Wenying Shi, Zhiqiang Zhang, Xiaotong Xu, Yanpeng Tian, Feng Li, Xianghua Huang, Yanfang Du, Zhongkang Li
Single-cell RNA sequencing (scRNA-seq) has emerged as an advanced biological technology capable of resolving the complexity of cancer landscapes at single-cell resolution. Spatial transcriptomics(ST), as an innovative complementary approach, effectively compensates for the lack of spatial information inherent in scRNA-seq data. This review explores the rapidly evolving integration of scRNA-seq and ST and their transformative role in deciphering the tumor microenvironment (TME). We highlight how these technologies jointly uncover cellular heterogeneity, stromal-immune interactions, and spatial niches driving tumor progression and therapy resistance. Moving beyond previous reviews, we emphasize emerging computational strategies for data integration-including deconvolution and mapping approaches-and evaluate their applications in characterizing immune evasion, fibroblast diversity, and cell-cell communication networks. Ultimately, this review provides a forward-looking perspective on how spatial multi-omics are poised to advance precision oncology through spatially-informed biomarkers and diagnostic tools. We conclude that the full clinical potential of these technologies relies on closing the gap between analytical innovation and robust clinical implementation.