Daily Respiratory Research Analysis

Lung cancer bone metastasis presents a major clinical challenge due to therapeutic resistance and severe morbidity. Although disrupting tumor-bone microenvironment crosstalk is a promising strategy, clinically actionable targets remain limited. Here, by analyzing bulk RNA sequencing data from bone metastatic tumors across multiple cancer types, we identified PARP10 as a gene consistently upregulated in bone metastases. High PARP10 expression in primary tumors was correlated with poor patient survival. Functional studies demonstrated that PARP10 promoted lung cancer growth and bone metastasis both in vitro and in vivo. Mechanistically, multi-omics integrated analyses revealed that PARP10 deletion induced DNA damage and oxidative stress, and upregulated BCAT2 expression in a MYC-dependent manner to enhance BCAA catabolism. This metabolism exerts an adaptive compensatory effect on tumor cells via boosting mitochondrial oxidative phosphorylation, yet depletes bone microenvironmental BCAA and consequently suppresses osteoclast differentiation, thereby inhibiting bone metastasis. Importantly, pharmacological inhibition of PARP10 with OUL232 mitigated bone metastatic burden in mice without observable toxicity, demonstrating its therapeutic potential by concurrently inducing tumor cell apoptosis and disrupting the pro-metastatic niche. Our findings establish PARP10 as a central regulator of a targetable metabolic competition axis and propose its inhibition as a dual-mechanism strategy that simultaneously attacks tumor cells and disrupts the pro-metastatic niche.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by persistent epithelial injury accompanied by mitochondrial dysfunction. Although mesenchymal stem cells (MSCs) can restore epithelial function by donating mitochondria to damaged cells, the molecular mechanisms driving this process remain unclear. In this study, we demonstrate that caveolin-1 (CAV1) enhances mitochondrial transfer from human umbilical-cord-derived MSCs (hucMSCs) to injured epithelial cells. METHODS: In vitro and in vivo bleomycin-induced models were used to evaluate mitochondrial transfer from hucMSCs to alveolar epithelial cells. Confocal microscopy and intravital lung imaging visualized mitochondrial transfer, while flow cytometry quantified transfer efficiency. Proteomic profiling, mitochondrial functional assays, and lipid analyses were conducted to explore CAV1-associated mechanisms and metabolic outcomes. RESULTS: hucMSC treatment restored mitochondrial membrane potential, ATP production, and epithelial cell viability while reducing reactive oxygen species in injured MLE-12 cells. Proteomic analysis showed significant upregulation of CAV1 in hucMSCs cocultured with injured epithelial cells. In the same dataset, differentially expressed proteins were enriched in pathways related to cytoskeletal remodeling and vesicular transport, supporting a role for hucMSC membrane and trafficking dynamics in mitochondrial delivery. Functional validation confirmed that CAV1 overexpression markedly enhanced mitochondrial transfer and restored mitochondrial function, whereas CAV1 knockdown impaired both transfer efficiency and therapeutic outcomes. Mechanistically, transferred mitochondria promoted mitochondria-lipid droplet tethering, boosted fatty acid β-oxidation, and reduced lipid accumulation. CAV1-overexpressing hucMSCs alleviated alveolar epithelial injury and attenuated pulmonary fibrosis. CONCLUSIONS: Our findings identify CAV1 as a crucial mediator of hucMSC-mediated mitochondrial transfer, which enhances epithelial repair through mitochondrial donation and metabolic reprogramming. These insights provide a mechanistic foundation for optimizing stem cell-based therapies in pulmonary fibrosis.

BACKGROUND: Asthma is a clinically heterogeneous airway disorder characterized by complex interactions between environmental exposures, immune activation, and molecular regulatory programs, whose underlying mechanisms are not fully elucidated by known genetic loci. DNA methylation serves as a mechanistic interface bridging genetic predisposition and environmental influences; however, most epigenetic studies remain confined to isolated CpG sites, lacking robust biological interpretability. METHODS: We developed a cross-tissue, multi-cohort, and mechanistically interpretable epigenetic framework to delineate pathway-level methylation mechanisms underlying asthma. Leveraging data from 908 participants across one combined training cohort and three independent validation cohorts, we constructed a linear support vector classifier based on pathway-derived methylation scores. Additionally, SHapley Additive exPlanations (SHAP) were applied to quantify the contributions of individual pathways. To assess the statistical significance of pathway contributions, one-sample t-tests were performed for each pathway's SHAP values against zero, followed by Benjamini-Hochberg false discovery rate (FDR) correction to obtain adjusted p values. RESULTS: The model exhibited reproducible and cross-tissue performance, achieving area under the curve (AUC) values of 0.792 (95% CI: 0.782-0.799; GSE65163) and 0.980 (95% CI: 0.974-0.990; GSE201872) in two airway epithelial cohorts, and 0.736 (95% CI: 0.690-0.771; GSE104471) in peripheral blood samples. Pathway interpretability analyses identified dominant roles of amino acid metabolism, epithelial and mesodermal developmental programs, metabolic-immune transport pathways, and neuroimmune signalling in shaping asthma-associated methylation patterns. Mediation analyses further revealed that these pathways influence asthma both directly and indirectly via eosinophil activity, epithelial proliferative dynamics, and nitric oxide-linked airway inflammation. Notably, pathways annotated by GO:0061205 and GO:0098727 exerted significant direct effects independent of immune intermediates. CONCLUSIONS: This study describes a pathway-level methylation model designed for biological interpretability that shows associations with both clinical severity and latent molecular heterogeneity. It provides statistical evidence contributing to the understanding of epigenetic, immune, and metabolic signatures in asthma, offering a potential framework warranting further validation for precision respiratory medicine.