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 - PubMed (original) (raw)
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 et al. Cancers (Basel). 2021.
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.
Conflict of interest statement
R.-K.L., C-.S.H., S.-C.W., Y.M.C. and C.-M.S. are named inventors on a patent owned by the Taipei Medical University, titled “Methods for early prediction, treatment response, recurrence and prognosis monitoring of breast cancer”.
Figures
Figure 1
Flowchart of the gene selection, study design, datasets and specimens used (i.e., the criteria and steps used for gene selection). For each step, the sample types and number of samples used for the analyses are indicated. ∆Avg β, β value in the tumor −β value in normal tissue; β, the DNA methylation level ranged from 0 (unmethylated) to 1 (completely methylated); BC, breast cancer; EPIC, Infinium MethylationEPIC array; methylation450K array, Infinium HumanMethylation450 BeadChip array; qMSP, quantitative methylation-specific PCR.
Figure 2
The boxplots for the DNA methylation levels of CCDC181, GCM2 and ITPRIPL1 in breast cancers and adjacent normal tissues from Taiwanese breast cancer patients. The assays were analyzed by qMSP and included 109 paired breast cancer, 24 paired colon cancer, 16 paired esophageal cancer, 33 paired lung cancer and 15 paired endometrial cancer tissues samples. An independent _t_-test was used to analyze the differences between breast cancer and other cancers samples. ** p ≤ 0.01 and *** p ≤ 0.001.
Figure 3
The methylation level of CCDC181, GCM2 and ITPRIPL1 in tissues and plasma specimens. Differentially methylated CpG heatmap of target genes in five paired Taiwanese BC patients (a) and 87 paired samples from the TCGA BC dataset (b). Methylation levels (average β values) at differentially methylated loci were identified using Illumina methylation array-based assays. (c) The box plot of the target gene methylation levels in 109 BC tumors and paired adjacent normal tissues. A paired Wilcoxon test was used to calculate group differences. (d) The box plot of target gene methylation levels in plasma of 141 BC and 200 healthy cases. A Mann–Whitney U test was used to calculate group differences. *** all p ≤ 0.001.
Figure 4
Stability and clinical validation of the automatic detection process for circulating methylated ccfDNA. (a) The PCR Ct value of the relative ccfDNA methylation level of the ACTB gene was used to compare the repeatability between the automatic process and manual process. (b) The PCR Ct value of the relative ccfDNA methylation level of the ACTB gene was used to compare the stability of the process in independent wells by parallel testing in two independent KingFisher™ Duo Prime Purification machines. (c) The decision tree model and ROC curve for the prediction of breast cancer in the training set by Recursive Partitioning and Regression Trees. (d) The decision tree model and ROC curve for the prediction of breast cancer in the test set by Recursive Partitioning and Regression Trees.
Figure 5
Consistency of the methylation levels of CCDC181, GCM2 and ITPRIPL1 between tissues and plasma in the same patients are shown. Representative figures of the target gene methylation levels determined by qMSP in BC tumor tissues and matched plasma in the same BC patients. Experiments were performed with three technical replicates. Bar charts for CCDC181 (a), GCM2 (b), and ITPRIPL1 (c) are shown. A Spearman’s rank correlation was used to calculate the correlation between two groups.
Figure 6
Changes in aberrant circulating hypermethylated CCDC181, GCM2 and ITPRIPL1 before and after surgery at different stages. Bar charts for CCDC181 (a), GCM2 (b), ITPRIPL1 (c), CA-153 (d), and CEA (e) are shown; ** p ≤ 0.001; *** p ≤ 0.001.
References
- Cancer Registry Annual Report. Health Promotion Administration Ministry of Health and Welfare; Taipei, Taiwan: 2018. [(accessed on 29 December 2020)]. Available online: https://www.hpa.gov.tw/Pages/Detail.aspx?nodeid=269&pid=13498.
Grants and funding
- MOST108-2320-B-038-020 and MOST 108-2745-8-038-002/Ministry of Science and Technology, Taiwan
- 108-5804-001-400/Ministry of Education
- 108YSR-03/Taipei Medical University-Shuang Ho Hospital
- 106IIT07/Taipei Medical University Hospital
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