Evaluation of cfDNA fragmentation characteristics in plasma for the diagnosis of lung cancer: A prospective cohort study.

IF 5.7 2区 医学 Q1 Medicine Cancer Science Pub Date : 2024-10-28 DOI:10.1111/cas.16360
Fudong Xu, Chong Wang, Hongxia Li, Bo Yu, Luyuan Chang, Feng Wang, Chaolian Long, Ling Bai, Hanqing Zhao, Nanying Che
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Abstract

Lung cancer is one of the most prevalent cancers worldwide, yet only approximately 16% of patients are diagnosed in early stage, highlighting the urgent need for novel, highly accurate detection models. In our study, patients with suspected lung cancer or lung disease, as identified through radiographic imaging, along with healthy individuals, were consecutively recruited from Beijing Chest Hospital. Circulating free DNA (cfDNA) was extracted from plasma samples, and low-depth whole-genome sequencing was performed to identify fragmentomic features for model construction. A total of 265 participants were prospectively enrolled, comprising 124 lung cancer patients and 141 noncancer individuals. The model we developed was based on four cfDNA fragmentation characteristics, including 20-bp breakpoint nucleotides motif, fragmentation size coverage, fragmentation size distribution, and copy number variation. In an independent test cohort, the model achieved an area under the curve (AUC) of 0.861 (95% CI: 0.781-0.942) and demonstrated a sensitivity of 70% (95% CI: 53.5%-83.4%) at a specificity of 89.4% (95% CI: 76.9%-96.5%). Notably, the model was also effective in detecting early-stage cancer, with an AUC of 0.808 (95% CI: 0.69-0.925). In summary, our lung cancer detection model shows strong screening capabilities by leveraging four cfDNA fragmentation characteristics, exhibiting robust performance in early cancer diagnosis.

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评估血浆中用于诊断肺癌的 cfDNA 片段特征:前瞻性队列研究
肺癌是全球发病率最高的癌症之一,但仅有约 16% 的患者能在早期确诊,这说明迫切需要新型、高精度的检测模型。在我们的研究中,我们从北京胸科医院连续招募了通过放射成像确定的疑似肺癌或肺部疾病患者以及健康人。我们从血浆样本中提取了循环游离 DNA(cfDNA),并进行了低深度全基因组测序,以确定用于构建模型的片段组特征。共有 265 人参与了前瞻性研究,其中包括 124 名肺癌患者和 141 名非癌症患者。我们建立的模型基于四个cfDNA片段特征,包括20-bp断点核苷酸主题、片段大小覆盖率、片段大小分布和拷贝数变异。在一个独立测试队列中,该模型的曲线下面积(AUC)为 0.861(95% CI:0.781-0.942),灵敏度为 70%(95% CI:53.5%-83.4%),特异度为 89.4%(95% CI:76.9%-96.5%)。值得注意的是,该模型在检测早期癌症方面也很有效,AUC 为 0.808(95% CI:0.69-0.925)。总之,我们的肺癌检测模型利用四种 cfDNA 片段特征显示出强大的筛查能力,在早期癌症诊断中表现出强劲的性能。
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来源期刊
Cancer Science
Cancer Science ONCOLOGY-
CiteScore
9.90
自引率
3.50%
发文量
406
审稿时长
17 weeks
期刊介绍: Cancer Science (formerly Japanese Journal of Cancer Research) is a monthly publication of the Japanese Cancer Association. First published in 1907, the Journal continues to publish original articles, editorials, and letters to the editor, describing original research in the fields of basic, translational and clinical cancer research. The Journal also accepts reports and case reports. Cancer Science aims to present highly significant and timely findings that have a significant clinical impact on oncologists or that may alter the disease concept of a tumor. The Journal will not publish case reports that describe a rare tumor or condition without new findings to be added to previous reports; combination of different tumors without new suggestive findings for oncological research; remarkable effect of already known treatments without suggestive data to explain the exceptional result. Review articles may also be published.
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