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肺腺癌的免疫相关基因预后指数(IRGPI)可预测患者预后及免疫治疗反应。

Immune-related gene prognostic index (IRGPI) for lung adenocarcinoma predicts patient prognosis and immunotherapy response.

作者信息

Zhu Zheng, Feng Wei, Tan Xiao-Yan, Gu Pin-Chao, Song Wei, Ma Hai-Tao

机构信息

Department of Thoracic Surgery, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow University No. 9 Chongwen Road, Suzhou 215000, Jiangsu, China.

Emergency Department, Suzhou Dushu Lake Hospital (Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University), Soochow University No. 9 Chongwen Road, Suzhou 215000, Jiangsu, China.

出版信息

Int J Clin Exp Pathol. 2023 Oct 15;16(10):260-281. eCollection 2023.

Abstract

OBJECTIVE

We searched for a predictive biomarker that also predicts whether patients would benefit from immune checkpoint blockade (ICB) treatment from a few angles, because existing biomarkers no longer wholly replicate the interconnections of distinctive elements in the tumor microenvironment (TME).

METHODS

We identified 55 pivotal IRGs by performing a WGCNA and univariate Cox regression analysis on a lung adenocarcinoma dataset from the TCGA database. The IRGPI model was then constructed using multivariate Cox regression analysis, which identified 16 genes and verified the use of the GSE68465 database. The AUC of the IRGPI was compared to those of the current biomarkers to determine its predictive potential. Then we examined the molecular and immunological properties of ICB and assessed its effectiveness using CTLA4 expression and TIDE.

RESULTS

Patients with a high IRGPI had a later clinical stage, more severe symptoms, and a worse prognosis. Patients with a low IRGPI had a higher immune escape potential and were less responsive to immunotherapy.

CONCLUSION

The IRGPI may be a biomarker for determining the prognosis of patients and whether they respond favorably to ICB therapy.

摘要

目的

我们从多个角度寻找一种预测性生物标志物,该标志物还能预测患者是否会从免疫检查点阻断(ICB)治疗中获益,因为现有的生物标志物已无法完全重现肿瘤微环境(TME)中独特元素的相互联系。

方法

我们通过对来自TCGA数据库的肺腺癌数据集进行加权基因共表达网络分析(WGCNA)和单变量Cox回归分析,确定了55个关键的免疫相关基因(IRG)。然后使用多变量Cox回归分析构建IRGPI模型,该模型确定了16个基因,并在GSE68465数据库中进行了验证。将IRGPI的曲线下面积(AUC)与当前生物标志物的AUC进行比较,以确定其预测潜力。然后我们研究了ICB的分子和免疫学特性,并使用CTLA4表达和TIDE评估了其有效性。

结果

IRGPI高的患者临床分期较晚,症状更严重,预后更差。IRGPI低的患者免疫逃逸潜力更高,对免疫治疗的反应性更低。

结论

IRGPI可能是一种用于确定患者预后以及他们是否对ICB治疗有良好反应的生物标志物。

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