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. 2023 Nov 2;15(21):5267.
doi: 10.3390/cancers15215267.

A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer

Andrew N Stephens  1   2   3 , Simon J Hobbs  3 , Sung-Woon Kang  1   2 , Maree Bilandzic  1   2 , Adam Rainczuk  1   2   4 , Martin K Oehler  5   6 , Tom W Jobling  7 , Magdalena Plebanski  8 , Richard Allman  3
Affiliations

A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer

Andrew N Stephens et al. Cancers (Basel). .

Abstract

Ovarian cancer remains the most lethal of gynecological malignancies, with the 5-year survival below 50%. Currently there is no simple and effective pre-surgical diagnosis or triage for patients with malignancy, particularly those with early-stage or low-volume tumors. Recently we discovered that CXCL10 can be processed to an inactive form in ovarian cancers and that its measurement has diagnostic significance. In this study we evaluated the addition of processed CXCL10 to a biomarker panel for the discrimination of benign from malignant disease. Multiple biomarkers were measured in retrospectively collected plasma samples (n = 334) from patients diagnosed with benign or malignant disease, and a classifier model was developed using CA125, HE4, Il6 and CXCL10 (active and total). The model provided 95% sensitivity/95% specificity for discrimination of benign from malignant disease. Positive predictive performance exceeded that of "gold standard" scoring systems including CA125, RMI and ROMA% and was independent of menopausal status. In addition, 80% of stage I-II cancers in the cohort were correctly identified using the multi-marker scoring system. Our data suggest the multi-marker panel and associated scoring algorithm provides a useful measurement to assist in pre-surgical diagnosis and triage of patients with suspected ovarian cancer.

Keywords: CXCL10; benign; biomarker; cancer; diagnostic; malignant; ovarian; triage.

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Conflict of interest statement

A.N.S. and R.A. are employees and executive board members for Cleo Diagnostics and declare a financial conflict of interest. T.W.J. is a non-executive board member for Cleo Diagnostics and declares a financial conflict of interest. S.J.H. was independently contracted by Cleo Diagnostics to perform statistical analyses and declares a financial conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Median marker values and linear discriminants for individual parameters used in scoring. (A) Individual analytes and/or calculated scores (ROMA, RMI2) within the cohort, according to disease type and stage. Sample numbers are provided in Table 1 and Table 2. * p ≤ 0.01; ** p ≤ 0.01; *** p ≤ 0.001; and **** p ≤ 0.0001. (B) Linear discriminant coefficients between groups for each parameter evaluated.
Figure 2
Figure 2
Performance of individual scoring systems for discrimination between benign and malignant disease. (A) ROC curves were constructed to assess each scoring system (multi-marker panel, CA125, RMI2 and ROMA). Cutoff values for each marker were as follows: multi-marker panel 3.68; CA125 > 35 U/mL, RMI > 200 and ROMA pre-menopausal >13.1% or post-menopausal >27.7%. (B) Violin plots demonstrating comparative scoring across all samples for each scoring system. Sample numbers are as indicated in Table 1 and Table 2.
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