Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis
Abstract Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational anal...
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Nature Portfolio
2021
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oai:doaj.org-article:ce41cf4e5e8947abb7343fc75c596e932021-12-02T17:08:25ZCirculating cell-free DNA-based methylation patterns for breast cancer diagnosis10.1038/s41523-021-00316-72374-4677https://doaj.org/article/ce41cf4e5e8947abb7343fc75c596e932021-08-01T00:00:00Zhttps://doi.org/10.1038/s41523-021-00316-7https://doaj.org/toc/2374-4677Abstract Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography.Xianyu ZhangDezhi ZhaoYanling YinTing YangZilong YouDalin LiYanbo ChenYongdong JiangShouping XuJingshu GengYashuang ZhaoJun WangHui LiJinsheng TaoShan LeiZeyu JiangZhiwei ChenShihui YuJian-Bing FanDa PangNature PortfolioarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENnpj Breast Cancer, Vol 7, Iss 1, Pp 1-8 (2021) |
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 |
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Xianyu Zhang Dezhi Zhao Yanling Yin Ting Yang Zilong You Dalin Li Yanbo Chen Yongdong Jiang Shouping Xu Jingshu Geng Yashuang Zhao Jun Wang Hui Li Jinsheng Tao Shan Lei Zeyu Jiang Zhiwei Chen Shihui Yu Jian-Bing Fan Da Pang Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| description |
Abstract Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p < 0.05). In conclusion, we developed and tested a cfDNA methylation model for BC diagnosis with better performance than mammography. |
| format |
article |
| author |
Xianyu Zhang Dezhi Zhao Yanling Yin Ting Yang Zilong You Dalin Li Yanbo Chen Yongdong Jiang Shouping Xu Jingshu Geng Yashuang Zhao Jun Wang Hui Li Jinsheng Tao Shan Lei Zeyu Jiang Zhiwei Chen Shihui Yu Jian-Bing Fan Da Pang |
| author_facet |
Xianyu Zhang Dezhi Zhao Yanling Yin Ting Yang Zilong You Dalin Li Yanbo Chen Yongdong Jiang Shouping Xu Jingshu Geng Yashuang Zhao Jun Wang Hui Li Jinsheng Tao Shan Lei Zeyu Jiang Zhiwei Chen Shihui Yu Jian-Bing Fan Da Pang |
| author_sort |
Xianyu Zhang |
| title |
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| title_short |
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| title_full |
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| title_fullStr |
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| title_full_unstemmed |
Circulating cell-free DNA-based methylation patterns for breast cancer diagnosis |
| title_sort |
circulating cell-free dna-based methylation patterns for breast cancer diagnosis |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/ce41cf4e5e8947abb7343fc75c596e93 |
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