ArticleFunctional & integrative genomics2025
Pan-cancer single-cell and spatial transcriptomics implicate cancer-associated fibroblasts in neutrophil immunosuppressive phenotypic transitions and immunotherapy resistance.
Article in Functional & integrative genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Single-cell profiling reveals peripheral blood immune landscape remodelling in breast cancer lymph node metastasis.Clinical and translational medicine · 2026Article
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Authors and funding
6 authors.
Funding
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Abstract
Neutrophils are the most abundant granulocyte population and have important functions such as defense against pathogens. However, they show significant Heterogeneity and play more complex roles in tumors. The theory of two-tiered differentiation of neutrophils is insufficient to summarize their phenotypic and functional Heterogeneity. Therefore, specific regulatory mechanisms remain to be explored and neutrophil-based therapeutic regimens remain challenging. Here, we generated a single-cell atlas of neutrophils from 462 patients with 21 cancer types, revealing their heterogeneity, with CXCR2 + VNN2 + Neu as the main functional subpopulation exerting immunosuppressive effects. Spatial transcriptomic analysis across pan-cancer tissues revealed an association between fibroblast activity and the phenotypic transition of CXCR2 + VNN2 + Neu, potentially enabling their acquisition of immunosuppressive functions via ligand-receptor interactions, cytokine signaling, and extracellular vesicle communication. These findings imply that tumor microenvironment components may contribute to the heterogeneous prognostic associations observed between neutrophils and clinical outcomes in pan-cancer patients. Subsequently, we constructed a gene regulatory network to demonstrate the specific regulatory mechanisms of CXCR2 + VNN2 + Neu and identified BACH1 and ATF2 as potential therapeutic targets. Combination therapy may enhance the efficacy of neutrophil-based therapeutic regimens. Analysis of pan-cancer immunotherapy cohorts revealed a significant correlation between CXCR2 + VNN2 + Neu phenotypic transition and immunotherapy resistance in patients. We finally constructed a deep learning model named Deepsurv to accurately stratify pan-cancer patients based on the CXCR2 + VNN2 + Neu Phenotypic Transition Gene Regulatory Network (CVN-GRN) and predict the prognosis of the patients, which achieved the desired results.
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