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Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers
Cancer Discovery ( IF 29.7 ) 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
Cancer Discovery ( IF 29.7 ) 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
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.
中文翻译:
使用游离 DNA 片段组和蛋白质生物标志物早期检测卵巢癌
卵巢癌是全世界女性死亡的主要原因,部分原因是筛查方法无效。在这项研究中,我们使用全基因组无细胞 DNA (cfDNA) 片段组和蛋白质生物标志物(CA-125 和 HE4)分析来评估 591 名患有卵巢癌、良性附件肿块或无卵巢病变的女性。使用具有组合特征的机器学习模型,我们检测到卵巢癌,I-IV 期的特异性为 >99%,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 可以检测到 34%、62%、63% 和 100% 的 I-IV 期卵巢癌。我们的方法以高精度区分良性肿块和卵巢癌(AUC=0.88,95% CI=0.83-0.92)。这些结果在独立人群中得到了验证。这些发现表明,整合的 cfDNA 片段组和蛋白质分析可以高性能地检测卵巢癌,为非侵入性卵巢癌筛查和诊断评估提供一种新的可行方法。
更新日期:2024-09-30
中文翻译:
使用游离 DNA 片段组和蛋白质生物标志物早期检测卵巢癌
卵巢癌是全世界女性死亡的主要原因,部分原因是筛查方法无效。在这项研究中,我们使用全基因组无细胞 DNA (cfDNA) 片段组和蛋白质生物标志物(CA-125 和 HE4)分析来评估 591 名患有卵巢癌、良性附件肿块或无卵巢病变的女性。使用具有组合特征的机器学习模型,我们检测到卵巢癌,I-IV 期的特异性为 >99%,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 可以检测到 34%、62%、63% 和 100% 的 I-IV 期卵巢癌。我们的方法以高精度区分良性肿块和卵巢癌(AUC=0.88,95% CI=0.83-0.92)。这些结果在独立人群中得到了验证。这些发现表明,整合的 cfDNA 片段组和蛋白质分析可以高性能地检测卵巢癌,为非侵入性卵巢癌筛查和诊断评估提供一种新的可行方法。