Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response

Sheng-Chao Wang; Li-Min Liao; Muhamad Ansar; Shih-Yun Lin; Wei-Wen Hsu; Chih-Ming Su; Yu-Mei Chung; Cai-Cing Liu; Chin-Sheng Hung; Ruo-Kai Lin

doi:10.3390/cancers13061375

Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response

Cancers (Basel). 2021 Mar 18;13(6):1375. doi: 10.3390/cancers13061375.

Authors

Sheng-Chao Wang¹, Li-Min Liao², Muhamad Ansar³, Shih-Yun Lin⁴, Wei-Wen Hsu⁵, Chih-Ming Su^{2

6}, Yu-Mei Chung⁷, Cai-Cing Liu⁸, Chin-Sheng Hung^{2

6}, Ruo-Kai Lin^{1

3

4

7

9}

Affiliations

¹ Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan.
² Division of General Surgery, Department of Surgery, Taipei Medical University Shuang Ho Hospital, No.291, Zhongzheng Rd., Zhonghe District, New Taipei City 23561, Taiwan.
³ Ph.D. Program in the Clinical Drug Development of Herbal Medicine, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan.
⁴ Graduate Institute of Pharmacognosy, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan.
⁵ Department of Statistics, College of Arts and Sciences, Kansas State University, 101 Dickens Hall, 1116 Mid-Campus Drive N, Manhattan, KS 66506-0802, USA.
⁶ Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, No. 250, Wuxing Street, Taipei 110, Taiwan.
⁷ Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan.
⁸ School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, 250 Wu-Hsing Street, Taipei 110, Taiwan.
⁹ Clinical trial center, Taipei Medical University Hospital, 252 Wu-Hsing Street, Taipei 110, Taiwan.

Abstract

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 CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (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 CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 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.

Keywords: CCDC181; DNA methylation; GCM2 and ITPRIPL1; Recursive Partitioning and Regression Trees; automatic detection; breast cancer; circulating cell-free DNA; early detection; surgical treatment response.

Abstract

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