无细胞DNA的多模态分析增强了早期乳腺癌与良性病变和健康个体的分化。

IF 4.5 1区 生物学 Q1 BIOLOGY
Thi Tuong Vi Van, Trung Hieu Tran, Thi Hue Hanh Nguyen, Van Thien Chi Nguyen, Dac Ho Vo, Giang Thi Huong Nguyen, Trong Hieu Nguyen, Kim Sang To, Anh Luan Nguyen, Cao Hong An Tran, Thanh Xuan Jasmine, Thi Loan Vo, Thi Huong Thoang Nai, Thuy Trang Tran, My Hoang Truong, Ngan Chau Tran, Thi Loc Le, Thi Hong Nhung Nguyen, Ngoc Hieu Tu, Thanh Son Tran, Bao Toan Le, Van Phong Tang, Pham Thanh Nhan Nguyen, Khac Tien Nguyen, Van Chien Ho, Xuan Vinh Nguyen, Nhu Nhat Tan Doan, Thi Trang Tran, Thi Minh Thu Tran, Vu Uyen Tran, Minh Phong Le, Thi Luyen Vu, Ba Linh Tieu, Huu Tam Phuc Nguyen, Luu Hong Dang Nguyen, Ngoc Minh Phan, Thi Van Phan, Thi Thanh Thuy Do, Thi Huyen Dao, Hung Sang Tang, Duy Sinh Nguyen, Hoa Giang, Minh Duy Phan, Hoai-Nghia Nguyen, Duc Hieu Vo, Le Son Tran
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引用次数: 0

摘要

背景:乳腺癌(BC)仍然是全球女性癌症相关死亡的第二大原因。基于循环肿瘤DNA (ctDNA)的液体活检为早期检测提供了一种有前途的无创方法;然而,鉴别恶性肿瘤与良性异常仍然是一个重大挑战。结果:在这里,我们开发了一种多模式方法来分析273名BC患者、108名乳腺良性疾病患者和134名健康对照者的cfDNA甲基化和片段组学模式。全基因组分析显示,在BC患者中存在明显的cfDNA拷贝数改变和胞嘧啶富集的切割位点。靶向测序进一步揭示了独特的甲基化模式,包括GPR126、KLF3和TLR10的高甲基化,以及TOP1和MAFB的低甲基化。我们的机器学习模型对I-II期癌症的AUC为0.90,特异性为93.6%,敏感性为62.1-66.3%。在有症状的人群中,BI-RADS 3、4和5类的敏感性分别为50.0%、68.2%和64.7%,特异性为96.1%。结论:这些发现强调了cfDNA生物标志物在提高BC检测和减少不必要的活检率方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

Background: Breast cancer (BC) remains the second leading cause of cancer-related mortality among women worldwide. Liquid biopsy based on circulating tumor DNA (ctDNA) offers a promising noninvasive approach for early detection; however, differentiating malignant tumors from benign abnormalities remains a significant challenge.

Results: Here, we developed a multimodal approach to analyze cfDNA methylation and fragmentomic patterns in 273 BC patients, 108 individuals with benign breast conditions, and 134 healthy controls. Genome-wide analyses revealed distinct cfDNA copy number alterations and cytosine-enriched cleavage sites in BC patients. Targeted sequencing further revealed unique methylation patterns, including hypermethylation in GPR126, KLF3, and TLR10 and hypomethylation in TOP1 and MAFB. Our machine-learning model achieved an AUC of 0.90, with 93.6% specificity and 62.1-66.3% sensitivity for stage I-II cancers. In symptomatic populations, sensitivities were 50.0%, 68.2%, and 64.7% for BI-RADS categories 3, 4, and 5, respectively, with 96.1% specificity.

Conclusions: These findings underscore the potential of cfDNA biomarkers to enhance BC detection and reduce the rate of unnecessary biopsies.

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来源期刊
BMC Biology
BMC Biology 生物-生物学
CiteScore
7.80
自引率
1.90%
发文量
260
审稿时长
3 months
期刊介绍: BMC Biology is a broad scope journal covering all areas of biology. Our content includes research articles, new methods and tools. BMC Biology also publishes reviews, Q&A, and commentaries.
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