Decoding the Lymphangioleiomyomatosis (LAM) Niche Microenvironment <i>via</i> Integrative Analysis of Single Cell Multiomics and Spatial Transcriptomics

Lymphangioleiomyomatosis (LAM) is a rare, destructive lung disease caused by mutations in TSC1 or TSC2, leading to mTORC1 hyperactivation. While mTOR inhibitor sirolimus, the only FDA approved drug for this disease, stabilizes lung function in most LAM patients, the drug does not eliminate LAM cells, underscoring a critical gap in our understanding of the tumor microenvironment and cellular heterogeneity that drive disease progression. This study provides the first comprehensive multiomics atlas of the human LAM niche, integrating single-cell/nucleus RNA-seq, single-nucleus ATAC-seq, and spatial transcriptomics to deconvolute its complex architecture. We elucidate LAM cellular heterogeneity by identifying three distinct subtypes: the canonical, uterine smooth muscle-like, mTORC1-hyperactive LAM CORE1 ; a novel, fibroblast-like LAM CORE2 subtype with potent extracellular matrix (ECM) remodeling activity; and LAM CORE3 , a substate of LAM CORE1 that shares LAM and myogenic signatures but is characterized by a lower transcriptional activity and specific functional enrichment in protein translation. Our analysis reveals the transcriptomic heterogeneity of the LAM subtypes, orchestrated by distinct transcriptional drivers and networks. Furthermore, we uncover spatially resolved LAM-associated fibroblast (LAF) states, LAF-seed and LAF-niche, that orchestrate TGF-β signaling, ECM deposition and remodeling, and niche expansion. Spatial mapping uncovers a structured ecosystem where LAM CORE1 cells form a central core enmeshed with the lymphatic endothelium, which is surrounded by LAFs, LAM CORE2 cells, and reprogrammed immune and epithelial cells. Findings were validated through multimodal imaging technologies. Present work advances the field by providing the first high-resolution blueprint of the LAM niche microenvironment, revealing novel cell states and crosstalk that identify promising therapeutic targets.