TY - JOUR
T1 - Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers
AU - Medina, Jamie E
AU - Annapragada, Akshaya V
AU - Lof, Pien
AU - Short, Sarah
AU - Bartolomucci, Adrianna L
AU - Mathios, Dimitrios
AU - Koul, Shashikant
AU - Niknafs, Noushin
AU - Noe, Michael
AU - Foda, Zachariah H
AU - Bruhm, Daniel C
AU - Hruban, Carolyn
AU - Vulpescu, Nicholas A
AU - Jung, Euihye
AU - Dua, Renu
AU - Canzoniero, Jenna V
AU - Cristiano, Stephen
AU - Adleff, Vilmos
AU - Symecko, Heather
AU - van den Broek, Daan
AU - Sokoll, Lori J
AU - Baylin, Stephen B
AU - Press, Michael F
AU - Slamon, Dennis J
AU - Konecny, Gottfried E
AU - Therkildsen, Christina
AU - Carvalho, Beatriz
AU - Meijer, Gerrit A
AU - Andersen, Claus Lindbjerg
AU - Domchek, Susan M
AU - Drapkin, Ronny
AU - Scharpf, Robert B
AU - Phallen, Jillian
AU - Lok, Christine A R
AU - Velculescu, Victor E
PY - 2024/9/30
Y1 - 2024/9/30
N2 - 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.
AB - 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.
U2 - 10.1158/2159-8290.CD-24-0393
DO - 10.1158/2159-8290.CD-24-0393
M3 - Journal article
C2 - 39345137
SN - 2159-8274
JO - Cancer Discovery
JF - Cancer Discovery
ER -