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.
Shi et al. (2025) studied this question.