Wang Ziqiang, Zhang Jing, Chen Huili, Zhang Xinyu, Zhang Kai, Zhang Feiyue, Xie Yiluo, Ma Hongyu, Pan Linfeng, Zhang Qiang, Lu Min, Wang Hongtao, Lian Chaoqun
Key Laboratory of Cancer Research and Clinical Laboratory Diagnosis, Bengbu Medical University, Bengbu, China.
Department of Genetics, School of Life Sciences, Bengbu Medical University, Bengbu, China.
Front Immunol. 2025 Aug 13;16:1650726. doi: 10.3389/fimmu.2025.1650726. eCollection 2025.
M2-like tumor-associated macrophages (TAMs) promote an immunosuppressive microenvironment and contribute to tumor progression and metastasis. However, their molecular characterization and prognostic value have not been fully explored in the field of breast cancer.
Weighted gene co-expression network analysis (WGCNA) was used to identify modules significantly associated with M2-like TAMs. Consensus clustering analysis identified three molecular subtypes with distinct clinical features, and we explored potential differences in genomic mutations, pathway enrichment, and immune infiltration in patients between subtypes. Machine learning algorithms were used to screen key genes and construct M2-like macrophage-associated prognostic models. Comprehensive transcriptomic analysis and phenotyping and polarization experiments were performed on the key gene .
M2-like TAMs infiltration was strongly associated with the prognosis of BC patients, and the associated gene characterization revealed three molecular subtypes, of which C2 has the worst prognosis with high M2 macrophages, immune desert phenotype, and immunotherapeutic resistance; C1 had the best prognosis, rich in stromal and immune cell infiltration, and metabolic pathway activation; and C3 had a high level of TILs and genomic mutations, with a high degree of immunogenicity and immunotherapeutic Potential. Risk scores can effectively predict the prognosis and immunotherapy response of BC patients, in which is a key gene that may be involved in shaping the immunosuppressive microenvironment of breast cancer, and down-regulation of can inhibit M2 polarization of macrophages.
We constructed and comprehensively solved a model of M2-like TAM-related molecular subtypes and prognosis, which helps stratify and customize treatment regimens for BC patients. We also explored the role of in BC progression and macrophage polarization.
M2样肿瘤相关巨噬细胞(TAM)促进免疫抑制微环境,并促进肿瘤进展和转移。然而,在乳腺癌领域,它们的分子特征和预后价值尚未得到充分探索。
使用加权基因共表达网络分析(WGCNA)来识别与M样TAM显著相关的模块。共识聚类分析确定了具有不同临床特征的三种分子亚型,我们探讨了各亚型患者在基因组突变、通路富集和免疫浸润方面的潜在差异。使用机器学习算法筛选关键基因并构建与M2样巨噬细胞相关的预后模型。对关键基因进行了综合转录组分析以及表型和极化实验。
M2样TAM浸润与BC患者的预后密切相关,相关基因特征揭示了三种分子亚型,其中C2预后最差,M2巨噬细胞含量高、免疫沙漠表型和免疫治疗耐药;C1预后最好,富含基质和免疫细胞浸润以及代谢途径激活;C3具有高水平的肿瘤浸润淋巴细胞(TIL)和基因组突变,具有高度免疫原性和免疫治疗潜力。风险评分可以有效预测BC患者的预后和免疫治疗反应,其中 是一个关键基因,可能参与塑造乳腺癌的免疫抑制微环境,下调 可抑制巨噬细胞的M2极化。
我们构建并全面解析了一个与M2样TAM相关的分子亚型和预后模型,这有助于为BC患者分层并定制治疗方案。我们还探讨了 在BC进展和巨噬细胞极化中的作用。