Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer.
Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer.
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DNA 甲基化和基因表达的综合分析以确定乳腺癌的特异性诊断生物标志物和预后生物标志物
DOI：
10.3389/fcell.2020.529386
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发表时间：
2020
影响因子：
5.5
通讯作者：
Zhao L
中科院分区：
文献类型：
--
作者：
Zhang M;Wang Y;Wang Y;Jiang L;Li X;Gao H;Wei M;Zhao L
背景资料：DNA甲基化是各种肿瘤早期发展中的常见事件，包括乳腺癌（BRCA），已被研究为潜在的肿瘤生物标志物。虽然以前的研究已经报道了BRCA中一组异常的启动子甲基化变化，但这些研究小组都没有证明这些DNA甲基化变化的特异性。在这里，我们的目的是确定特定的DNA甲基化标志物在BRCA中，可用作诊断和预后标志物。方法：使用癌症基因组图谱（TCGA）BRCA数据集鉴定差异甲基化位点。我们通过比较BRCA患者、健康乳腺活检组织和血液样本的甲基化谱来筛选BRCA差异甲基化。将这些差异甲基化位点与9个主要癌症样本进行比较，以鉴定BRCA特异性甲基化位点。建立贝叶斯网络模型来区分BRCA患者和健康供体。使用三个基因表达综合数据集（GEO）独立的数据集验证该模型。此外，我们还进行了考克斯回归分析，以确定与BRCA患者的总生存率（OS）显著相关的DNA甲基化标志物，并在验证队列中进行验证。结果如下：我们确定了7个与细胞周期高度相关的差异甲基化位点（DMS）作为BRCA患者潜在的特异性诊断生物标志物。7种DMS的组合在预测BRCA方面达到约94%的灵敏度，比较健康与癌症样本的约95%的特异性，以及排除其他癌症的约88%的特异性。7种DMS与细胞周期高度相关。我们还发现了6个与BRCA患者OS高度相关的甲基化位点，可用于准确预测BRCA患者的生存率（训练队列：似然比= 70.25，p = 3.633 × 10−13，曲线下面积（AUC）= 0.784;验证队列：AUC = 0.734）。按年龄、临床分期、肿瘤类型和化疗进行分层分析仍具有统计学意义。结论：总之，我们的研究表明甲基化谱在BRCA的诊断和预后中的作用。该标记优于目前发表的用于BRCA患者诊断和预后的甲基化标志物上级。它可以作为BRCA早期诊断和预后的生物标志物。
Background: DNA methylation is a common event in the early development of various tumors, including breast cancer (BRCA), which has been studies as potential tumor biomarkers. Although previous studies have reported a cluster of aberrant promoter methylation changes in BRCA, none of these research groups have proved the specificity of these DNA methylation changes. Here we aimed to identify specific DNA methylation signatures in BRCA which can be used as diagnostic and prognostic markers. Methods: Differentially methylated sites were identified using the Cancer Genome Atlas (TCGA) BRCA data set. We screened for BRCA-differential methylation by comparing methylation profiles of BRCA patients, healthy breast biopsies and blood samples. These differential methylated sites were compared to nine main cancer samples to identify BRCA specific methylated sites. A BayesNet model was built to distinguish BRCA patients from healthy donors. The model was validated using three Gene Expression Omnibus (GEO) independent data sets. In addition, we also carried out the Cox regression analysis to identify DNA methylation markers which are significantly related to the overall survival (OS) rate of BRCA patients and verified them in the validation cohort. Results: We identified seven differentially methylated sites (DMSs) that were highly correlated with cell cycle as potential specific diagnostic biomarkers for BRCA patients. The combination of 7 DMSs achieved ~94% sensitivity in predicting BRCA, ~95% specificity comparing healthy vs. cancer samples, and ~88% specificity in excluding other cancers. The 7 DMSs were highly correlated with cell cycle. We also identified 6 methylation sites that are highly correlated with the OS of BRCA patients and can be used to accurately predict the survival of BRCA patients (training cohort: likelihood ratio = 70.25, p = 3.633 × 10−13, area under the curve (AUC) = 0.784; validation cohort: AUC = 0.734). Stratification analysis by age, clinical stage, Tumor types, and chemotherapy retained statistical significance. Conclusion: In summary, our study demonstrated the role of methylation profiles in the diagnosis and prognosis of BRCA. This signature is superior to currently published methylation markers for diagnosis and prognosis for BRCA patients. It can be used as promising biomarkers for early diagnosis and prognosis of BRCA.
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影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
影响因子：
64.8
作者：
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影响因子：
6.2
作者：
Domchek, Susan M.;Jhaveri, Komal;Robson, Mark
通讯作者：
Robson, Mark
影响因子：
8.8
作者：
Russell, Matthew R.;Graham, Ciaren;Graham, Robert L. J.
通讯作者：
Graham, Robert L. J.
影响因子：
45.3
作者：
Liedtke, Cornelia;Mazouni, Chafika;Pusztai, Lajos
通讯作者：
Pusztai, Lajos