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Targeting fibroblast–endothelial cell interactions in LAM pathogenesis using 3D spheroid models and spatial transcriptomics
Sinem Koc-Gunel, Emily C. Liu, Lalit K. Gautam, Ben A. Calvert, Shubha Murthy, Noa C. Harriott, Janna C. Nawroth, Beiyun Zhou, Vera P. Krymskaya, Amy L. Ryan
Sinem Koc-Gunel, Emily C. Liu, Lalit K. Gautam, Ben A. Calvert, Shubha Murthy, Noa C. Harriott, Janna C. Nawroth, Beiyun Zhou, Vera P. Krymskaya, Amy L. Ryan
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Research Article Cell biology Pulmonology

Targeting fibroblast–endothelial cell interactions in LAM pathogenesis using 3D spheroid models and spatial transcriptomics

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Abstract

Lymphangioleiomyomatosis (LAM) is a progressive lung disease with limited treatments, largely because of an incomplete understanding of its pathogenesis. Lymphatic endothelial cells (LECs) invade LAM cell clusters, which include human melanoma black-45–positive epithelioid cells and smooth muscle α-actin–expressing LAM-associated fibroblasts (LAMFs). Recent evidence shows that LAMFs resemble cancer-associated fibroblasts, with LAMF-LEC interactions contributing to disease progression. To explore these mechanisms, we used spatial transcriptomics on LAM lung tissues and identified a gene cluster enriched in kinase signaling pathways linked to myofibroblasts and coexpressed with LEC markers. Kinase arrays revealed elevated PDGFR and FGFR in LAMFs. Using a 3D coculture spheroid model of primary LAMFs and LECs, we observed increased invasion in LAMF-LEC spheroids compared with non-LAM fibroblasts. Treatment with sorafenib, a multikinase inhibitor, significantly reduced invasion, outperforming rapamycin. We also verified tuberous sclerosis complex 2–deficient renal angiomyolipoma (TSC2-null AML) cells as key VEGF-A secretors; VEGF-A was suppressed by sorafenib in both TSC2-null AML cells and LAMFs. These findings highlight VEGF-A and basic FGF as potential therapeutic targets and suggest multikinase inhibition as a promising strategy for LAM.

Authors

Sinem Koc-Gunel, Emily C. Liu, Lalit K. Gautam, Ben A. Calvert, Shubha Murthy, Noa C. Harriott, Janna C. Nawroth, Beiyun Zhou, Vera P. Krymskaya, Amy L. Ryan

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Figure 4

Spatial transcriptomic analysis of LAM tissue highlights LAM-core regions.

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Spatial transcriptomic analysis of LAM tissue highlights LAM-core region...
(A) UMAP where colors represent distinct cellular clusters categorized by gene expression at individual spatial transcriptomic spots, for the combined dataset from both LAM tissues. (B–D) Spatial localization of well-established LAM genes ACTA2 and VEGFD from LAM_D1 lungs showing LAM nodule localization correlating to high gene expression. (E) Violin plots of LAM-core genes in the combined dataset identifying cluster 4 as the LAM-core. (F) Heatmap for gene expression for the combined dataset where each column represents the color coded cell cluster for all differentially expressed LAM-core–enriched genes with key up- and downregulated genes highlighted. (G) Significant IPA canonical pathways’ enrichment in the LAM-core. Orange represents positive z-scores, and blue represents negative z-scores.

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