defined stromal and macrophage inputs. The platform detected responses to multiple fibrogenic and pharmacological conditions, supporting its application in PF modelling, therapeutic-response assessment, and early detection of drug-associated pulmonary response signals.