CpG methylation signature predicts prognosis in breast cancer
CpG methylation signature predicts prognosis in breast cancer
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DOI：
10.1007/s10549-019-05417-3
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发表时间：
2019-12-01
影响因子：
3.8
通讯作者：
Wu, Yuanyu
中科院分区：
文献类型：
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作者：
Du, Tonghua;Liu, Bin;Wu, Yuanyu
目的DNA甲基化可作为多种癌症的预后生物标志物。我们的目的是确定一个CpG甲基化模式乳腺cancer.Methods在这项研究中，使用来自癌症基因组图谱（TCGA）和基因表达综合（GEO）的微阵列数据，我们描绘了97个健康对照样本和786个乳腺癌样本在一个训练队列（从TCGA，n = 883）使用惩罚回归模型建立一个基因分类器。我们在一个内部验证队列（来自GEO，n = 72）中验证了该基因分类器的预后准确性。结果共选择了1777个差异甲基化CpG，对应于1777个不同甲基化基因（DMG）。随后，生成16个CpG以将患者分类为训练队列中的高风险组和低风险组。训练队列中高风险评分患者的总生存期短于低风险评分患者（风险比[HR]，4.674; 95% CI 2.918 - 7.487; P = 1.678e-12）。在验证队列中也验证了预后准确性。此外，在联合训练和验证队列中具有低风险评分的患者中，与年龄< 60岁的患者相比，年龄> 60岁的患者与总生存率的改善相关（HR 2.088，95% CI 1.348 - 3.235; p = 7.575e-04），在高风险评分患者中，但在低风险评分患者中不存在（HR 1.246，95% CI 0.515至3.011; p = 0.625）。与未接受放疗的患者相比，接受放疗的患者与高风险评分患者的总生存期改善相关（HR 0.418，95% CI 0.249至0.703; p = 6.991e-04），但与低风险评分患者无关（HR 2.092，95% CI 0.574至7.629; p = 0.253）。对于复发和未复发的患者，两组均与总生存率的改善相关（HR 7.475，95% CI 4.333 - 12.901; p = 6.991e-04），高风险评分患者和低风险评分患者（HR 14.33，95%CI 4.265 ~ 48.17; p = 4.883e-13）。结论16个CpG基序的标记物可作为乳腺癌患者预后的生物标志物。
Purpose DNA methylation can be used as prognostic biomarkers in various types of cancers. We aimed to identify a CpG methylation pattern for breast cancer.Methods In this study, using the microarray data from the cancer genome atlas (TCGA) and gene expression omnibus (GEO), we profiled DNA methylation between 97 healthy control samples and 786 breast cancer samples in a training cohort (from TCGA, n = 883) to build a gene classifier using a penalized regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (from GEO, n = 72).Results A total of 1777 differentially methylated CpGs corresponding to 1777 different methylated genes (DMGs) between breast cancer and control were chosen for this study. Subsequently, 16 CpGs were generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter overall survival (hazard ratio [HR], 4.674; 95% CI 2.918 to 7.487; P = 1.678e-12) than patients with low-risk scores. The prognostic accuracy was also validated in the validation cohorts. Furthermore, among patients with low-risk scores in the combined training and validation cohorts, the patients with the age > 60 years compared with the patients with the age < 60 years were associated with improved overall survival (HR 2.088, 95% CI 1.348 to 3.235; p = 7.575e-04) in patients with a high-risk score but not in patients with low-risk score (HR 1.246, 95% CI 0.515 to 3.011; p = 0.625). The patients treated with radiotherapy compared with the patients without radiotherapy were associated with improved overall survival (HR 0.418, 95% CI 0.249 to 0.703; p = 6.991e-04) in patients with a high-risk score but not in patients with low-risk score (HR 2.092, 95% CI 0.574 to 7.629; p = 0.253). For the patients with recurrence and the patients without recurrence both groups were all associated with improved overall survival (HR 7.475, 95% CI 4.333 to 12.901; p = 6.991e-04) in patients with a high-risk score and in patients with low- risk score (HR 14.33, 95% CI 4.265 to 48.17; p = 4.883e-13).Conclusion The 16 CpG-based signature is useful as a biomarker in predicting prognosis for patients with breast cancer.