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构建M2巨噬细胞相关基因特征以预测膀胱癌患者的预后并揭示不同的免疫治疗反应

Construction of M2 macrophage-related gene signature for predicting prognosis and revealing different immunotherapy response in bladder cancer patients.

作者信息

Tuo Zhouting, Gao Mingzhu, Jiang Chao, Zhang Duobing, Chen Xin, Jiang Zhiwei, Wang Jinyou

机构信息

Department of Urology, Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.

Department of Oncology, Second Affiliated Hospital of Anhui Medical University, Hefei, 230601, China.

出版信息

Clin Transl Oncol. 2025 May;27(5):2191-2206. doi: 10.1007/s12094-024-03698-9. Epub 2024 Sep 30.

Abstract

BACKGROUND

Bladder cancer development is closely associated with the dynamic interaction and communication between M2 macrophages and tumor cells. However, specific biomarkers for targeting M2 macrophages in immunotherapy remain limited and require further investigation.

METHODS

In this study, we identified key co-expressed genes in M2 macrophages and developed gene signatures to predict prognosis and immunotherapy response in patients. Public database provided the bioinformatics data used in the analysis. We created and verified an M2 macrophage-related gene signature in these datasets using Lasso-Cox analysis.

RESULTS

The predictive value and immunological functions of our risk model were examined in bladder cancer patients, and 158 genes were found to be significantly positively correlated with M2 macrophages. Moreover, we identified two molecular subgroups of bladder cancer with markedly different immunological profiles and clinical prognoses. The five key risk genes identified in this model were validated, including CALU, ECM1, LRP1, CYTL1, and CCDC102B, demonstrating the model can accurately predict prognosis and identify unique responses to immunotherapy in patients with bladder cancer.

CONCLUSIONS

In summary, we constructed and validated a five-gene signature related to M2 macrophages, which shows strong potential for forecasting bladder cancer prognosis and immunotherapy response.

摘要

背景

膀胱癌的发生与M2巨噬细胞和肿瘤细胞之间的动态相互作用及通讯密切相关。然而,免疫治疗中靶向M2巨噬细胞的特异性生物标志物仍然有限,需要进一步研究。

方法

在本研究中,我们鉴定了M2巨噬细胞中关键的共表达基因,并开发了基因特征以预测患者的预后和免疫治疗反应。公共数据库提供了分析中使用的生物信息学数据。我们使用套索-考克斯分析在这些数据集中创建并验证了一个与M2巨噬细胞相关的基因特征。

结果

在膀胱癌患者中检验了我们风险模型的预测价值和免疫功能,发现158个基因与M2巨噬细胞显著正相关。此外,我们鉴定出膀胱癌的两个分子亚组,其免疫特征和临床预后明显不同。该模型中鉴定出的五个关键风险基因得到验证,包括CALU、ECM1、LRP1、CYTL1和CCDC102B,表明该模型可以准确预测膀胱癌患者的预后并识别其对免疫治疗的独特反应。

结论

总之,我们构建并验证了一个与M2巨噬细胞相关的五基因特征,其在预测膀胱癌预后和免疫治疗反应方面显示出强大潜力。

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