Abstract The tumor microenvironment (TME) plays a pivotal role in shaping immune responses and therapeutic outcomes in lung cancer, yet the diversity and functional specialization of tumor-associated macrophages (TAMs) remain poorly resolved. Here, we present a refined classification of TAM subtypes across large cohorts of cancer datasets using integrative analysis of single-cell RNA sequencing, spatial transcriptomics, and clinical datasets from lung adenocarcinoma and lung squamous cell carcinoma. By combining cell-based gene scoring with hierarchical classification, we defined 7 macrophage subtypes—each with distinct transcriptional programs and abundances. Notably, lipid-associated TAMs expand with disease progression and exhibit immunosuppressive and protumorigenic features, whereas tissue-resident macrophages decline. Spatial and survival analyses reveal that an increased lipid-associated to tissue-resident TAM ratio correlates with advanced disease and poor prognosis. Given that spatial transcriptomic assays rely on deconvolution techniques to infer cell type compositions, accurate gene expression signatures are essential, especially for fine-grained subpopulations of TAMs. Our refined subtype-specific signatures address this bottleneck and enhance the resolution of spatial mapping efforts. These findings offer new insights into macrophage heterogeneity and highlight lipid-associated TAMs as potential biomarkers and therapeutic targets in lung cancer.
Keremitçi et al. (Tue,) studied this question.
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