Spatial proteomics in precision medicine: technologies, bioinformatics, and translational applications
Yiwen Li1, Yusheng Zhang1, Ying Zhang1
1Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Precision Clinical Medicine
|February 6, 2026
Summary
Spatial proteomics reveals protein function based on location and interactions. Advances in technology and computation enable precise analysis for clinical applications like cancer and neurodegeneration.
Area of Science:
- Proteomics
- Cell Biology
- Biochemistry
Background:
- Protein function is determined by spatial context, including localization and interactions.
- Conventional bulk proteomics lacks the resolution and contextual information of spatial proteomics.
- Understanding protein behavior in situ is crucial for biological insights.
Purpose of the Study:
- To review advances in spatial proteomics technologies and computational methods.
- To highlight the clinical applications of spatial proteomics.
- To discuss future directions for spatial proteomics.
Main Methods:
- DNA-barcoded multiplexing
- Cyclic fluorescence platforms
- Mass spectrometry imaging
- Graph neural networks
- Self-supervised embeddings
- Workflow management tools
Main Results:
- Technological advancements have increased multiplexing capacity, sensitivity, and spatial accuracy.
- Computational tools enhance cell segmentation, noise reduction, and multi-modal data integration.
- Spatial proteomics supports analysis of tumor microenvironments, neurodegeneration, and tissue repair.
Conclusions:
- Spatial proteomics offers superior resolution and contextual information compared to bulk methods.
- It has significant potential in clinical diagnostics and targeted therapies.
- Standardization and 3D mapping are key future research areas.
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