Wang Sheng-Chao, Liao Li-Min, Ansar Muhamad, Lin Shih-Yun, Hsu Wei-Wen, Su Chih-Ming, Chung Yu-Mei, Liu Cai-Cing, Hung Chin-Sheng, Lin Ruo-Kai
Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan.
Division of General Surgery, Department of Surgery, Taipei Medical University Shuang Ho Hospital, No.291, Zhongzheng Rd., Zhonghe District, New Taipei City 23561, Taiwan.
Cancers (Basel). 2021 Mar 18;13(6):1375. doi: 10.3390/cancers13061375.
The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated , and biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of , and (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of , and (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated , and was also significantly decreased after surgery (all < 0.001). The aberrant methylation patterns of the , and genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.
癌症的早期检测可降低癌症相关死亡率。目前尚无临床上可用于早期检测乳腺癌的非侵入性生物标志物。本研究的目的是开发准确且精确的早期检测生物标志物以及治疗后的动态监测系统。我们分析了台湾乳腺癌患者和癌症基因组图谱（TCGA）乳腺癌（BC）患者的全基因组甲基化阵列。大多数乳腺癌特异性循环甲基化、和生物标志物在血浆中被发现。建立了甲基化循环游离DNA（ccfDNA）的自动分析流程。在R语言中使用递归划分和回归树对、和（CGIm）进行联合分析，以建立新的预测模型。发现、和（CGIm）联合分析在训练集中的灵敏度水平为97%，曲线下面积（AUC）为0.955，在测试集中的灵敏度水平为100%，AUC为0.961。手术后循环甲基化、和也显著降低（均P<0.001）。、和基因的异常甲基化模式表明它们是早期乳腺癌检测的潜在生物标志物，可与乳腺成像数据相结合以实现更高的准确性、灵敏度和特异性，便于乳腺癌检测。它们还可用于监测手术治疗反应。
