Aishan Nadire, Ju Siwei, Zheng Zhongqiu, Chen Yongxia, Meng Qingna, He Qina, Zhang Jiahang, Lang Jiaheng, Xie Bojian, Jin Lidan, Shen Jun, Lu Yi, Cai Yangjun, Ji Feiyang, Cao Feilin, Wang Linbo
Department of Surgical Oncology, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, Zhejiang, China.
Department of Thyroid and Breast Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, China.
Biomark Med. 2025 May;19(9):317-328. doi: 10.1080/17520363.2025.2483156. Epub 2025 Mar 26.
Breast cancer is one of the most prevalent cancers among women, and early diagnosis is crucial in reducing the mortality rate. This study aims to identify novel, reliable, and specific biomarkers for breast cancer diagnosis using 5-Hydroxymethylcytosine (5hmC) signatures in circulating cell-free DNA (cfDNA).
We utilized the sensitive 5hmC seal method to map 5hmC profiles in cfDNA samples from 203 breast cancer patients and 60 healthy individuals. Machine learning models were applied to identify 5hmC marker signatures with high sensitivity and specificity.
A global loss of 5hmC was observed in the blood samples from cancer patients compared to the control group. Several specific 5hmC marker signatures were identified, providing a basis for distinguishing between tumor and healthy individuals.
Our study offers a comprehensive understanding of genome-wide 5hmC in cfDNA from breast cancer patients, and identifies valuable epigenetic biomarkers for the minimally invasive diagnosis of breast cancer.
乳腺癌是女性中最常见的癌症之一,早期诊断对于降低死亡率至关重要。本研究旨在利用循环游离DNA(cfDNA)中的5-羟甲基胞嘧啶(5hmC)特征来识别用于乳腺癌诊断的新型、可靠且特异的生物标志物。
我们采用灵敏的5hmC封闭方法来绘制203例乳腺癌患者和60例健康个体的cfDNA样本中的5hmC图谱。应用机器学习模型来识别具有高灵敏度和特异性的5hmC标记特征。
与对照组相比,在癌症患者的血液样本中观察到5hmC整体缺失。鉴定出了几种特定的5hmC标记特征,为区分肿瘤个体和健康个体提供了依据。
我们的研究全面了解了乳腺癌患者cfDNA中全基因组范围的5hmC情况,并鉴定出了用于乳腺癌微创诊断的有价值的表观遗传生物标志物。