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

SIMPLE SUMMARY: Ovarian cancer remains one of the most lethal malignancies for women, with a complex presentation and, typically, a late-stage diagnosis. Many common benign gynecological diseases can present with similar symptoms to malignancy, and exploratory surgery is required before a conclusive...

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Autores principales: Stephens, Andrew N., Hobbs, Simon J., Kang, Sung-Woon, Bilandzic, Maree, Rainczuk, Adam, Oehler, Martin K., Jobling, Tom W., Plebanski, Magdalena, Allman, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650329/
https://www.ncbi.nlm.nih.gov/pubmed/37958440
http://dx.doi.org/10.3390/cancers15215267
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author Stephens, Andrew N.
Hobbs, Simon J.
Kang, Sung-Woon
Bilandzic, Maree
Rainczuk, Adam
Oehler, Martin K.
Jobling, Tom W.
Plebanski, Magdalena
Allman, Richard
author_facet Stephens, Andrew N.
Hobbs, Simon J.
Kang, Sung-Woon
Bilandzic, Maree
Rainczuk, Adam
Oehler, Martin K.
Jobling, Tom W.
Plebanski, Magdalena
Allman, Richard
author_sort Stephens, Andrew N.
collection PubMed
description SIMPLE SUMMARY: Ovarian cancer remains one of the most lethal malignancies for women, with a complex presentation and, typically, a late-stage diagnosis. Many common benign gynecological diseases can present with similar symptoms to malignancy, and exploratory surgery is required before a conclusive diagnosis can be made. We have developed a new biomarker panel to assist in pre-surgical diagnosis and improve the clinical decision-making process. In a retrospectively collected cohort of 334 women, a multi-biomarker panel measured in plasma correctly identified malignant from benign samples with 95% sensitivity/specificity and out-performed current clinical methods. This new panel may provide a useful clinical adjunct to improve clinical workflows for patients with suspected ovarian malignancy. 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.
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spelling pubmed-106503292023-11-02 A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer Stephens, Andrew N. Hobbs, Simon J. Kang, Sung-Woon Bilandzic, Maree Rainczuk, Adam Oehler, Martin K. Jobling, Tom W. Plebanski, Magdalena Allman, Richard Cancers (Basel) Article SIMPLE SUMMARY: Ovarian cancer remains one of the most lethal malignancies for women, with a complex presentation and, typically, a late-stage diagnosis. Many common benign gynecological diseases can present with similar symptoms to malignancy, and exploratory surgery is required before a conclusive diagnosis can be made. We have developed a new biomarker panel to assist in pre-surgical diagnosis and improve the clinical decision-making process. In a retrospectively collected cohort of 334 women, a multi-biomarker panel measured in plasma correctly identified malignant from benign samples with 95% sensitivity/specificity and out-performed current clinical methods. This new panel may provide a useful clinical adjunct to improve clinical workflows for patients with suspected ovarian malignancy. 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. MDPI 2023-11-02 /pmc/articles/PMC10650329/ /pubmed/37958440 http://dx.doi.org/10.3390/cancers15215267 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stephens, Andrew N.
Hobbs, Simon J.
Kang, Sung-Woon
Bilandzic, Maree
Rainczuk, Adam
Oehler, Martin K.
Jobling, Tom W.
Plebanski, Magdalena
Allman, Richard
A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title_full A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title_fullStr A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title_full_unstemmed A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title_short A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer
title_sort novel predictive multi-marker test for the pre-surgical identification of ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650329/
https://www.ncbi.nlm.nih.gov/pubmed/37958440
http://dx.doi.org/10.3390/cancers15215267
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