鉴定差异甲基化基因作为乳腺癌的诊断和预后生物标志物。
Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer.
机构信息
Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China.
Department of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
出版信息
World J Surg Oncol. 2021 Jan 26;19(1):29. doi: 10.1186/s12957-021-02124-6.
BACKGROUND
Aberrant DNA methylation is significantly associated with breast cancer.
METHODS
In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.
RESULTS
In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival.
CONCLUSIONS
Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.
背景
异常的 DNA 甲基化与乳腺癌显著相关。
方法
本研究采用生物信息学分析方法，旨在寻找新的甲基化生物标志物，这些标志物可能对乳腺癌的诊断和预后具有临床价值。首先，通过比较公开的数据集（GSE72245 和 GSE88883），检测乳腺癌样本中的差异甲基化 DNA 模式。然后，使用在线工具 UALCAN 估算 7 个选定的甲基化生物标志物的甲基化水平。接下来，通过 ROC 曲线分析，在两个独立队列和两个混合队列中评估这些选定生物标志物的诊断价值。最后，通过 Kaplan-Meier 绘图分析评估选定的甲基化生物标志物对乳腺癌的预后价值。
结果
在这项研究中，在乳腺癌数据集中共确定了 23 个显著差异甲基化位点，对应 9 个不同的基因。在鉴定的 9 个基因中，ADCY4、CPXM1、DNM3、GNG4、MAST1、mir129-2、PRDM14 和 ZNF177 呈高甲基化。重要的是，每个选定的甲基化基因的个体值均大于 0.9，而所有基因组合的预测值为 0.9998。我们还发现，7 个基因（ADCY4、CPXM1、DNM3、GNG4、MAST1、PRDM14、ZNF177）的组合标记物的 AUC 为 0.9998 [95%CI 0.9994-1]，而 3 个基因（MAST1、PRDM14 和 ZNF177）的组合标记物的 AUC 为 0.9991 [95%CI 0.9976-1]。额外的验证分析结果表明，MAST1、PRDM14 和 ZNF177 对乳腺癌的诊断具有高灵敏度、特异性和准确性。最后，患者生存分析显示，ADCY4、CPXM1、DNM3、PRDM14、PRKCB 和 ZNF177 的高表达与更好的总生存显著相关。
结论
MAST1、PRDM14 和 ZNF177 的甲基化模式可能代表乳腺癌的新诊断生物标志物，而 ADCY4、CPXM1、DNM3、PRDM14、PRKCB 和 ZNF177 的甲基化可能对乳腺癌具有预后潜力。
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