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<p>Idiopathic pulmonary fibrosis (IPF) is associated with cigarette smoking, yet the relationship between the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone (NNK) and IPF-associated lung transcriptional remodeling remains incompletely understood. Here, we developed an exposure-informed computational framework integrating multi-database target prediction, lung single-cell and single-nucleus transcriptomic analysis, co-expression network analysis, bulk lung cohort projection, and exploratory structure-based modeling. Putative human protein targets of NNK were predicted from ChEMBL, PharmMapper, and SwissTargetPrediction, yielding 2,505 nonredundant targets. These targets were intersected with IPF-associated intramodular hub genes identified from cell type-specific weighted gene co-expression network analysis, defining a focused 42-gene ExposureA-core gene set. Projected ExposureA-core scores showed the clearest IPF-control differences in endothelial and epithelial pseudo-bulk profiles. Functional annotation of the training-derived epithelial ExposureA-core Top30 signature highlighted MAPK and p38 MAPK signaling, PI3K-AKT signaling, angiogenesis or vasculature regulation, cell–substrate adhesion, and membrane-, adhesion-, and cytoskeleton-related cellular components, suggesting remodeling- and adhesion-related epithelial transcriptional features in IPF. The fixed epithelial ExposureA-core Top30 signature remained detectable in independent bulk lung transcriptomic cohorts without gene re-selection, coefficient fitting, or score optimization, with exploratory ROC analyses showing apparent IPF-control separation in GSE110147 and GSE92592. Exploratory docking and 100-ns molecular dynamics simulations of selected epithelial Top30-encoded candidates showed that modeled ECE1–NNK, MMP7–NNK, and TGM2–NNK complexes reached dynamic equilibrium, with relatively stable RMSD, radius of gyration, solvent-accessible surface area, residue-level fluctuation, and low-energy conformational states, supporting their structural plausibility as candidate modeled complexes. Overall, this study defines a focused exposure-informed IPF-associated transcriptional framework and prioritizes epithelial remodeling-related candidate features for future experimental validation. These findings support hypothesis-generating computational prioritization rather than direct evidence that NNK drives IPF pathogenesis.</p>

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Exposure-informed lung transcriptomic analysis links predicted NNK targets to cell type-specific remodeling programs in idiopathic pulmonary fibrosis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Kairui Meng,
  • Lu Wang,
  • Xueqing Gong,
  • Wenjun Tang,
  • Guobing Jia,
  • Yanmei Wang,
  • Chengshi He

摘要

Idiopathic pulmonary fibrosis (IPF) is associated with cigarette smoking, yet the relationship between the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone (NNK) and IPF-associated lung transcriptional remodeling remains incompletely understood. Here, we developed an exposure-informed computational framework integrating multi-database target prediction, lung single-cell and single-nucleus transcriptomic analysis, co-expression network analysis, bulk lung cohort projection, and exploratory structure-based modeling. Putative human protein targets of NNK were predicted from ChEMBL, PharmMapper, and SwissTargetPrediction, yielding 2,505 nonredundant targets. These targets were intersected with IPF-associated intramodular hub genes identified from cell type-specific weighted gene co-expression network analysis, defining a focused 42-gene ExposureA-core gene set. Projected ExposureA-core scores showed the clearest IPF-control differences in endothelial and epithelial pseudo-bulk profiles. Functional annotation of the training-derived epithelial ExposureA-core Top30 signature highlighted MAPK and p38 MAPK signaling, PI3K-AKT signaling, angiogenesis or vasculature regulation, cell–substrate adhesion, and membrane-, adhesion-, and cytoskeleton-related cellular components, suggesting remodeling- and adhesion-related epithelial transcriptional features in IPF. The fixed epithelial ExposureA-core Top30 signature remained detectable in independent bulk lung transcriptomic cohorts without gene re-selection, coefficient fitting, or score optimization, with exploratory ROC analyses showing apparent IPF-control separation in GSE110147 and GSE92592. Exploratory docking and 100-ns molecular dynamics simulations of selected epithelial Top30-encoded candidates showed that modeled ECE1–NNK, MMP7–NNK, and TGM2–NNK complexes reached dynamic equilibrium, with relatively stable RMSD, radius of gyration, solvent-accessible surface area, residue-level fluctuation, and low-energy conformational states, supporting their structural plausibility as candidate modeled complexes. Overall, this study defines a focused exposure-informed IPF-associated transcriptional framework and prioritizes epithelial remodeling-related candidate features for future experimental validation. These findings support hypothesis-generating computational prioritization rather than direct evidence that NNK drives IPF pathogenesis.