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基于免疫细胞浸润水平评估结直肠癌患者的预后及免疫治疗反应性。

Assessment of prognosis and responsiveness to immunotherapy in colorectal cancer patients based on the level of immune cell infiltration.

作者信息

Liao Kaili, Zhu Minqi, Guo Lei, Gao Zijun, Cheng Jinting, Sun Bing, Qian Yihui, Lin Bingying, Zhang Jingyan, Qian Tingyi, Jiang Yixin, Xu Yanmei, Zhong Qionghui, Wang Xiaozhong

机构信息

Jiangxi Province Key Laboratory of Immunology and Inflammation, Jiangxi Provincial Clinical Research Center for Laboratory Medicine, Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

School of Public Health, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

出版信息

Front Immunol. 2025 Feb 3;16:1514238. doi: 10.3389/fimmu.2025.1514238. eCollection 2025.

Abstract

OBJECTIVE

To build a new prognostic risk assessment model based on immune cell co-expression networks for predicting overall survival and evaluating the efficacy of immunotherapy for colon cancer patients.

METHODS

The Cancer Genome Atlas (TCGA) database was used to obtain mRNA expression profiling data, clinical information, and somatic mutation data from colorectal cancer patients. The degree of tumor immune cell infiltration of the samples was analyzed using the CIBERSORT algorithm. Co-expression of immune-related genes was analyzed using weighted correlation network analysis (WGCNA) and gene modules were identified. Prognosis-related genes were screened and models were constructed using LASSO-Cox analysis. The models were validated by survival analysis. The prognostic potential of the models was quantitatively assessed using Cox regression analysis and the development of column line plots. Immunotherapy sensitivity analysis was performed using CIBERSORT and TIMER algorithms. Gene biofunction analysis was performed using Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA). And the chemotherapeutic response to different drugs was assessed.

RESULTS

We established a novel prognostic model utilizing the WGCNA method, which demonstrated robust predictive accuracy for patient survival. The high-risk subgroup in our model exhibited elevated immune cell infiltration coupled with a higher tumor mutation burden, but the difference in response to immunotherapy was not significant compared to the low-risk group. Furthermore, we identified distinct chemotherapy responses to 39 drugs between these risk subgroups.

CONCLUSION

This study revealed a significant correlation between high levels of immune infiltration and unfavorable prognosis in patients with colon cancer. Furthermore, an accurate prognostic risk prediction model based on the co-expression of relevant genes by immune cells was developed, enabling precise prediction of survival of colon cancer patients. These findings offer valuable insights for accurate prognostication and comprehensive management of individuals diagnosed with colon cancer.

摘要

目的

构建基于免疫细胞共表达网络的新型预后风险评估模型,用于预测结肠癌患者的总生存期并评估免疫治疗疗效。

方法

利用癌症基因组图谱(TCGA)数据库获取结直肠癌患者的mRNA表达谱数据、临床信息和体细胞突变数据。使用CIBERSORT算法分析样本的肿瘤免疫细胞浸润程度。采用加权相关网络分析(WGCNA)分析免疫相关基因的共表达情况并识别基因模块。筛选预后相关基因并使用LASSO-Cox分析构建模型。通过生存分析验证模型。使用Cox回归分析和柱状线图的绘制对模型的预后潜力进行定量评估。使用CIBERSORT和TIMER算法进行免疫治疗敏感性分析。使用基因集富集分析(GSEA)和基因集变异分析(GSVA)进行基因生物功能分析。并评估对不同药物的化疗反应。

结果

我们利用WGCNA方法建立了一种新型预后模型,该模型对患者生存具有强大的预测准确性。我们模型中的高危亚组表现出免疫细胞浸润增加以及更高的肿瘤突变负担,但与低危组相比,免疫治疗反应的差异不显著。此外,我们确定了这些风险亚组之间对39种药物的不同化疗反应。

结论

本研究揭示了结肠癌患者免疫浸润水平高与不良预后之间存在显著相关性。此外,开发了一种基于免疫细胞相关基因共表达的准确预后风险预测模型,能够精确预测结肠癌患者的生存期。这些发现为准确预测预后和全面管理结肠癌患者提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f094/11830669/f0d00720f2f6/fimmu-16-1514238-g001.jpg

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