Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

IF 29.7 1区医学 Q1 ONCOLOGY

Cancer discovery Pub Date : 2024-09-30 DOI:10.1158/2159-8290.cd-24-0393

Jamie E. Medina, Akshaya V. Annapragada, Pien Lof, Sarah Short, Adrianna L. Bartolomucci, Dimitrios Mathios, Shashikant Koul, Noushin Niknafs, Michael Noe, Zachariah H. Foda, Daniel C. Bruhm, Carolyn Hruban, Nicholas A. Vulpescu, Euihye Jung, Renu Dua, Jenna V. Canzoniero, Stephen Cristiano, Vilmos Adleff, Heather Symecko, Daan van den Broek, Lori J. Sokoll, Stephen B. Baylin, Michael F. Press, Dennis J. Slamon, Gottfried E. Konecny, Christina Therkildsen, Beatriz Carvalho, Gerrit A. Meijer, Claus Lindbjerg. Andersen, Susan M. Domchek, Ronny Drapkin, Robert B. Scharpf, Jillian Phallen, Christine A.R. Lok, Victor E. Velculescu

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引用次数: 0

Abstract

Ovarian cancer is a leading cause of death for women worldwide in part due to ineffective screening methods. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model with the combined features, we detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV. Our approach differentiated benign masses from ovarian cancers with high accuracy (AUC=0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

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利用无细胞 DNA 片段组和蛋白质生物标记物早期检测卵巢癌

卵巢癌是全球妇女死亡的主要原因之一，部分原因是筛查方法无效。在这项研究中，我们利用全基因组无细胞DNA（cfDNA）片段组和蛋白质生物标志物（CA-125和HE4）分析，对591名患有卵巢癌、良性附件肿块或无卵巢病变的妇女进行了评估。利用具有综合特征的机器学习模型，我们检测出卵巢癌的特异性>99%，对I-IV期的敏感性分别为72%、69%、87%和100%。在相同的特异性下，单独使用 CA-125 检测 I-IV 期卵巢癌的特异性分别为 34%、62%、63% 和 100%。我们的方法能准确区分良性肿块和卵巢癌（AUC=0.88，95% CI=0.83-0.92）。这些结果在一个独立人群中得到了验证。这些研究结果表明，cfDNA片段组和蛋白质综合分析能高效检测卵巢癌，为无创卵巢癌筛查和诊断评估提供了一种新的便捷方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer discovery ONCOLOGY-

CiteScore

22.90

自引率

1.40%

发文量

838

审稿时长

6-12 weeks

期刊介绍： Cancer Discovery publishes high-impact, peer-reviewed articles detailing significant advances in both research and clinical trials. Serving as a premier cancer information resource, the journal also features Review Articles, Perspectives, Commentaries, News stories, and Research Watch summaries to keep readers abreast of the latest findings in the field. Covering a wide range of topics, from laboratory research to clinical trials and epidemiologic studies, Cancer Discovery spans the entire spectrum of cancer research and medicine.