Spatially resolving cancer: from cell states to therapy

Recent advances in spatial multi-omics technologies and analytical methods are transforming our understanding of how cancer cells and their microenvironments interact to drive critical processes such as lineage plasticity, immune evasion, and therapeutic resistance. By linking cancer cell states, li...

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Bibliographic Details
Published in:Trends in cancer
Main Authors: Pei, Guangsheng, Liu, Yang, Wang, Linghua
Format: Journal Article
Language:English
Published: United States 02.10.2025
Subjects:
cancer cell state
multimodal data integration
computational pathology
machine learning
spatial profiling
spatial multi-omics
ISSN:2405-8025, 2405-8025
Online Access:Get more information
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Summary:Recent advances in spatial multi-omics technologies and analytical methods are transforming our understanding of how cancer cells and their microenvironments interact to drive critical processes such as lineage plasticity, immune evasion, and therapeutic resistance. By linking cancer cell states, lineage plasticity, clonal dynamics, oncogenic pathways, and cellular interactions to their spatial context, these innovations provide deep biological insights and reveal clinically relevant molecular programs and spatial biomarkers. This review highlights key breakthroughs in spatial profiling and computational approaches, including integration with computational pathology, multimodal data, and machine learning to uncover important biological insights. We discuss challenges in spatial multimodal data integration and emerging clinical applications, and we propose a roadmap to accelerate clinical translation and advance precision oncology through spatially resolved, actionable, molecular insights.
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ISSN:2405-8025
2405-8025
DOI:10.1016/j.trecan.2025.09.002