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Cinobufotalin Ameliorates the Development of Pulmonary Fibrosis by Suppressing the TGF-β/Smad Pathway via Regulating PI15.

Dong Xia | Xingyan Liu | Qiuting Yang | Jie Li | Li Li | Yong You | Jing Wang | Weiyi Fang | Huiling Yang
Journal of cellular and molecular medicine | 2025

Pulmonary fibrosis (PF) is a common hallmark of several types of interstitial lung diseases (ILDs), for which effective therapeutic drugs are lacking. The small-molecule chemical compound cinobufotalin (CB) has demonstrated significant anti-cancer effects in lung cancer. In this study, we first found that CB attenuated bleomycin (BLM)-induced PF and inhibited transforming growth factor-beta 1 (TGF-β1)-induced myofibroblast activation and epithelial-mesenchymal transition (EMT). Subsequently, comparative RNA sequencing (RNA-Seq) was conducted to analyse the lung gene expression profiles in mice. Interestingly, peptidase inhibitor 15 (PI15) was identified as a significantly differentially expressed gene (DEG) and may be a potential target in PF progression. Mechanistic studies showed that CB exerts anti-PF effects by inhibiting PI15 and thereby regulating the TGF-β/Smad signalling pathway. Our data demonstrated that CB represents a promising anti-PF drug and may be a candidate therapeutic for PF patients.

Pubmed ID: 40845143

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Associated grants

  • Agency: the Science and Technology Program of Guangzhou,
    Id: 202206010068
  • Agency: the Discipline construction project of Guangdong Medical University,
    Id: 4SG23008G
  • Agency: the National Natural Science Foundation of China,
    Id: 82470060
  • Agency: the Open Foundation of NHC Key Laboratory of Tropical Disease Control, Hainan Medical University,
    Id: 2020-PT310-009

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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