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. 2024 Dec;26(12):1129-1148.
doi: 10.1016/j.jmoldx.2024.09.001. Epub 2024 Sep 24.

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort

Emily S Winn-Deen  1 , Laura T Bortolin  2 , Daniel Gusenleitner  2 , Kelly M Biette  2 , Karen Copeland  3 , Aleksandra Gentry-Maharaj  4 , Sophia Apostolidou  5 , Anthony D Couvillon  2 , Daniel P Salem  2 , Sanchari Banerjee  2 , Jonian Grosha  2 , Ibukunoluwapo O Zabroski  2 , Christopher R Sedlak  2 , Delaney M Byrne  2 , Bilal F Hamzeh  2 , MacKenzie S King  2 , Lauren T Cuoco  2 , Peter A Duff  2 , Brendan J Manning  2 , Troy B Hawkins  2 , Dawn Mattoon  2 , Toumy Guettouche  2 , Steven J Skates  6 , Amy Jamieson  7 , Jessica N McAlpine  7 , David Huntsman  8 , Usha Menon  5
Affiliations

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort

Emily S Winn-Deen et al. J Mol Diagn. 2024 Dec.

Abstract

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles from blood. The novel Mercy Halo Ovarian Cancer Test (OC Test) uses immunoaffinity capture of tumor-associated extracellular vesicles, followed by proximity-ligation real-time quantitative PCR to detect combinations of up to three biomarkers to maximize specificity, and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cutoff between cancer and noncancer. Performance was verified and compared with cancer antigen 125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, and 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI, 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI, 87.8%-99.2%), and an area under the curve of 0.97 (95% CI, 0.93-0.99) and detected 73.5% (61/83; 95% CI, 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, nonovarian cancers, and inflammatory conditions when compared with cancer antigen 125. The combined sensitivity and specificity of this new test suggests that it may have potential in OC screening.

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Conflict of interest statement

Disclosure Statement L.T.B., A.D.C., D.P.S., S.B., I.O.Z., D.M.B., M.S.K., L.T.C., B.J.M., T.B.H., T.G., and D.M. are current employees of Mercy BioAnalytics Inc. E.S.W.-D. is a retired Mercy BioAnalytics employee and is currently a paid consultant of Mercy BioAnalytics Inc. She was a full-time employee when this work was performed. K.M.B., P.A.D., J.G., D.G., B.F.H., and C.R.S. are former employees of Mercy BioAnalytics Inc., who were active employees at the time this work was performed. S.J.S. and K.C. are paid consultants for Mercy BioAnalytics Inc. A.J., J.N.M., and D.H. are employees of University of British Columbia and provided the patient samples used for the training study. A.G.-M., S.A., and U.M. are employees of University College London and provided the patient samples used for the verification study. They also report research collaborations with Cambridge University, QIMR Berghofer Medical Research Institute, Intelligent Lab on Fiber, RNA Guardian, Micronoma, Imperial College London, University of Innsbruck, and Dana Farber USA in the area of early detection of cancer. U.M. had stock ownership (2011 to 2021) awarded by University College London in Abcodia, which held the license for the Risk of Ovarian Cancer Algorithm. She has received grant funding from the Medical Research Council, Cancer Research UK, the National Institute for Health Research UK, the Eve Appeal, and the Australian National Health and Medical Research Council. She is also a member of Tina's Wish Scientific Advisory Board (United States) and the Research Advisory Panel, Yorkshire Cancer Research (United Kingdom). L.T.B. and D.P.S. are inventors on US patent number 11,085,089 B2, Systems, Compositions and Methods for Target Entity Detection (issued August 10, 2021). L.T.B., D.P.S., E.S.W.-D., D.G., K.M.B., and A.D.C. are inventors on US patent application 63/417309, Composition and Methods for Detection of Ovarian Cancer (filed October 18, 2022). U.M. holds patent number EP10178345.4 for Breast Cancer Diagnostics.

Figures

Figure 1
Figure 1
Overview of a biomarker combination design. A: Antibodies (Abs) are conjugated to magnetic beads (capture antibody) or double-stranded DNA (dsDNA) oligonucleotides (detection antibodies). B: After immunoaffinity capture, the extracellular vesicles are incubated with the dsDNA detection antibodies. Their single-stranded overhangs ligate only when in proximity to the complementary probe on a second antibody and are then quantitated using TaqMan real-time quantitative PCR (qPCR).
Figure 2
Figure 2
Overview of the design for the training and verification studies. Training study: The training study was composed of five cohorts of plasma samples sourced from academic and commercial biobanks and prospective collection. High-grade serous carcinoma (HGSC) and benign mass cohorts were used to develop a machine learning model to discriminate cancer from benign disease. A cutoff was determined in a separate cohort of healthy donors at a fixed specificity of 98.5%. Accuracy of this model was then assessed in cohorts of confounding inflammatory conditions and nonovarian cancers. Verification study: Performance of the model was assessed in samples from the UK Ovarian Cancer Population Study (UKOPS) as a forward evaluation in an independent cohort. OTB, Ontario Tumour Bank; OVCARE, Ovarian Cancer Research Program.
Figure 3
Figure 3
Linearity of the OC Test. Plasma was spiked with extracellular vesicles (EVs) isolated from the COV413A ovarian cancer cell line to cover the full range of OC Test scores.
Figure 4
Figure 4
OC Test and CA125 enzyme-linked immunosorbent assay performance in healthy controls and in ovarian cancers. A and C: Training study EDTA plasma samples are shown. B and D: The verification study serum samples are shown. The cutoff set between healthy controls and OC cases is shown as a red dotted line in each graph. HGSC, high-grade serous carcinoma; LGSC, low-grade serous carcinoma.
Figure 5
Figure 5
OC Test and CA125 enzyme-linked immunosorbent assay performance in benign ovarian conditions. A and C: Training study EDTA plasma samples are shown. B and D: The verification study serum samples are shown. The cutoff set between healthy controls and OC cases is shown as a red dotted line in each graph.
Figure 6
Figure 6
OC Test and CA125 enzyme-linked immunosorbent assay performance in nonovarian cancers and inflammatory conditions. A and C: Nonovarian (off-target cancer) samples are shown. B and D: The inflammatory condition samples are shown. The cutoff set between healthy controls and OC cases is shown as a red dotted line in each graph.
Figure 7
Figure 7
Correlation of the OC Test score with 10-year survival. Distribution of OC Test scores by survival status across all ovarian cancer cases in the verification study.
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