| 基于m6A RNA修饰相关基因的肺腺癌预后模型构建与分析 |
| 投稿时间：2024-11-14 修订日期：2024-11-17 点此下载全文 |
| 引用本文：方蒙,杨帆,王浓燕,陈少明,胡海燕,胡旭钢.基于m6A RNA修饰相关基因的肺腺癌预后模型构建与分析[J].医学研究杂志,2025,54(5):129-135 |
| DOI：
10.11969/j.issn.1673-548X.2025.05.024 |
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| 基金项目:浙江省医药卫生科技计划项目(2021KY946)；浙江省教育厅一般项目(Y202456549)；中国人民解放军联勤部队第903医院自主科研项目(YQ202306) |
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| 中文摘要:目的 基于N6-腺苷酸RNA甲基化修饰(N6-methyladenosine,m6A)相关基因构建肺腺癌( lung adenocarcinoma,LUAD)预后模型并探讨其临床意义。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)和基因综合表达数据库(gene expression omnibus,GEO)下载LUAD数据集。将TCGA数据集按7∶3的比例划分为训练集和验证集,在训练集中采用单因素COX分析及LASSO回归分析构建m6A相关基因预后模型。在TCGA、GSE30219、GSE31210、GSE41271、GSE50081和GSE68465数据集中分别计算风险评分,按其中位值将患者分为高、低风险。通过绘制Kaplan-Meier曲线、ROC曲线、多因素COX回归分析验证预后模型的可靠性；构建列线图模型探究风险评分在预后监测中的作用；利用基因富集分析探索预后模型富集的信号通路；并进一步探讨风险评分与免疫浸润、驱动基因突变的相关性。结果 本研究构建了一个包含AKAP12、CBFA2T3、KIF14、KL、KRT6A、LIFR、MIF、RRM2、TLR8等9个m6A相关基因的预后模型,是LUAD患者预后的独立因素。基于风险评分和T、N分期的列线图模型能更准确地预测LUAD患者的预后。进一步分析显示高风险组的mTORC1、Myc信号通路、DNA损伤修复等信号通路显著激活,CD8+ T 细胞、CD4+ T 细胞浸润比例显著降低,免疫检查点CD276表达升高,CTLA4表达降低,且风险评分与EGFR、KRAS突变相关。结论 基于m6A相关基因的预后模型能有效预测LUAD患者的预后,可用于指导患者的靶向及免疫治疗。 |
| 中文关键词:肺腺癌 m6A 预后 免疫浸润 驱动基因突变 |
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| Construction and Analysis of a Prognostic Risk Model for Lung Adenocarcinoma Based on m6A-related Genes |
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| Abstract:Objective To construct a prognostic model for lung adenocarcinoma (LUAD) based on N6-methyladenosine (m6A)-related genes and explore its clinical significance. Methods The LUAD dataset was obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The TCGA dataset was divided into a training set and a validation set in a 7∶3 ratio. In the training set, the m6A-related gene prognostic model was constructed using univariate COX analysis and LASSO regression analysis. Risk scores were calculated for the TCGA, GSE30219, GSE31210, GSE41271, GSE50081, and GSE68465datasets. Patients were categorized into low-risk and high-risk groups based on the median value of the risk scores. Kaplan-Meier (KM) curves, receiver operating characteristic (ROC) curves and multivariate COX regression analysis were used to verify the reliability of the prognosis model. A nomogram model was constructed to assess the role of risk scores in prognostic monitoring. Gene set enrichment analysis (GSEA) was performed to identify enriched signaling pathways in the prognostic model. The correlation between risk scores, immune infiltration, and driver gene mutations was analyzed. Results A prognostic model comprising nine m6A-related genes (AKAP12, CBFA2T3, KIF14, KL, KRT6A, LIFR, MIF, RRM2, TLR8) was developed. which emerged as an independent prognostic factor for LUAD. The model based on the risk score, T stages and N stages, accurately predicted LUAD prognosis. In high-risk group, mTORC1, Myc signaling pathways, and DNA repair mechanisms were significantly activated, the infiltration of CD8+T cells and CD4+ T cells decreased, the expression of CD276 increased, and the expression of CTLA4 decreased. Additionally, risk scores were correlated with EGFR and KRAS mutations. ConclusionThe prognostic model based on m6A-related genes effectively predicts LUAD prognosis and can guide targeted therapy and immunotherapy treatments for patients. |
| keywords:Lung adenocarcinoma m6A Prognosis Immune infiltration Driver-gene mutation |
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