基于表观基因组数据的乳腺癌预后基因-年龄交互作用研究

周添霖; 薛茂杰; 戴智翔; 张汝阳; 陈峰

文章摘要

周添霖,薛茂杰,戴智翔,张汝阳,陈峰.基于表观基因组数据的乳腺癌预后基因-年龄交互作用研究[J].中华流行病学杂志,2024,45(7):1007-1013

基于表观基因组数据的乳腺癌预后基因-年龄交互作用研究

Gene-age interaction study of breast cancer prognosis based on epigenomic data

收稿日期:2024-02-01 出版日期:2024-07-13

DOI：10.3760/cma.j.cn112338-20240201-00057

中文关键词: 乳腺癌 DNA甲基化年龄交互作用

英文关键词: Breast cancer DNA methylation Age Interaction

基金项目:国家自然科学基金（82220108002，82273737）

作者	单位	E-mail
周添霖	南京医科大学公共卫生学院生物统计学系, 南京 211166
薛茂杰	南京医科大学附属常州第二人民医院信息科, 常州 213164
戴智翔	南京医科大学公共卫生学院生物统计学系, 南京 211166
张汝阳	南京医科大学附属常州第二人民医院信息科, 常州 213164	zhangruyang@njmu.edu.cn
陈峰	南京医科大学公共卫生学院生物统计学系, 南京 211166 南京医科大学环境与人类健康国际联合研究中心, 南京 211166	fengchen@njmu.edu.cn

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中文摘要:

目的基于表观基因组数据，探索乳腺癌预后基因-年龄交互作用。方法利用癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）多个独立乳腺癌表观基因组数据集，进行DNA甲基化的差异表达分析。采用错误发现率（FDR）法进行多重校正，保留q-FDR≤0.05的差异表达甲基化位点。应用三阶段分析策略，采用多因素Cox比例风险回归模型检验基因-年龄交互作用。发现阶段使用TCGA-BRCA数据库筛选q-FDR≤0.05的信号。验证阶段Ⅰ使用GSE72245数据验证交互作用，标准为P≤0.05且效应方向一致。验证阶段Ⅱ使用GSE37754和GSE75067数据再次验证信号。通过结合临床指标与交互作用信号构建预后预测模型。结果三阶段分析策略鉴定出一个甲基化位点（cg16126280_EBF1），其与年龄存在交互作用，共同影响患者的生存时间（交互作用HR=1.001 1，95%CI：1.000 7~1.001 5，P<0.001）。年龄分层分析显示，cg16126280_EBF1的高甲基化效应在乳腺癌年轻患者（HR=0.550 5，95%CI：0.383 8~0.789 6，P=0.001）和老年患者中完全相反（HR=2.166 5，95%CI：1.285 2~3.652 2，P=0.004）。结论 DNA甲基化位点cg16126280_EBF1与年龄存在交互作用，以复杂的关联模式共同影响乳腺癌预后，为年龄特异性靶向药物研发提供了新的人群证据。

英文摘要:

Objective Exploring gene-age interactions associated with breast cancer prognosis based on epigenomic data. Methods Differential expression analysis of DNA methylation was conducted using multiple independent epigenomic datasets of breast cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The false discovery rate (FDR) method was used for multiple corrections, retaining differentially methylated sites with q-FDR≤0.05. A three-stage analytic strategy was implemented, using a multivariable Cox proportional hazards regression model to examine gene-age interactions. In the discovery phase, signals with q-FDR≤ 0.05 were screened out using TCGA-BRCA database. In validation phaseⅠ, the interaction was validated using GSE72245 data, with criteria of P≤0.05 and consistent effect direction. In validation phaseⅡ, the signals were further validated using GSE37754 and GSE75067 data. A prognostic prediction model was constructed by incorporating clinical indicators and interaction signals. Results The three-stage analytic strategy identified a methylation site (cg16126280_EBF1), which interacted with age to jointly affect the overall survival time of patients (interaction HR= 1.001 1,95%CI:1.000 7-1.001 5,P<0.001). Stratified analysis by age showed that the effect of hypermethylation of cg16126280_EBF1 was completely opposite in younger patients (HR=0.550 5, 95%CI: 0.383 8-0.789 6, P=0.001) and older patients (HR=2.166 5, 95%CI: 1.285 2-3.652 2, P=0.004). Conclusions The DNA methylation site cg16126280_EBF1 exhibits an interaction with age, jointly influencing the prognosis of breast cancer in a complex association pattern. This finding contributes new population-based evidence for the development of age-specific targeted drugs.

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