Department of Radiation Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, 325035, China.
Zhejiang Provincial Key Laboratory of Watershed Sciences and Health, Wenzhou Medical University, Wenzhou, 325035, China.
Respir Res. 2022 Jul 15;23(1):190. doi: 10.1186/s12931-022-02110-w.
As a DNA surveillance mechanism, cell cycle checkpoint has recently been discovered to be closely associated with lung adenocarcinoma (LUAD) prognosis. It is also an essential link in the process of DNA damage repair (DDR) that confers resistance to radiotherapy. Whether genes that have both functions play a more crucial role in LUAD prognosis remains unclear.
In this study, DDR-related genes with cell cycle checkpoint function (DCGs) were selected to investigate their effects on the prognosis of LUAD. The TCGA-LUAD cohort and two GEO external validation cohorts (GSE31210 and GSE42171) were performed to construct a prognosis model based on the least absolute shrinkage and selection operator (LASSO) regression. Patients were divided into high-risk and low-risk groups based on the model. Subsequently, the multivariate COX regression was used to construct a prognostic nomogram. The ssGSEA, CIBERSORT algorithm, TIMER tool, CMap database, and IC50 of chemotherapeutic agents were used to analyze immune activity and responsiveness to chemoradiotherapy.
4 DCGs were selected as prognostic signatures, and patients in the high-risk group had a lower overall survival (OS). The lower infiltration levels of immune cells and the higher expression levels of immune checkpoints appeared in the high-risk group. The damage repair pathways were upregulated, and chemotherapeutic agent sensitivity was poor in the high-risk group.
The 4-DCGs signature prognosis model we constructed could predict the survival rate, immune activity, and chemoradiotherapy responsiveness of LUAD patients.
作为一种 DNA 监测机制,细胞周期检查点最近被发现与肺腺癌 (LUAD) 预后密切相关。它也是赋予放射治疗抗性的 DNA 损伤修复 (DDR) 过程中的一个重要环节。具有这两种功能的基因是否在 LUAD 预后中发挥更关键的作用尚不清楚。
本研究选择具有细胞周期检查点功能的 DDR 相关基因 (DCGs),探讨其对 LUAD 预后的影响。对 TCGA-LUAD 队列和两个 GEO 外部验证队列 (GSE31210 和 GSE42171) 进行分析,构建基于最小绝对收缩和选择算子 (LASSO) 回归的预后模型。根据模型将患者分为高风险组和低风险组。然后,采用多变量 COX 回归构建预后列线图。使用 ssGSEA、CIBERSORT 算法、TIMER 工具、CMap 数据库和化疗药物的 IC50 分析免疫活性和对放化疗的反应性。
筛选出 4 个 DCGs 作为预后标志物,高风险组患者的总体生存率 (OS) 较低。高风险组的免疫细胞浸润水平较低,免疫检查点表达水平较高。损伤修复途径上调,高风险组化疗药物敏感性较差。
我们构建的 4-DCGs 预后模型可预测 LUAD 患者的生存率、免疫活性和放化疗反应性。