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乳腺癌中M2样巨噬细胞浸润相关基因模型的预后和免疫学价值
作者:米叶沙尔· 安尼娃尔  郭凡  孔维娜  何伟澜  夏菲菲  马秀敏 
单位:新疆医科大学第三临床医学院 医学检验中心, 新疆 乌鲁木齐 830011
关键词:乳腺癌 M2样肿瘤相关巨噬细胞 免疫浸润 预后风险模型 
分类号:R737.9
出版年·卷·期(页码):2024·43·第二期(157-170)
摘要:

目的: 乳腺癌发展不但涉及癌细胞的基因改变, 还与肿瘤微环境相关。肿瘤相关巨噬细胞(TAMs)是乳腺肿瘤微环境中最丰富且活跃的免疫细胞。本研究旨在探索M2样巨噬细胞(M2-TAMs)相关基因作为评估乳腺癌个体风险生物标志物的潜力。方法: 利用癌症基因组图谱数据库(TCGA)和基因表达综合数据库(GEO),筛选M2-TAMs相关基因后采用比例风险回归(Cox)及最小绝对收缩和选择算子(LASSO)回归分析,建立M2-TAMs相关基因模型,将患者分为高、低危组进行生存、临床特征、免疫学等分析。结果: M2-TAMs相关基因模型中低危组患者的预后明显优于高危组,并且模型中的风险评分可作为乳腺癌患者预后的独立预测因子,另结合临床特征和风险评分可更准确地评估患者预后。大部分免疫细胞在低危组中呈高度浸润,两组患者在免疫功能上存在显著差异,且有许多差异表达的免疫检查点相关基因。结论: M2-TAMs相关基因模型表现出突出的预测性能,并为评估免疫治疗的成功提供了新的观点,有助于为精确治疗和综合治疗提供新的见解。

Objective: The development of breast cancer is not only related to the genetic changes of tumor cells, but also to the tumor microenvironment. Tumor-associated macrophages(TAMs) are the most abundant and active immune cells in breast tumor microenvironment. This study aimed to explore the potential of M2 macrophages(M2-TAMs) related genes as biomarkers to assess individual risk of breast cancer. Methods: Using the Cancer Genome Atlas(TCGA) and the Gene Expression Omnibus(GEO) databases, the M2-TAMs related genes were screened, then, the proportional hazards model(Cox) and Least Absolute Value Convergence and Selection Operator(LASSO) regression analysis were used to establish the M2-TAMs related risk model. Patients were divided into high-risk and low-risk groups for survival, clinical characteristics, and immunology analysis. Results: The prognosis of patients in the low-risk group in the M2-TAMs related risk model was obviously better than that in the high-risk group. Moreover, the risk score in the model can be used as an independent predictor of the prognosis of breast cancer patients, and combined with clinical characteristics and risk score, the prognosis of patients can be evaluated more accurately. Most immune cells were highly infiltrated in the low-risk group and there were significant differences in immune function between the two groups, and there were many differentially expressed immune checkpoint-related genes. Conclusion: M2-TAMs related risk model shows outstanding predictive performance, and provides a new perspective for evaluating the success of immunotherapy, which is helpful to provide new insights for precise treatment and comprehensive treatment.

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