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
| Autor: | Li Min Liao, Chih Ming Su, Muhamad Ansar, Sheng Chao Wang, Chin Sheng Hung, Shih Yun Lin, Yu Mei Chung, Cai Cing Liu, Ruo Kai Lin, Wei Wen Hsu |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Oncology Cancer Research medicine.medical_specialty Breast imaging CCDC181 GCM2 and ITPRIPL1 Recursive partitioning lcsh:RC254-282 Article 03 medical and health sciences breast cancer 0302 clinical medicine Breast cancer Internal medicine medicine early detection DNA methylation business.industry Area under the curve Cancer Methylation circulating cell-free DNA automatic detection lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens medicine.disease Recursive Partitioning and Regression Trees Circulating Cell-Free DNA surgical treatment response 030104 developmental biology 030220 oncology & carcinogenesis business |
| Zdroj: | Cancers, Vol 13, Iss 1375, p 1375 (2021) Cancers Volume 13 Issue 6 |
| ISSN: | 2072-6694 |
| DOI: | 10.3390/cancers13061375 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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