Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer
Abstract Early detection is crucial to improve breast cancer (BC) patients’ outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnec...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-02-01
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| Series: | Molecular Cancer |
| Online Access: | https://doi.org/10.1186/s12943-021-01330-w |
| _version_ | 1818326097255727104 |
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| author | Jiaqi Liu Hengqiang Zhao Yukuan Huang Shouping Xu Yan Zhou Wei Zhang Jiaqi Li Yue Ming Xinyu Wang Sen Zhao Kai Li Xiying Dong Yunlong Ma Tianyi Qian Xinyi Chen Zeyu Xing Yan Zhang Hongyan Chen Zhihua Liu Da Pang Meng Zhou Zhihong Wu Xiaowo Wang Xiang Wang Nan Wu Jianzhong Su |
| author_facet | Jiaqi Liu Hengqiang Zhao Yukuan Huang Shouping Xu Yan Zhou Wei Zhang Jiaqi Li Yue Ming Xinyu Wang Sen Zhao Kai Li Xiying Dong Yunlong Ma Tianyi Qian Xinyi Chen Zeyu Xing Yan Zhang Hongyan Chen Zhihua Liu Da Pang Meng Zhou Zhihong Wu Xiaowo Wang Xiang Wang Nan Wu Jianzhong Su |
| author_sort | Jiaqi Liu |
| collection | DOAJ |
| description | Abstract Early detection is crucial to improve breast cancer (BC) patients’ outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78–0.79 to 0.93–0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms. |
| first_indexed | 2024-12-13T11:54:57Z |
| format | Article |
| id | doaj.art-8afa449857f044288daa003baf410e6b |
| institution | Directory Open Access Journal |
| issn | 1476-4598 |
| language | English |
| last_indexed | 2024-12-13T11:54:57Z |
| publishDate | 2021-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Molecular Cancer |
| spelling | doaj.art-8afa449857f044288daa003baf410e6b2022-12-21T23:47:15ZengBMCMolecular Cancer1476-45982021-02-012011710.1186/s12943-021-01330-wGenome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancerJiaqi Liu0Hengqiang Zhao1Yukuan Huang2Shouping Xu3Yan Zhou4Wei Zhang5Jiaqi Li6Yue Ming7Xinyu Wang8Sen Zhao9Kai Li10Xiying Dong11Yunlong Ma12Tianyi Qian13Xinyi Chen14Zeyu Xing15Yan Zhang16Hongyan Chen17Zhihua Liu18Da Pang19Meng Zhou20Zhihong Wu21Xiaowo Wang22Xiang Wang23Nan Wu24Jianzhong Su25Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Orthopedic Surgery, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesInstitute of Biomedical Big Data, Wenzhou Medical UniversityDepartment of Breast Surgery, Harbin Medical University Cancer HospitalCollege of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua UniversityMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua UniversityPET-CT Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Biomedical Big Data, Wenzhou Medical UniversityDepartment of Orthopedic Surgery, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesWenzhou Institute, University of Chinese Academy of SciencesDepartment of Orthopedic Surgery, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesInstitute of Biomedical Big Data, Wenzhou Medical UniversityDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeSchool of Life Science and Biotechnology, Harbin Institute of TechnologyState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgery, Harbin Medical University Cancer HospitalInstitute of Biomedical Big Data, Wenzhou Medical UniversityMedical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesMinistry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua UniversityDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Orthopedic Surgery, Beijing Key Laboratory for Genetic Research of Skeletal Deformity & Key Laboratory of Big Data for Spinal Deformities, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesInstitute of Biomedical Big Data, Wenzhou Medical UniversityAbstract Early detection is crucial to improve breast cancer (BC) patients’ outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78–0.79 to 0.93–0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms.https://doi.org/10.1186/s12943-021-01330-w |
| spellingShingle | Jiaqi Liu Hengqiang Zhao Yukuan Huang Shouping Xu Yan Zhou Wei Zhang Jiaqi Li Yue Ming Xinyu Wang Sen Zhao Kai Li Xiying Dong Yunlong Ma Tianyi Qian Xinyi Chen Zeyu Xing Yan Zhang Hongyan Chen Zhihua Liu Da Pang Meng Zhou Zhihong Wu Xiaowo Wang Xiang Wang Nan Wu Jianzhong Su Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer Molecular Cancer |
| title | Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer |
| title_full | Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer |
| title_fullStr | Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer |
| title_full_unstemmed | Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer |
| title_short | Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer |
| title_sort | genome wide cell free dna methylation analyses improve accuracy of non invasive diagnostic imaging for early stage breast cancer |
| url | https://doi.org/10.1186/s12943-021-01330-w |
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