Basic & Clinical Medicine ›› 2026, Vol. 46 ›› Issue (2): 155-163.doi: 10.16352/j.issn.1001-6325.2026.02.0155

• Original Articles • Previous Articles     Next Articles

SilicosisOmics: an integrated multi-omics platform for silicosis

WANG Jixin1,2#, HUANG Xinlei1#, QI Xianmei1, ZHANG Tiantian1, PANG Junling1*, LONG Erping1*, WANG Jing1*   

  1. 1. State Key Laboratory of Respiratory Health and Multimorbidity, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing 100005;
    2. School of Basic Medical Sciences, Tsinghua University, Beijing 100084, China
  • Received:2025-11-06 Revised:2025-12-19 Online:2026-02-05 Published:2026-01-21
  • Contact: * pjl_happy@ibms.pumc.edu.cn; erping.long@ibms.pumc.edu.cn; wangjing@ibms.pumc.edu.cn

Abstract: Objective To address the challenges of fragmented multi-omics data and insufficient integrated analysis in silicosis research, we aim to construct a comprehensive data platform that supports systematic analysis of multi-level molecular alterations in fibrotic lung tissues and facilitates rapid identification of therapeutic targets. Methods We systematically integrated transcriptomic, single-cell transcriptomic, quantitative proteomic, post-translational modification-specific proteomic, and metabolomic data from human and mouse silicotic and control lung tissues. By leveraging bioinformatics tools including DESeq2, Seurat, and CellChat, we developed a web-based visualization platform enabling data visualization and interactive analysis. Results We successfully constructed SilicosisOmics (https://respir.pumc.edu.cn/SilicosisOmics/), a comprehensive multi-omics data platform for silicosis research. The platform integrated five types of omics data derived from both silicotic and non-diseased lung tissues across human and mouse species. SilicosisOmics provided not only online search functionality for static visualization of gene expression and single-cell clustering but also interactive analytical tools supporting user-customized analyses including differential gene expression, pathway enrichment, and cell-cell interaction studies. Conclusions The SilicosisOmics platform offers systematic multi-omics data resources and user-friendly analytical tools for silicosis and pulmonary fibrosis research, thereby facilitating the advancement of mechanistic studies, target discovery, and subsequent translational research.

Key words: silicosis, pulmonary fibrosis, multi-omics, data platform, data sharing

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