Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass

Journal article (2024)

Authors

D.H.K. Gaillard Pattern Recognition and Bioinformatics - EEMCS
Pien Lof Center for Gynecologic Oncology Amsterdam, Amsterdam
Erik A. Sistermans Netherlands Cancer Institute, Vrije Universiteit Amsterdam
T.O. Mokveld Pattern Recognition and Bioinformatics - EEMCS
Hugo Mark Horlings Netherlands Cancer Institute
Constantijne H. Mom Center for Gynecologic Oncology Amsterdam, Amsterdam
M.J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS
M. J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS
Marcel J.T. Reinders Pattern Recognition and Bioinformatics - EEMCS
Marcel Reinders Pattern Recognition and Bioinformatics - EEMCS
Frédéric Amant University Hospital Leuven, Center for Gynecologic Oncology Amsterdam, Amsterdam
Daan van den Broek Netherlands Cancer Institute
Lodewyk F.A. Wessels Netherlands Cancer Institute
Lodewyk Wessels Netherlands Cancer Institute
L.F.A. Wessels Netherlands Cancer Institute
Research Group
Pattern Recognition and Bioinformatics (EEMCS) (TU Delft)
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Published Date

2024

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

Objective: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). Methods: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. Results: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. Conclusion: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.