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Watrowski R, Schuster E, Hofstetter G, Fischer MB, Mahner S, Van Gorp T, Polterauer S, Zeillinger R, Obermayr E. Association of Four Interleukin-8 Polymorphisms (-251 A>T, +781 C>T, +1633 C>T, +2767 A>T) with Ovarian Cancer Risk: Focus on Menopausal Status and Endometriosis-Related Subtypes. Biomedicines 2024; 12:321. [PMID: 38397923 PMCID: PMC10886609 DOI: 10.3390/biomedicines12020321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/22/2024] [Accepted: 01/27/2024] [Indexed: 02/25/2024] Open
Abstract
Interleukin-8 (IL-8) is involved in the regulation of inflammatory processes and carcinogenesis. Single-nucleotide polymorphisms (SNPs) within the IL-8 gene have been shown to alter the risks of lung, gastric, or hepatocellular carcinomas. To date, only one study examined the role of IL-8 SNPs in ovarian cancer (OC), suggesting an association between two IL-8 SNPs and OC risk. In this study, we investigated four common IL-8 SNPs, rs4073 (-251 A>T), rs2227306 (+781 C>T), rs2227543 (+1633 C>T), and rs1126647 (+2767 A>T), using the restriction fragment length polymorphism (PCR-RFLP) technique. Our study included a cohort of 413 women of Central European descent, consisting of 200 OC patients and 213 healthy controls. The most common (73.5%) histological type was high-grade serous OC (HGSOC), whereas 28/200 (14%) patients had endometriosis-related (clear cell or endometrioid) OC subtypes (EROC). In postmenopausal women, three of the four investigated SNPs, rs4073 (-251 A>T), rs2227306 (+781 C>T), and rs2227543 (+1633 C>T), were associated with OC risk. Furthermore, we are the first to report a significant relationship between the T allele or TT genotype of SNP rs1126647 (+2767 A>T) and the EROC subtype (p = 0.02 in the co-dominant model). The TT homozygotes were found more than twice as often in EROC compared to other OC subtypes (39% vs. 19%, p = 0.015). None of the examined SNPs appeared to influence OC risk in premenopausal women, nor were they associated with the aggressive HGSOC subtype or the stage of disease at the initial diagnosis.
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Affiliation(s)
- Rafał Watrowski
- Department of Obstetrics and Gynecology, Helios Hospital Muellheim, Teaching Hospital of the University of Freiburg, Heliosweg 1, 79379 Muellheim, Germany;
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
- Molecular Oncology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center-Gynaecologic Cancer Unit, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria; (E.S.); (R.Z.)
| | - Eva Schuster
- Molecular Oncology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center-Gynaecologic Cancer Unit, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria; (E.S.); (R.Z.)
| | - Gerda Hofstetter
- Department of Pathology, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria;
| | - Michael B. Fischer
- Department of Blood Group Serology and Transfusion Medicine, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria;
- Center for Biomedical Technology, Department for Biomedical Research, Danube University Krems, Dr.-Karl-Dorrek-Straße 30, 3500 Krems, Austria
| | - Sven Mahner
- Department of Gynaecology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany;
- Department of Obstetrics and Gynaecology, University Hospital, Ludwig-Maximilians-University Munich, 81377 Munich, Germany
| | - Toon Van Gorp
- Division of Gynaecologic Oncology, University Hospital Leuven, 3000 Leuven, Belgium;
- Leuven Cancer Institute, Catholic University of Leuven, 3000 Leuven, Belgium
| | - Stefan Polterauer
- Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany;
| | - Robert Zeillinger
- Molecular Oncology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center-Gynaecologic Cancer Unit, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria; (E.S.); (R.Z.)
| | - Eva Obermayr
- Molecular Oncology Group, Department of Obstetrics and Gynecology, Comprehensive Cancer Center-Gynaecologic Cancer Unit, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria; (E.S.); (R.Z.)
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Stephens AN, Hobbs SJ, Kang SW, Bilandzic M, Rainczuk A, Oehler MK, Jobling TW, Plebanski M, Allman R. A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer. Cancers (Basel) 2023; 15:5267. [PMID: 37958440 PMCID: PMC10650329 DOI: 10.3390/cancers15215267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 10/27/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
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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Affiliation(s)
- Andrew N. Stephens
- Hudson Institute of Medical Research, Clayton 3168, Australia; (S.-W.K.); (M.B.); (A.R.)
- Department of Molecular and Translational Sciences, Monash University, Clayton 3168, Australia
- Cleo Diagnostics Ltd., Melbourne 3000, Australia; (S.J.H.); (R.A.)
| | - Simon J. Hobbs
- Cleo Diagnostics Ltd., Melbourne 3000, Australia; (S.J.H.); (R.A.)
| | - Sung-Woon Kang
- Hudson Institute of Medical Research, Clayton 3168, Australia; (S.-W.K.); (M.B.); (A.R.)
- Department of Molecular and Translational Sciences, Monash University, Clayton 3168, Australia
| | - Maree Bilandzic
- Hudson Institute of Medical Research, Clayton 3168, Australia; (S.-W.K.); (M.B.); (A.R.)
- Department of Molecular and Translational Sciences, Monash University, Clayton 3168, Australia
| | - Adam Rainczuk
- Hudson Institute of Medical Research, Clayton 3168, Australia; (S.-W.K.); (M.B.); (A.R.)
- Department of Molecular and Translational Sciences, Monash University, Clayton 3168, Australia
- Bruker Pty Ltd., Preston 3072, Australia
| | - Martin K. Oehler
- Department of Gynecological Oncology, Royal Adelaide Hospital, Adelaide 5000, Australia;
- Robinson Institute, University of Adelaide, Adelaide 5000, Australia
| | - Tom W. Jobling
- Department of Gynecology Oncology, Monash Medical Centre, Bentleigh East 3165, Australia;
| | - Magdalena Plebanski
- School of Health and Biomedical Sciences, RMIT University, Bundoora 3083, Australia;
| | - Richard Allman
- Cleo Diagnostics Ltd., Melbourne 3000, Australia; (S.J.H.); (R.A.)
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Diagnostics of Ovarian Tumors in Postmenopausal Patients. Diagnostics (Basel) 2022; 12:diagnostics12112619. [DOI: 10.3390/diagnostics12112619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 10/16/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022] Open
Abstract
Early diagnosis of ovarian cancer remains an urgent issue owing to the continuing trend towards increasing incidence along with only marginal improvements in mortality and 5-year survival rates. Furthermore, there is a lack of a clear formulation of the concept of pathogenesis. The diagnostic values of tumor markers, their potential advantages and disadvantages, and their combination with radiation imaging methods and transvaginal sonography are discussed. More advanced imaging techniques, such as computed tomography and magnetic resonance imaging have proven too expensive for widespread use. According to the World Health Organization, more than half of the world’s population does not have access to diagnostic imaging. Consequently, there is high demand for a low-cost, reliable, and safe imaging system for detecting and monitoring cancer. Currently, there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and for determining surgical access and optimal surgical intervention measures in postmenopausal patients are lacking. Medical microwave radiometry shows promising results yielding an accuracy of 90%.
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Liberto JM, Chen SY, Shih IM, Wang TH, Wang TL, Pisanic TR. Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review. Cancers (Basel) 2022; 14:2885. [PMID: 35740550 PMCID: PMC9221480 DOI: 10.3390/cancers14122885] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/06/2022] [Accepted: 06/08/2022] [Indexed: 02/04/2023] Open
Abstract
With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.
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Affiliation(s)
- Juliane M. Liberto
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
| | - Sheng-Yin Chen
- School of Medicine, Chang Gung University, 33302 Taoyuan, Taiwan;
| | - Ie-Ming Shih
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Tza-Huei Wang
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Tian-Li Wang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; (J.M.L.); (I.-M.S.); (T.-L.W.)
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA;
| | - Thomas R. Pisanic
- Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
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