Abstract Rationale Silica dust-induced pulmonary fibrosis is the most common occupational lung disease worldwide, and despite efforts at prevention is on the rise. While substantial progress has been made in studying animal models of silicosis, a detailed molecular understanding of the disease in humans remains lacking. Here, we combine single-nuclei mRNA sequencing (snRNA-Seq) and spatial transcriptomics to identify the molecular and cellular networks underlying human end-stage silicosis. Methods 53 FFPE lung samples were obtained from 27 explant end-stage fibrotic silicosis patients, who were exposed to artificial silica dust, 6 IPF samples, and 4 healthy controls. snRNA sequencing was performed on 8 silica samples, 2 controls, and 2 IPF samples using 10x Genomics Flex technology. For Spatial transcriptomics, a tissue microarray with 24 different samples of ∅2mm each was constructed (14 Silica samples, 6 IPFs, and 4 controls). Then we performed a spatial transcriptomics analysis using the 10x Genomics Spatial Xenium imager. Data analysis was conducted in R using the Seurat package. Results We detected 39,226 genes encompassing all main compartments of the lung. After subsetting the data, we focused on immune cells (n = 4,984) and identified several distinct profibrotic macrophage phenotypes, including osteoclast-like macrophages and ChIT1 macrophages. Utilizing Spatial technology, we observed up to 480 genes per field of view. Integrating all samples enabled us to identify the primary lung compartments, including airways, capillaries, endothelium, alveoli, and immune cells. Notably, we observed significant changes in cellular and gene expression patterns in silicosis-affected lungs. We found that different macrophage phenotypes (Figure 1i) were associated with the stage of granuloma and fibrotic progression within the tissue(Figure 1ii). Conclusions The findings from our snRNA Seq analysis and spatial transcriptomics provide the first in-depth molecular and cellular profile of fibrotic silicosis, which reveal distinct profibrotic macrophage phenotypes spatially associated with disease progression. This abstract is funded by: None
Hussein et al. (2026) studied this question.