Spatiotemporal multi-omics reveals lineage, spatial and functional heterogeneity of tumor-associated macrophages and therapeutic vulnerabilities in the tumor microenvironment

Tumor-associated macrophages (TAMs) are central orchestrators of immune evasion, therapeutic resistance, and clinical outcome across diverse solid tumors. However, the classical M1/M2 paradigm fails to capture the lineage diversity, spatial heterogeneity, and functional plasticity of TAMs within the tumor microenvironment. Unlike previous reviews that mainly summarize macrophage polarization or TAM subtype classification, this review focuses on how emerging single-cell and spatial multi-omics technologies redefine TAM ontogeny, phenotypic diversity, spatial organization, and therapeutic vulnerabilities. This review summarizes how fate-mapping, single-cell transcriptomics, and spatial multi-omics have contributed to the understanding of the dual origins of TAMs, including embryo-derived tissue-resident macrophages and monocyte-derived macrophages, and how these technologies further delineate transcriptionally and functionally distinct TAM subsets such as SPP1 + , TREM2 + , C1QC + , and MMP9 + TAMs with context-dependent roles in immune regulation, metastasis, and treatment resistance. We then integrate spatial transcriptomics, multiplex imaging, and radiomics evidence to outline TAM-enriched niches at hypoxic cores, invasive fronts, perivascular regions and tertiary lymphoid structures, emphasizing how these niches coordinate crosstalk among cancer cells, T cells, cancer-associated fibroblasts, endothelial cells and B cells. Emerging TAM-related gene signatures and multi-omics-based scores were further highlighted that predict response or resistance to radiotherapy, chemotherapy, anti-angiogenic therapy, and immune checkpoint blockade. Finally, we provide a forward-looking perspective on strategies to reprogram, deplete, or redirect specific TAM subsets, including CSF1/CSF1R and CCR2/CCL2 blockade, metabolic and epigenetic modulators, agonists of phagocytosis, and CAR-macrophage–based therapies. Overall, we propose that integrating single-cell and spatial omics with AI-assisted digital pathology and longitudinal sampling will enable TAM-informed patient stratification and rational design of combination immunotherapies, thereby accelerating the translation of TAM biology into precision oncology.