综合性多组学硅肺病数据平台SilicosisOmics的构建

doi:10.16352/j.issn.1001-6325.2026.02.0155

基础医学与临床 ›› 2026, Vol. 46 ›› Issue (2): 155-163.doi: 10.16352/j.issn.1001-6325.2026.02.0155

综合性多组学硅肺病数据平台SilicosisOmics的构建

王季馨^1,2#, 黄鑫磊^1#, 齐先梅¹, 张田甜¹, 庞军玲^1*, 龙尔平^1*, 王婧^1*

1.中国医学科学院北京协和医学院基础医学研究所呼吸和共病全国重点实验室,北京 100005;
2.清华大学基础医学院,北京 100084

收稿日期:2025-11-06 修回日期:2025-12-19 出版日期:2026-02-05 发布日期:2026-01-21
通讯作者: ^* pjl_happy@ibms.pumc.edu.cn; erping.long@ibms.pumc.edu.cn; wangjing@ibms.pumc.edu.cn
作者简介:^#对本文有同等贡献
基金资助:
癌症、心脑血管、呼吸和代谢性疾病防治研究国家科技重大专项 (2024ZD0528904);国家自然科学基金 (82100080);中国医学科学院医学与健康科技创新工程 (2021-I2M-1-049,2023-I2M-2-001);北京高校卓越青年科学家计划 (BJZQ2024002);全国重点实验室专项基金 (2060204)

SilicosisOmics: an integrated multi-omics platform for silicosis

WANG Jixin^1,2#, HUANG Xinlei^1#, QI Xianmei¹, ZHANG Tiantian¹, PANG Junling^1*, LONG Erping^1*, WANG Jing^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

摘要/Abstract

摘要： 目的解决硅肺研究领域多组学数据分散、整合分析不足的瓶颈,构建一个综合性数据平台,以支持纤维化肺组织中的多层次分子变化的系统解析与治疗靶点的快速挖掘。方法系统整合人类和小鼠硅肺及对照肺组织的转录组、单细胞转录组、定量蛋白质组、修饰特异性蛋白质组和代谢组学数据,集成DESeq2、Seurat、CellChat等生物信息学工具,开发基于Web的可视化分析平台,实现数据可视化和交互分析功能。结果构建了一个综合性的硅肺病多组学数据平台SilicosisOmics (https://respir.pumc.edu.cn/SilicosisOmics/#/)。该数据平台整合了来自硅肺病肺组织以及非病变肺组织的五种类型组学数据,涵盖人类和小鼠两个物种。SilicosisOmics不仅提供在线搜索以静态展示基因表达或单细胞聚类等信息,还提供交互式分析工具,支持用户执行差异基因表达、通路富集和细胞间相互作用等个性化分析。结论 SilicosisOmics平台为硅肺病及肺纤维化研究提供了系统的多组学数据资源与分析工具,有助于推动疾病机制研究、靶点发现及后续转化研究的发展。

关键词: 硅肺病, 肺纤维化, 多组学, 数据平台, 数据共享

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

中图分类号:

Q811.4

王季馨, 黄鑫磊, 齐先梅, 张田甜, 庞军玲, 龙尔平, 王婧. 综合性多组学硅肺病数据平台SilicosisOmics的构建[J]. 基础医学与临床, 2026, 46(2): 155-163.

WANG Jixin, HUANG Xinlei, QI Xianmei, ZHANG Tiantian, PANG Junling, LONG Erping, WANG Jing. SilicosisOmics: an integrated multi-omics platform for silicosis[J]. Basic & Clinical Medicine, 2026, 46(2): 155-163.

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综合性多组学硅肺病数据平台SilicosisOmics的构建

SilicosisOmics: an integrated multi-omics platform for silicosis

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