中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 上海药物研究所
  3. 中国科学院上海药物研究所
Integrating cross-sample and cross-modal data for spatial transcriptomics and metabolomics with SpatialMETA

文献类型：期刊论文

作者Tian, Ruonan10,11; Xue, Ziwei9,10,11; Chen, Yiru9,10; Qi, Yicheng9,10; Zhang, Jian6,7,8; Yuan, Jie5; Ruan, Dengfeng4; Lin, Junxin3; Liu, Jia5; Wang, Di7,8
刊名NATURE COMMUNICATIONS
出版日期2025-10-06
卷号16期号:1页码:16
DOI10.1038/s41467-025-63915-z
通讯作者Liu, Wanlu(wanluliu@intl.zju.edu.cn)
英文摘要Simultaneous profiling of spatial transcriptomics (ST) and spatial metabolomics (SM) on the same or adjacent tissue sections offers a revolutionary approach to decode tissue microenvironment and identify potential therapeutic targets for cancer immunotherapy. Unlike other spatial omics, cross-modal integration of ST and SM data is challenging due to differences in feature distributions of transcript counts and metabolite intensities, and inherent disparities in spatial morphology and resolution. Furthermore, cross-sample integration is essential for capturing spatial consensus and heterogeneous patterns but is often complicated by batch effects. Here, we introduce SpatialMETA, a conditional variational autoencoder (CVAE)-based framework for cross-modal and cross-sample integration of ST and SM data. SpatialMETA employs tailored decoders and loss functions to enhance modality fusion, batch effect correction and biological conservation, enabling interpretable integration of spatially correlated ST-SM patterns and downstream analysis. SpatialMETA identifies immune spatial clusters with distinct metabolic features in cancer, revealing insights that extend beyond the original study. Compared to existing tools, SpatialMETA demonstrates superior reconstruction capability and fused modality representation, accurately capturing ST and SM feature distributions. In summary, SpatialMETA offers a powerful platform for advancing spatial multi-omics research and refining the understanding of metabolic heterogeneity within the tissue microenvironment.
WOS关键词ENDOTHELIAL-CELL METABOLISM
资助项目National Natural Science Foundation of China (National Science Foundation of China)[2024YFC3407700] ; National Key R&D Program of China[32400741] ; National Natural Science Foundation of China ; ZJU-YST joint research center for fundamental science ; State Key Laboratory (SKL) of Biobased Transportation Fuel Technology
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:001589217000016
出版者NATURE PORTFOLIO
源URL[http://119.78.100.183/handle/2S10ELR8/319675]  
专题中国科学院上海药物研究所
通讯作者Liu, Wanlu
作者单位1.Zhejiang Key Lab Med Imaging Artificial Intelligen, Haining, Peoples R China
2.Shanghai Jiao Tong Univ, Shanghai Inst Immunol, Sch Med, Shanghai, Peoples R China
3.Taizhou Univ, Sch Med, Taizhou, Zhejiang, Peoples R China
4.Zhejiang Univ, Affiliated Hosp 2, Sch Med, Dept Sports Med & Orthoped Surg, Hangzhou, Zhejiang, Peoples R China
5.Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai, Peoples R China
6.Zhejiang Univ, Med Ctr, Liangzhu Lab, Hangzhou, Peoples R China
7.Zhejiang Univ, Inst Immunol, Sch Med, Hangzhou, Peoples R China
8.Zhejiang Univ, Sir Run Run Shaw Hosp, Sch Med, Hangzhou, Peoples R China
9.Univ Edinburgh, Coll Med & Vet Med, Biomed Sci, Edinburgh, Scotland
10.Zhejiang Univ, Zhejiang Univ Univ Edinburgh Inst, Ctr Biomed Syst & Informat, Sch Med, Haining, Peoples R China
推荐引用方式
GB/T 7714		 Tian, Ruonan,Xue, Ziwei,Chen, Yiru,et al. Integrating cross-sample and cross-modal data for spatial transcriptomics and metabolomics with SpatialMETA[J]. NATURE COMMUNICATIONS,2025,16(1):16.
APA Tian, Ruonan.,Xue, Ziwei.,Chen, Yiru.,Qi, Yicheng.,Zhang, Jian.,...&Liu, Wanlu.(2025).Integrating cross-sample and cross-modal data for spatial transcriptomics and metabolomics with SpatialMETA.NATURE COMMUNICATIONS,16(1),16.
MLA Tian, Ruonan,et al."Integrating cross-sample and cross-modal data for spatial transcriptomics and metabolomics with SpatialMETA".NATURE COMMUNICATIONS 16.1(2025):16.

入库方式： OAI收割

来源：上海药物研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。