Application of semidefinite programming approach for detection of genomic copy number variations from peripheral blood in ovarian cancer
- 1Institute of Medical Statistics, Kiel University and University Medical Center Schleswig-Holstein
- 2Department of Gynecology and Obstetrics, Christian-Albrechts-University and University Medical Center Schleswig-Holstein
- 3Department of Gynaecology, Jena University Hospital
Abstract
Background: In 2025, we developed and published a detection test using digital droplet polymerase chain reaction (ddPCR) from cell-free DNA that indicates the presence of ovarian cancer (OC) in peripheral blood immediately before surgery with a sensitivity and specificity of 80%.
Methods: By applying a new classification approach based on semidefinite programming (SDP), we were able to significantly improve the predictive power of this test, which consists of six ddPCR combinations that indicate genomic imbalances. In addition to the previously used ratio of the ddPCR combination products, we now also include the sum of the ddPCR combination products.
Results: Data from the already published 57 controls without tumor background and a positive cohort of 15 OC were expanded by 5 additional OCs. With these data, we were able to define a separating boundary plane in a multidimensional space that better distinguishes the test results.
Conclusions: This new method allows the detection of cell-free tumor DNA from OC with high tumor burdens in the plasma with high sensitivity and specificity. Further studies using larger and independent cohorts are needed to evaluate the robustness of our approach to evaluate its potential use as a screening algorithm and to assess the diagnostic potential of minimally invasive blood-based ddPCR tests in OC.
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BibTeX
@article{kalab2026application,
title = {{Application of semidefinite programming approach for detection of genomic copy number variations from peripheral blood in ovarian cancer}},
author = {Michael Kalab and Arunabh Sharma and Anastasia Klopf and Lena Wahl and Huy Duc Le and Nina Hedemann and Annika Brauer and David Holthaus and Christoph Rogmans and Dirk Olaf Bauerschlag and Nicolai Maass and Marion van Mackelenbergh and Jörg Paul Weimer and Astrid Dempfle},
journal = {Frontiers in Oncology},
year = {2026},
month = oct,
doi = {10.3389/fonc.2026.1916039},
url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.1916039/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Application of semidefinite programming approach for detection of genomic copy number variations from peripheral blood in ovarian cancer
AU - Michael Kalab
AU - Arunabh Sharma
AU - Anastasia Klopf
AU - Lena Wahl
AU - Huy Duc Le
AU - Nina Hedemann
AU - Annika Brauer
AU - David Holthaus
AU - Christoph Rogmans
AU - Dirk Olaf Bauerschlag
AU - Nicolai Maass
AU - Marion van Mackelenbergh
AU - Jörg Paul Weimer
AU - Astrid Dempfle
PY - 2026
DA - 2026/10/19
JO - Frontiers in Oncology
DO - 10.3389/fonc.2026.1916039
UR - https://www.frontiersin.org/articles/10.3389/fonc.2026.1916039/full
AB - Background: In 2025, we developed and published a detection test using digital droplet polymerase chain reaction (ddPCR) from cell-free DNA that indicates the presence of ovarian cancer (OC) in peripheral blood immediately before surgery with a sensitivity and specificity of 80%. Methods: By applying a new classification approach based on semidefinite programming (SDP), we were able to significantly improve the predictive power of this test, which consists of six ddPCR combinations that indicate genomic imbalances. In addition to the previously used ratio of the ddPCR combination products, we now also include the sum of the ddPCR combination products. Results: Data from the already published 57 controls without tumor background and a positive cohort of 15 OC were expanded by 5 additional OCs. With these data, we were able to define a separating boundary plane in a multidimensional space that better distinguishes the test results. Conclusions: This new method allows the detection of cell-free tumor DNA from OC with high tumor burdens in the plasma with high sensitivity and specificity. Further studies using larger and independent cohorts are needed to evaluate the robustness of our approach to evaluate its potential use as a screening algorithm and to assess the diagnostic potential of minimally invasive blood-based ddPCR tests in OC.
SN - 2234-943X
ER -