The Technological Frontiers,Computational Paradigms and Emerging Challenges of Single-cell and Spatial Omics
10.13865/j.cnki.cjbmb.2025.10.0001
- VernacularTitle:单细胞与空间组学的技术前沿、计算范式及新兴挑战
- Author:
Guan-Chuan LIN
1
;
Xing-Hua PAN
Author Information
1. 南方医科大学基础医学院生物化学与分子生物学教研室,广州 510515;广东省单细胞与细胞外囊泡重点实验室,广州 510515
- Publication Type:Journal Article
- Keywords:
single-cell sequencing;
spatial omics;
multi-omics integration;
artificial intelligence(AI);
computational analysis;
tumor microenvironment;
precision medicine
- From:
Chinese Journal of Biochemistry and Molecular Biology
2025;41(11):1559-1565
- CountryChina
- Language:Chinese
-
Abstract:
Single-cell and spatial omics technologies are spearheading a profound paradigm shift in the life sciences,moving beyond'population averages'to'single-cell resolution'and reintegrating'cellu-lar constitution'with'tissue spatial architecture',thereby dramatically advancing our understanding of biological complexity.This review provides a brief comprehensive overview of recent advancements in the field.Technologically,the evolution has progressed from single-cell transcriptomics to integrated approa-ches capturing multiple molecular layers simultaneously,while the emergence of transcriptome-badsed spatial omics has successfully preserved the spatial positioning of cells or microscosystem within native tis-sues,and further enabling spatial epigenomics and spatial-multiomics.Computationally,artificial intelli-gence and machine learning have become central engines,powering tools for data integration,spatial de-convolution,cellular communication and other novel foundation models,which not only tackle the chal-lenges of massive datasets but also serve as instruments for novel biological discovery.These technological leaps have fostered significant theoretical innovations.In clinical translation,these technologies,particu-larly in precision oncology,demonstrate transformative potential by dissecting tumor heterogeneity,map-ping the spatial architecture of the tumor immune microenvironment,and enabling disease modeling through single-cell-guided deconvolution of bulk data,offering new avenues for diagnosis,prognosis,and personalized therapy.Despite ongoing challenges in technological throughput,computational scalability,and clinical integration,the continued convergence of single-cell and spatial omics with AI promises to propel basic research towards a more mechanistic and predictive era,ultimately reshaping the future of precision medicine.
