Abstract

The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high‐throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi‐modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

Details

Title
Spatial omics: Navigating to the golden era of cancer research
Author
Wu, Yingcheng 1   VIAFID ORCID Logo  ; Cheng, Yifei 2 ; Wang, Xiangdong 3   VIAFID ORCID Logo  ; Fan, Jia 4 ; Gao, Qiang 5   VIAFID ORCID Logo 

 Center for Tumor Diagnosis & Therapy and Department of Cancer Center, Jinshan Hospital and Jinshan Branch of Zhongshan Hospital, Zhongshan Hospital, Fudan University, Shanghai, China, Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China 
 Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China 
 Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital Institute for Clinical Science, Shanghai Institute of Clinical Bioinformatics, Shanghai Engineering Research for AI Technology for Cardiopulmonary Diseases, Jinshan Hospital Centre for Tumor Diagnosis and Therapy, Fudan University Shanghai Medical College, Shanghai, China 
 Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China, State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China 
 Center for Tumor Diagnosis & Therapy and Department of Cancer Center, Jinshan Hospital and Jinshan Branch of Zhongshan Hospital, Zhongshan Hospital, Fudan University, Shanghai, China, Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China, State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, China 
Section
REVIEWS
Publication year
2022
Publication date
Jan 1, 2022
Publisher
John Wiley & Sons, Inc.
e-ISSN
20011326
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2760822687
Copyright
© 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.