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Ivansson E, Hedlund Lindberg J, Stålberg K, Sundfeldt K, Gyllensten U, Enroth S. Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women. Sci Rep 2024; 14:17288. [PMID: 39068297 PMCID: PMC11283551 DOI: 10.1038/s41598-024-68249-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024] Open
Abstract
Ovarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30-50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I-IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.
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Affiliation(s)
- Emma Ivansson
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, 75108, Uppsala, Sweden
| | - Julia Hedlund Lindberg
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, 75108, Uppsala, Sweden
| | - Karin Stålberg
- Department of Women's and Children's Health, Uppsala University, 75185, Uppsala, Sweden
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, 41685, Gothenburg, Sweden
| | - Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, 75108, Uppsala, Sweden
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, 75108, Uppsala, Sweden.
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2
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Zhang D, Xu R, Huo T, Liu Y, Hao Z, Sun Y, Xi X, Du X, Wang L, Du J. Perioperative management of a patient with unexpectedly detected early-stage ovarian mucinous carcinoma combined with progressive bulbar paralysis: a case report and literature review. BMC Womens Health 2024; 24:274. [PMID: 38704534 PMCID: PMC11069129 DOI: 10.1186/s12905-024-03117-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 04/26/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND Giant ovarian cysts (GOCs)complicated with progressive bulbar paralysis (PBP) are very rare, and no such literature about these cases have been reported. Through the diagnosis and treatment of this case, the perioperative related treatment of such patients was analyzed in detail, and early-stage ovarian mucinous carcinoma was unexpectedly found during the treatment, which provided reference for clinical diagnosis and treatment of this kind of diseases. CASE PRESENTATION In this article, we reported a 38-year-old female patient. The patient was diagnosed with PBP 2 years ago. Examination revealed a large fluid-dominated cystic solid mass in the pelvis measuring approximately 28.6×14.2×8.0 cm. Carbohydrate antigen19-9(CA19-9) 29.20 IU/mL and no other significant abnormalities were observed. The patient eventually underwent transabdominal right adnexal resection under regional anesthesia, epidural block. Postoperative pathology showed mucinous carcinoma in some areas of the right ovary. The patient was staged as stage IA, and surveillance was chosen. With postoperative follow-up 1 month later, her CA19-9 decreased to 14.50 IU/ml. CONCLUSIONS GOCs combined with PBP patients require a multi-disciplinary treatment. Preoperative evaluation of the patient's PBP progression, selection of the surgical approach in relation to the patient's fertility requirements, the nature of the ovarian cyst and systemic condition are required. Early mucinous ovarian cancer accidentally discovered after operation and needs individualized treatment according to the guidelines and the patient's situation. The patient's dysphagia and respiratory function should be closely monitored during the perioperative period. In addition, moral support from the family is also very important.
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Affiliation(s)
- Dingbei Zhang
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Ruibo Xu
- Department of Gynecology, Handan first hospital, Handan, 056000, Hebei, China
| | - Tingting Huo
- Department of Anaesthesiology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, 300072, China
| | - Ying Liu
- Department of Ultrasound, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Zengfang Hao
- Department of Pathology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Yao Sun
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Xiaoyu Xi
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Xiaoli Du
- Department of Gynecology, Traditional Chinese Medicine Hospital of Shijiazhuang, Hebei, 050000, China
| | - Lili Wang
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China
| | - Jiexian Du
- Department of Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China.
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Englisz A, Smycz-Kubańska M, Mielczarek-Palacz A. Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer. Diagnostics (Basel) 2024; 14:949. [PMID: 38732363 PMCID: PMC11083226 DOI: 10.3390/diagnostics14090949] [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: 02/16/2024] [Revised: 04/09/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.
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Affiliation(s)
- Aleksandra Englisz
- The Doctoral School, Medical University of Silesia, 40-055 Katowice, Poland;
| | - Marta Smycz-Kubańska
- Department of Immunology and Serology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland;
| | - Aleksandra Mielczarek-Palacz
- Department of Immunology and Serology, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 40-055 Katowice, Poland;
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Wang Z, Luo S, Chen J, Jiao Y, Cui C, Shi S, Yang Y, Zhao J, Jiang Y, Zhang Y, Xu F, Xu J, Lin Q, Dong F. Multi-modality deep learning model reaches high prediction accuracy in the diagnosis of ovarian cancer. iScience 2024; 27:109403. [PMID: 38523785 PMCID: PMC10959660 DOI: 10.1016/j.isci.2024.109403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/29/2023] [Accepted: 02/28/2024] [Indexed: 03/26/2024] Open
Abstract
We evaluated the diagnostic performance of a multimodal deep-learning (DL) model for ovarian mass differential diagnosis. This single-center retrospective study included 1,054 ultrasound (US)-detected ovarian tumors (699 benign and 355 malignant). Patients were randomly divided into training (n = 675), validation (n = 169), and testing (n = 210) sets. The model was developed using ResNet-50. Three DL-based models were proposed for benign-malignant classification of these lesions: single-modality model that only utilized US images; dual-modality model that used US images and menopausal status as inputs; and multi-modality model that integrated US images, menopausal status, and serum indicators. After 5-fold cross-validation, 210 lesions were tested. We evaluated the three models using the area under the curve (AUC), accuracy, sensitivity, and specificity. The multimodal model outperformed the single- and dual-modality models with 93.80% accuracy and 0.983 AUC. The Multimodal ResNet-50 DL model outperformed the single- and dual-modality models in identifying benign and malignant ovarian tumors.
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Affiliation(s)
- Zimo Wang
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Shuyu Luo
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Jing Chen
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Yang Jiao
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Chen Cui
- Illuminate, LLC, 6B, Building 5, Tianyu Xiangshan Garden, No. 33, Nongxuan Road, Futian District, Donghai Community, Xiangmihu Street, Futian District, Shenzhen 518000, China
- Microport Prophecy, 1601 ZhangDong Road, ZJHi-Tech Park, Shanghai 201203, China
| | - Siyuan Shi
- Illuminate, LLC, 6B, Building 5, Tianyu Xiangshan Garden, No. 33, Nongxuan Road, Futian District, Donghai Community, Xiangmihu Street, Futian District, Shenzhen 518000, China
- Microport Prophecy, 1601 ZhangDong Road, ZJHi-Tech Park, Shanghai 201203, China
| | - Yang Yang
- Illuminate, LLC, 6B, Building 5, Tianyu Xiangshan Garden, No. 33, Nongxuan Road, Futian District, Donghai Community, Xiangmihu Street, Futian District, Shenzhen 518000, China
- Microport Prophecy, 1601 ZhangDong Road, ZJHi-Tech Park, Shanghai 201203, China
| | - Junyi Zhao
- University of Shanghai for Science and Technology, Shanghai 201203, China
| | - Yitao Jiang
- Illuminate, LLC, 6B, Building 5, Tianyu Xiangshan Garden, No. 33, Nongxuan Road, Futian District, Donghai Community, Xiangmihu Street, Futian District, Shenzhen 518000, China
- Microport Prophecy, 1601 ZhangDong Road, ZJHi-Tech Park, Shanghai 201203, China
| | - Yujuan Zhang
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Fanhua Xu
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Jinfeng Xu
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Qi Lin
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
| | - Fajin Dong
- Second Clinical College of Jinan University, Department of Ultrasound, Shenzhen People’s Hospital, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen Medical Ultrasound Engineering Center. Shenzhen, Guangdong 518020, China
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Hedlund Lindberg J, Widgren A, Ivansson E, Gustavsson I, Stålberg K, Gyllensten U, Sundfeldt K, Bergquist J, Enroth S. Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid. iScience 2024; 27:109001. [PMID: 38352226 PMCID: PMC10863317 DOI: 10.1016/j.isci.2024.109001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 10/24/2023] [Accepted: 01/19/2024] [Indexed: 02/16/2024] Open
Abstract
Early detection is key for increased survival in ovarian cancer, but no general screening program exists today due to lack of biomarkers and overall cost versus benefit over traditional clinical methods. Here, we used dried cervico-vaginal fluid (CVF) as sampling matrix coupled with mass spectrometry for detection of protein biomarkers. We find that self-collected CVF on paper cards yields robust results and is suitable for high-throughput proteomics. Artificial intelligence-based methods were used to identify an 11-protein panel that separates cases from controls. In validation data, the panel achieved a sensitivity of 0.97 (95% CI 0.91-1.00) at a specificity of 0.67 (0.40-0.87). Analyses of samples collected prior to development of symptoms indicate that the panel is informative also of future risk of disease. Dried CVF is used in cervical cancer screening, and our results opens the possibility for a screening program also for ovarian cancer, based on self-collected CVF samples.
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Affiliation(s)
- Julia Hedlund Lindberg
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Anna Widgren
- Analytical Chemistry, Department of Chemistry-Biomedical Center, Uppsala University, SE-75237 Uppsala, Sweden
| | - Emma Ivansson
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Inger Gustavsson
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, SE-75185 Uppsala, Sweden
| | - Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-41685 Gothenburg, Sweden
| | - Jonas Bergquist
- Analytical Chemistry, Department of Chemistry-Biomedical Center, Uppsala University, SE-75237 Uppsala, Sweden
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
- Swedish Collegium for Advanced Study, Thunbergsvägen 2, SE-752 38 Uppsala, Sweden
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Garg P, Mohanty A, Ramisetty S, Kulkarni P, Horne D, Pisick E, Salgia R, Singhal SS. Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers. Biochim Biophys Acta Rev Cancer 2023; 1878:189026. [PMID: 37980945 DOI: 10.1016/j.bbcan.2023.189026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 11/09/2023] [Accepted: 11/14/2023] [Indexed: 11/21/2023]
Abstract
Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the greatest threat to world health, with early identification being crucial to patient outcomes and survival rates. The application of machine learning (ML) and artificial intelligence (AI) approaches to the study of gynecological cancer has shown potential to revolutionize cancer detection and diagnosis. The current review outlines the significant advancements, obstacles, and prospects brought about by AI and ML technologies in the timely identification and accurate diagnosis of different types of gynecological cancers. The AI-powered technologies can use genomic data to discover genetic alterations and biomarkers linked to a particular form of gynecologic cancer, assisting in the creation of targeted treatments. Furthermore, it has been shown that the potential benefits of AI and ML technologies in gynecologic tumors can greatly increase the accuracy and efficacy of cancer diagnosis, reduce diagnostic delays, and possibly eliminate the need for needless invasive operations. In conclusion, the review focused on the integrative part of AI and ML based tools and techniques in the early detection and exclusion of various cancer types; together with a collaborative coordination between research clinicians, data scientists, and regulatory authorities, which is suggested to realize the full potential of AI and ML in gynecologic cancer care.
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Affiliation(s)
- Pankaj Garg
- Department of Chemistry, GLA University, Mathura, Uttar Pradesh 281406, India
| | - Atish Mohanty
- Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA
| | - Sravani Ramisetty
- Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA
| | - Prakash Kulkarni
- Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA
| | - David Horne
- Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA
| | - Evan Pisick
- Department of Medical Oncology, City of Hope, Chicago, IL 60099, USA
| | - Ravi Salgia
- Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA
| | - Sharad S Singhal
- Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA.
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Brincat MR, Mira AR, Lawrence A. Current and Emerging Strategies for Tubo-Ovarian Cancer Diagnostics. Diagnostics (Basel) 2023; 13:3331. [PMID: 37958227 PMCID: PMC10647517 DOI: 10.3390/diagnostics13213331] [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: 09/04/2023] [Revised: 10/22/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Tubo-ovarian cancer is the most lethal gynaecological cancer. More than 75% of patients are diagnosed at an advanced stage, which is associated with poorer overall survival. Symptoms at presentation are vague and non-specific, contributing to late diagnosis. Multimodal risk models have improved the diagnostic accuracy of adnexal mass assessment based on patient risk factors, coupled with findings on imaging and serum-based biomarker tests. Newly developed ultrasonographic assessment algorithms have standardised documentation and enable stratification of care between local hospitals and cancer centres. So far, no screening test has proven to reduce ovarian cancer mortality in the general population. This review is an update on the evidence behind ovarian cancer diagnostic strategies.
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Affiliation(s)
- Mark R. Brincat
- Department of Gynaecological Oncology, Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK
| | - Ana Rita Mira
- Department of Gynaecological Oncology, Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK
- Hospital Garcia de Orta, 2805-267 Almada, Portugal
| | - Alexandra Lawrence
- Department of Gynaecological Oncology, Royal London Hospital, Barts Health NHS Trust, London E1 1FR, UK
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Shan Y, Mao B, Jin Y, You Y, Wang Y, Shen K, Li L. Expression of DDB1 is associated with subtypes of epithelial ovarian cancer and predicts clinical outcomes. Tissue Cell 2023; 82:102072. [PMID: 36934683 DOI: 10.1016/j.tice.2023.102072] [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: 07/18/2022] [Revised: 02/28/2023] [Accepted: 03/14/2023] [Indexed: 03/17/2023]
Abstract
BACKGROUND Ovarian cancer is the most lethal gynaecological malignancy. Damage specific DNA-binding protein 1 (DDB1) functions in nucleotide-excision repair and has been reported to be involved in cancer development. In this study, we aimed to determine the expression levels of DDB1 and their association with the clinical outcomes of patients with ovarian cancer. METHODS Tissue arrays were performed on 54 epithelial ovarian cancer (EOC) samples. Immunohistochemistry was performed to determine DDB1 expression. DDB1 expression levels among different EOC subtypes were analysed via one-way analysis of variance using SPSS Statistics 19.0. Correlation between DDB1 expression and chemotherapy course/progression-free survival (PFS) of patients was determined via Kaplan-Meier survival analysis using GraphPad Prism 5. Moreover, knockdown of DDB1 in ovarian cancer cells ES2 and OVCAR3 was used to preliminarily validate the role of DDB1. RESULTS DDB1 was detected in the cytoplasm, especially in the nucleus, of all subtypes of EOC. However, DDB1 expression levels were significantly different between clear cell carcinoma and low-grade serous carcinoma (P = 0.022) and clear cell carcinoma and endometrioid cancer (P = 0.016). In addition, DDB1 expression was not significantly correlated with chemotherapy course (P = 0.433) or PFS (P = 0.566). High expression levels of DDB1 were correlated with significantly worse overall survival (P = 0.017) in patients with EOC. In addition, DDB1 knockdown in ovarian cancer cells decreased their proliferation in vitro. CONCLUSION Our results revealed that DDB1 expression is heterogeneous in ovarian cancer, suggesting its use as a potential biomarker for poor survival in ovarian cancer.
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Affiliation(s)
- Ying Shan
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China
| | - Banyun Mao
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China; Department of Gynecology and Obstetrics, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, No. 32, West Second Section, First Ring Road, Chengdu, Sichuan Province 610072, China
| | - Ying Jin
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China
| | - Yan You
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China
| | - Yongxue Wang
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China
| | - Keng Shen
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China.
| | - Lei Li
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuai Fu Yuan, Eastern District, Beijing 100730, China.
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9
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Yao Q, Chen W, Gao F, Wu Y, Zhou L, Xu H, Yu J, Zhu X, Wang L, Li L, Cao H. Characteristic Analysis of Featured Genes Associated with Cholangiocarcinoma Progression. Biomedicines 2023; 11:biomedicines11030847. [PMID: 36979826 PMCID: PMC10045321 DOI: 10.3390/biomedicines11030847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/28/2023] [Accepted: 03/07/2023] [Indexed: 03/14/2023] Open
Abstract
The noninvasive diagnosis of cholangiocarcinoma (CCA) is insufficiently accurate. Therefore, the discovery of new prognostic markers is vital for the understanding of the CCA mechanism and related treatment. The information on CCA patients in The Cancer Genome Atlas database was used for weighted gene co-expression network analysis. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to analyze the modules of interest. By using receiver operating characteristic (ROC) analysis to analyze the Human Protein Atlas (HPA), the featured genes were subsequently verified. In addition, clinical samples and GSE119336 cohort data were also collected for the validation of these hub genes. Using WGCNA, we identified 61 hub genes that regulated the progression and prognosis of CCA. Eight hub genes (VSNL1, TH, PCP4, IGDCC3, RAD51AP2, MUC2, BUB1, and BUB1B) were identified which exhibited significant interactions with the tumorigenic mechanism and prognosis of CCA. In addition, GO and KEGG clarified that the blue and magenta modules were involved with chromosome segregation, mitotic and oocyte meiosis, the cell cycle, and sister chromatid segregation. Four hub genes (VSNL1, PCP4, BUB1, and BUB1B) were also verified as featured genes of progression and prognosis by the GSE119336 cohort data and five human tissue samples.
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Affiliation(s)
- Qigu Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Wenyi Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Feiqiong Gao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Yuchen Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Lingling Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Haoying Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Jong Yu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
| | - Xinli Zhu
- Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China
| | - Lan Wang
- Key Laboratory of Diagnosis and Treatment of Aging and Physic-Chemical Injury Diseases of Zhejiang Province, 79 Qingchun Road, Hangzhou 310003, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan 250117, China
| | - Hongcui Cao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Hangzhou 310003, China; (Q.Y.)
- Key Laboratory of Diagnosis and Treatment of Aging and Physic-Chemical Injury Diseases of Zhejiang Province, 79 Qingchun Road, Hangzhou 310003, China
- Correspondence: ; Tel.: +86-571-87236451; Fax: +86-571-87236459
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Ain QU, Muhammad S, Hai Y, Peiling L. The role of urine and serum biomarkers in the early detection of ovarian epithelial tumours. J OBSTET GYNAECOL 2023; 42:3441-3449. [PMID: 36757337 DOI: 10.1080/01443615.2022.2151352] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Ovarian cancer (OC) is one of the leading causes of gynaecological cancer mortality in women worldwide. If detected at an early stage (I, II), OC has a 90% 5-year survival rate; nevertheless, symptoms are often hidden, leading to late-stage (III, IV) diagnosis and a poor prognosis. The current diagnostic procedures, such as a pelvic exam, transvaginal ultrasound, CA-125 blood tests, serum HE4 tests and multivariate index assays (MIA), are insufficient. Sadly, surgery is frequently required to confirm a positive diagnosis. Therefore, there has been an increased interest in different biomarkers using a non-invasive test as a tool for the earlier diagnosis of OC to resolve the need for precise and non-invasive diagnostic methods. This review article aims to investigate how biomarkers influence early OC detection and to emphasise the role of using a combination of serum biomarkers panel rather than a single biomarker. In addition, this review provides insights into the current serum biomarkers, urine biomarkers and other emerging biomarkers in the early detection of OC for better specificity and sensitivity and to improve the overall survival (OS) rate.
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Affiliation(s)
- Qurat Ul Ain
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Harbin medical university, Harbin, PR China
| | - Shan Muhammad
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China
| | - Yang Hai
- Department of International Education, Harbin Medical University, Harbin, PR China
| | - Li Peiling
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Harbin medical university, Harbin, PR China
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11
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Wang R, Li X, Li S, Fang S, Zhao C, Yang H, Yang Z. Clinical value of O-RADS combined with serum CA125 and HE4 for the diagnosis of ovarian tumours. Acta Radiol 2023; 64:821-828. [PMID: 35291856 DOI: 10.1177/02841851221087376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Ovarian tumors (OTs) are common gynecological tumors in women. It is very important to correctly distinguish benign and malignant OTs. PURPOSE To assess the diagnostic performance of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) and evaluate the clinical value of O-RADS combined with serum carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) in differentiating benign from malignant OTs. MATERIAL AND METHODS A retrospective analysis was performed on 431 cases including pathology and clinical data. The receiver operating characteristic (ROC) curve was drawn, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. RESULTS In premenopausal women, O-RADS and O-RADS combined with serum CA125 and HE4 showed sensitivity at 92.2% and 94.8%, specificity at 91.8% and 93.4%, and accuracy at 91.9% and 93.8%, respectively. In postmenopausal women, the sensitivity of O-RADS, O-RADS combined with serum CA125 and HE4 was 94.8% and 95.8%, specificity was 83.9% and 93.6%, and accuracy was 90.5% and 95.6%, respectively. The sensitivity, specificity, and accuracy of O-RADS combined with CA125 and HE4 in premenopausal and postmenopausal women were higher than that of O-RADS (P<0.05). CONCLUSION O-RADS has high diagnostic performance in OTs. When O-RADS is combined with CA125 and HE4 in the diagnosis of OTs, the sensitivity and specificity are improved, which is helpful to improve the diagnostic efficiency of OTs and has high clinical application value.
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Affiliation(s)
- Rongling Wang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Xiumei Li
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Shuqin Li
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Shibao Fang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Cheng Zhao
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Hui Yang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
| | - Zongli Yang
- Department of Abdominal Ultrasound, 235960the Affiliated Hospital of Qingdao University, Qingdao, PR China
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Popovici D, Socolov R, Hurjui L, Stan C, Bălan R, Hurjui I, Tărniceriu CC, Bereşteanu S, Hurjui IA. Chistadenom mucinos gigant recidivat – caz clinic. GINECOLOGIA.RO 2023. [DOI: 10.26416/gine.39.1.2023.7790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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13
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IETA Ultrasonic Features Combined with GI-RADS Classification System and Tumor Biomarkers for Surveillance of Endometrial Carcinoma: An Innovative Study. Cancers (Basel) 2022; 14:cancers14225631. [PMID: 36428723 PMCID: PMC9688181 DOI: 10.3390/cancers14225631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/23/2022] [Accepted: 10/28/2022] [Indexed: 11/18/2022] Open
Abstract
Objectives: We were the first to combine IETA ultrasonic features with GI-RADS and tumor biomarkers for the surveillance of endometrial carcinoma. The aim was to evaluate the efficacy of single IETA ultrasonography GI-RADS classification and combined tumor biomarkers in differentiating benign and malignant lesions in the uterine cavity and endometrium. Methods: A total of 497 patients with intrauterine and endometrial lesions who had been treated surgically between January 2017 and December 2021 were enrolled; all of them had undergone ultrasound examinations before surgery. We analyzed the correlation between the terms of ultrasonic signs of the uterine cavity and endometrial lesions defined by the expert consensus of IETA and the benign and malignant lesions and then classified these ultrasonic signs by GI-RADS. In addition, the tumor biomarkers CA125, CA15-3, CA19-9 and HE4 were combined by adjusting the classification. The results of the comprehensive analysis were compared with pathological results to analyze their diagnostic efficacy. Results: (1) The statistic analysis confirmed that there were seven independent predictors of malignant lesions, including thickened endometrium (premenopause ≥ 18.5 mm, postmenopause ≥ 15.5 mm), non-uniform endometrial echogenicity (heterogeneous with irregular cysts), endometrial midline appearance (not defined), the endometrial-myometrial junction (interrupted or not defined), intracavitary fluid (ground glass or "mixed" echogenicity), color score (3~4 points) and vascular pattern (focal origin multiple vessels or multifocal origin multiple vessels). (2) In traditional ultrasound GI-RADS (U-T-GI-RADS), if category 4a was taken as the cut-off value of benign and malignant, the diagnostic sensitivity, specificity, PPV, NPV and diagnostic accuracy were 97.2%, 65.2%, 44.0%, 98.8% and 72.2%, respectively, and the area under the ROC curve (AUC) was 0.812. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 88.1%, 92.0%, 75.6%, 96.5% and 91.2%, 0.900, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.5%, 93.2%, 93.4%, 93.4% and 0.868, respectively, when taking category 5 as the cutoff point. In modified ultrasound GI-RADS (U-M-GI-RADS), if 4a was taken as the cut-off value, The diagnostic efficacy was the same as U-T-GI-RADS. If 4b was taken as the cut-off value, the diagnostic sensitivity, specificity, PPV, NPV, diagnostic accuracy and AUC were 88.1%, 92.3%, 76.2%, 96.5%, 91.3% and 0.902, respectively. If 4c was taken as the cutoff point, the diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 75.2%, 98.7%, 94.3%, 93.4%, 93.6% and 0.870, respectively. The diagnostic sensitivity, specificity, PPV, NPV diagnostic accuracy and AUC were 66.1%, 99.7%, 98.6%, 91.3%, 92.4% and 0.829, respectively, if taking category 5 as the cutoff point. (3) In the comprehensive diagnostic method of U-T-GI-RADS combined tumor biomarkers results, the AUC of class 4a, 4b and 5 as the cutoff value was 0.877, 0.888 and 0.738, respectively. The AUC of class 4a, 4b, 4c and 5 as the cutoff value in the comprehensive diagnostic method of U-M-GI-RADS combined tumor biomarkers results was 0.877, 0.888, 0.851 and 0.725, respectively. There was no significant difference in diagnostic efficiency between the two comprehensive diagnostic methods. Conclusions: In this study, no matter which diagnostic method was used, the best cutoff value for predicting malignant EC was ≥GI-RADS 4b. The GI-RADS classification had good performance in discriminating EC. The tumor biomarkers, CA125, CA19-9, CA15-3 and HE4, could improve the diagnostic efficacy for preoperative endometrial carcinoma assessment.
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Punzón-Jiménez P, Lago V, Domingo S, Simón C, Mas A. Molecular Management of High-Grade Serous Ovarian Carcinoma. Int J Mol Sci 2022; 23:13777. [PMID: 36430255 PMCID: PMC9692799 DOI: 10.3390/ijms232213777] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/04/2022] [Accepted: 11/07/2022] [Indexed: 11/11/2022] Open
Abstract
High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.
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Affiliation(s)
- Paula Punzón-Jiménez
- Carlos Simon Foundation, INCLIVA Health Research Institute, 46010 Valencia, Spain
| | - Victor Lago
- Department of Gynecologic Oncology, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Department of Obstetrics and Gynecology, CEU Cardenal Herrera University, 46115 Valencia, Spain
| | - Santiago Domingo
- Department of Gynecologic Oncology, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Department of Pediatrics, Obstetrics and Gynecology, Universidad de Valencia, 46010 Valencia, Spain
| | - Carlos Simón
- Carlos Simon Foundation, INCLIVA Health Research Institute, 46010 Valencia, Spain
- Department of Pediatrics, Obstetrics and Gynecology, Universidad de Valencia, 46010 Valencia, Spain
- Department of Pediatrics, Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Harvard University, Boston, MA 02215, USA
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Aymara Mas
- Carlos Simon Foundation, INCLIVA Health Research Institute, 46010 Valencia, Spain
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15
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de Melo ALL, Linder A, Sundfeldt K, Lindquist D, Hedman H. Single-molecule array assay reveals the prognostic impact of plasma LRIG1 in ovarian carcinoma. Acta Oncol 2022; 61:1425-1433. [PMID: 36326616 DOI: 10.1080/0284186x.2022.2140016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Ovarian carcinoma is the eighth most common cause of cancer death in women worldwide. The disease is predominantly diagnosed at a late stage. This contributes to high recurrence rates, eventually leading to the development of treatment-resistant disease. Leucine-rich repeats and immunoglobulin-like domains protein 1 (LRIG1) is a transmembrane protein that functions as a tumor suppressor and regulator of growth factor signaling. LRIG1 levels have not been investigated in human plasma previously. MATERIALS AND METHODS A quantitative LRIG1-specific single molecule array assay was developed and validated. LRIG1 levels were quantified in plasma samples from 486 patients with suspicious ovarian masses. RESULTS Among women with ovarian carcinoma, LRIG1 levels were significantly elevated compared to women with benign or borderline type tumors. High LRIG1 plasma levels were associated with worse overall survival and shorter disease-free survival both in the group of all malignant cases and among the stage 3 cases only. LRIG1 was an independent prognostic factor in patients with stage 3 ovarian carcinoma. CONCLUSION LRIG1 plasma levels were elevated in patients with ovarian carcinoma, and high levels were associated with poor prognosis, suggesting that LRIG1 might be an etiologic factor and a potentially useful biomarker in ovarian carcinoma.
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Affiliation(s)
| | - Anna Linder
- Sahlgrenska Center for Cancer research, Department of Gynecology and Obstetrics, Institute of clinical Sciences, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Karin Sundfeldt
- Sahlgrenska Center for Cancer research, Department of Gynecology and Obstetrics, Institute of clinical Sciences, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - David Lindquist
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Håkan Hedman
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
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16
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Guo F, Liu Y, Lu J, Wu Z, Zhu X. Human chorionic gonadotropin elevation in gliomatosis peritonei complicated with immature teratoma: A case report and review of the literature. Medicine (Baltimore) 2022; 101:e31305. [PMID: 36316907 PMCID: PMC9622604 DOI: 10.1097/md.0000000000031305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
RATIONALE Gliomatosis peritonei (GP) refers to the implantation of glial tissue on the visceral and parietal peritoneal surface, often associated with immature teratoma. It is a rare condition and the pathogenesis is not fully understood. In addition, the indistinguishable radiological appearance of immature and mature teratomas, and limited pathology samples make an accurate diagnosis difficult in most cases. More importantly, patients are also at risk of recurrence after surgery. This report aims to describe the process of diagnosis and treatment of GP with immature teratoma. PATIENT CONCERNS The patient, a 38-year-old woman presented with GP complicated with immature teratoma after laparoscopic ovarian cyst excision. DIAGNOSES On physical examination, a 15 cm-pelvic mass, with poor mobility, was palpated. And tumor marker demonstrated a moderate increase in α-fetoprotein and carbohydrate antigen 125. We suspected malignancy according to the comprehensive preoperative evaluation, the postoperative pathology revealed an immature teratoma of the left ovary and complicated with gliomatosis peritonei. Three months after the second surgery, possible recurrence of immature teratoma was considered and the patient underwent the third laparotomy. But the postoperative pathology indicated mature teratoma and mature glial components in the pelvic lesions. INTERVENTIONS AND OUTCOME The patient underwent 2 more surgical resections after the initial resection and 3 cycles of bleomycin, etoposide, and cisplatin regimen chemotherapy. She was regularly followed up in the outpatient after surgery, and no recurrence has been reported in the pelvic cavity till date. LESSON The case illuminated that the primary diagnosis of GP complicated with immature teratoma is critical but highly challenging for both gynecologists and pathologists and more attention should be paid to "GP complicated with immature cystic teratoma" patients to avoid inappropriate treatment.
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Affiliation(s)
- Fei Guo
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Yukai Liu
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Jiaqi Lu
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Zhiyong Wu
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
| | - Xiaoyong Zhu
- Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- * Correspondence: Xiaoyong Zhu, Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China (e-mail: )
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Enroth S, Ivansson E, Lindberg JH, Lycke M, Bergman J, Reneland A, Stålberg K, Sundfeldt K, Gyllensten U. Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment. COMMUNICATIONS MEDICINE 2022; 2:124. [PMID: 36196264 PMCID: PMC9526736 DOI: 10.1038/s43856-022-00193-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 09/23/2022] [Indexed: 11/05/2022] Open
Abstract
Background Ovarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30-50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass. Methods Protein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher's Exact tests on achieved sensitivity and specificity. Results The assay's performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive. Conclusion The robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.
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Affiliation(s)
- Stefan Enroth
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden ,grid.462826.c0000 0004 5373 8869Swedish Collegium for Advanced Study, Thunbergsvägen 2, SE-752 38 Uppsala, Sweden
| | - Emma Ivansson
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Julia Hedlund Lindberg
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
| | - Maria Lycke
- grid.8761.80000 0000 9919 9582Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-416 85 Gothenburg, Sweden
| | | | | | - Karin Stålberg
- grid.8993.b0000 0004 1936 9457Department of Women’s and Children’s Health, Uppsala University, SE-751 85 Uppsala, Sweden
| | - Karin Sundfeldt
- grid.8761.80000 0000 9919 9582Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-416 85 Gothenburg, Sweden
| | - Ulf Gyllensten
- grid.8993.b0000 0004 1936 9457Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden
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Yang S, Tang J, Rong Y, Wang M, Long J, Chen C, Wang C. Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer. Front Oncol 2022; 12:949766. [PMID: 36185223 PMCID: PMC9523238 DOI: 10.3389/fonc.2022.949766] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 08/26/2022] [Indexed: 12/24/2022] Open
Abstract
Objective This work was designed to investigate the performance of the International Ovarian Tumor Analysis (IOTA) ADNEX (Assessment of Different NEoplasias in the adneXa) model combined with human epithelial protein 4 (HE4) for early ovarian cancer (OC) detection. Methods A total of 376 women who were hospitalized and operated on in Women and Children’s Hospital of Chongqing Medical University were selected. Ultrasonographic images, cancer antigen-125 (CA 125) levels, and HE4 levels were obtained. All cases were analyzed and the histopathological diagnosis serves as the reference standard. Based on the IOTA ADNEX model post-processing software, the risk prediction value was calculated. We analyzed receiver operating characteristic curves to determine whether the IOTA ADNEX model alone or combined with HE4 provided better diagnostic accuracy. Results The area under the curve (AUC) of the ADNEX model alone or combined with HE4 in predicting benign and malignant ovarian tumors was 0.914 (95% CI, 0.881–0.941) and 0.916 (95% CI, 0.883–0.942), respectively. With the cutoff risk of 10%, the ADNEX model had a sensitivity of 0.93 (95% CI, 0.87–0.97) and a specificity of 0.73 (95% CI, 0.67–0.78), while combined with HE4, it had a sensitivity of 0.90 (95% CI, 0.84–0.95) and a specificity of 0.81 (95% CI, 0.76–0.86). The IOTA ADNEX model combined with HE4 was better at improving the accuracy of the differential diagnosis between different OCs than the IOTA ADNEX model alone. A significant difference was found in separating borderline masses from Stage II–IV OC (p = 0.0257). Conclusions A combination of the IOTA ADNEX model and HE4 can improve the specificity of diagnosis of ovarian benign and malignant tumors and increase the sensitivity and effectiveness of the differential diagnosis of Stage II–IV OC and borderline tumors.
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Affiliation(s)
- Suying Yang
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Jing Tang
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Jing Tang,
| | - Yue Rong
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Min Wang
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Jun Long
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Cheng Chen
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Cong Wang
- Department of Ultrasonography, Chongqing Health Center for Women and Children, Chongqing, China
- Department of Ultrasonography, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
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Davenport CF, Rai N, Sharma P, Deeks J, Berhane S, Mallett S, Saha P, Solanki R, Bayliss S, Snell K, Sundar S. Diagnostic Models Combining Clinical Information, Ultrasound and Biochemical Markers for Ovarian Cancer: Cochrane Systematic Review and Meta-Analysis. Cancers (Basel) 2022; 14:3621. [PMID: 35892881 PMCID: PMC9332683 DOI: 10.3390/cancers14153621] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/21/2022] [Indexed: 12/22/2022] Open
Abstract
Background: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stages. Existing systematic reviews of diagnostic models either use inappropriate meta-analytic methods or do not conduct statistical comparisons of models or stratify test performance by menopausal status. Methods: We searched CENTRAL, MEDLINE, EMBASE, CINAHL, CDSR, DARE, Health Technology Assessment Database and SCI Science Citation Index, trials registers, conference proceedings from 1991 to June 2019. Cochrane collaboration review methods included QUADAS-2 quality assessment and meta-analysis using hierarchical modelling. RMI, ROMA or ADNEX at any test positivity threshold were investigated. Histology or clinical follow-up was the reference standard. We excluded screening studies, studies restricted to pregnancy, recurrent or metastatic OC. 2 × 2 diagnostic tables were extracted separately for pre- and post-menopausal women. Results: We included 58 studies (30,121 patients, 9061 cases of ovarian cancer). Prevalence of OC ranged from 16 to 55% in studies. For premenopausal women, ROMA at a threshold of 13.1 (+/−2) and ADNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at 200 (p < 0.0001) 77.8 (72.5, 82.4), 94.9 (92.5, 96.6), and 57.1% (50.6 to 63.4) but lower specificity (p < 0.002), 92.5 (90.0, 94.4), 84.3 (81.3, 86.8), and 78.2 (75.8, 80.4). For postmenopausal women, ROMA at a threshold of 27.7 (+/−2) and AdNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at a threshold of 200 (p < 0.001) 90.4 (87.4, 92.7), 97.6 (96.2, 98.5), and 78.7 (74.3, 82.5), specificity of ROMA was comparable, whilst ADneX was lower, 85.5 (81.3, 88.9), 81.3 (76.9, 85.0) (p = 0.155), compared to RMI 55.2 (51.2, 59.1) (p < 0.001). Conclusions: In pre-menopausal women, ROMA and ADNEX offer significantly higher sensitivity but significantly decreased specificity. In post-menopausal women, ROMA demonstrates significantly higher sensitivity and comparable specificity to RMI I, ADNEX has the highest sensitivity of all models, but with significantly reduced specificity. RMI I has poor sensitivity compared to ROMA or ADNEX. Choice between ROMA and ADNEX as a replacement test will depend on cost effectiveness and resource implications.
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Affiliation(s)
- Clare F. Davenport
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; (P.S.); (J.D.); (S.B.); (S.B.)
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham B15 2TT, UK
| | - Nirmala Rai
- Southend University Hospital NHS Trust, Southend-on-Sea SS0 0RY, UK;
| | - Pawana Sharma
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; (P.S.); (J.D.); (S.B.); (S.B.)
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham B15 2TT, UK
| | - Jon Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; (P.S.); (J.D.); (S.B.); (S.B.)
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham B15 2TT, UK
| | - Sarah Berhane
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; (P.S.); (J.D.); (S.B.); (S.B.)
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham B15 2TT, UK
| | - Sue Mallett
- Centre for Medical Imaging, University College London, London NW1 2BU, UK;
| | - Pratyusha Saha
- College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK;
| | - Rita Solanki
- Nuffield Division of Clinical Laboratory Sciences, John Radcliffe Hospital, Oxford OX3 9DU, UK;
| | - Susan Bayliss
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham B15 2TT, UK; (P.S.); (J.D.); (S.B.); (S.B.)
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham B15 2TT, UK
| | - Kym Snell
- Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Keele ST5 5BG, UK;
| | - Sudha Sundar
- Pan Birmingham Gynaecological Cancer Centre, City Hospital, Birmingham B187QH, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Vincent Drive, Edgbaston, Birmingham B152TT, UK
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Davenport C, Rai N, Sharma P, Deeks JJ, Berhane S, Mallett S, Saha P, Champaneria R, Bayliss SE, Snell KI, Sundar S. Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women. Cochrane Database Syst Rev 2022; 7:CD011964. [PMID: 35879201 PMCID: PMC9314189 DOI: 10.1002/14651858.cd011964.pub2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Diagnostic delays are caused by non-specific symptoms. Existing systematic reviews have not comprehensively covered tests in current practice, not estimated accuracy separately in pre- and postmenopausal women, or used inappropriate meta-analytic methods. OBJECTIVES To establish the accuracy of combinations of menopausal status, ultrasound scan (USS) and biomarkers for the diagnosis of ovarian cancer in pre- and postmenopausal women and compare the accuracy of different test combinations. SEARCH METHODS We searched CENTRAL, MEDLINE (Ovid), Embase (Ovid), five other databases and three trial registries from 1991 to 2015 and MEDLINE (Ovid) and Embase (Ovid) form June 2015 to June 2019. We also searched conference proceedings from the European Society of Gynaecological Oncology, International Gynecologic Cancer Society, American Society of Clinical Oncology and Society of Gynecologic Oncology, ZETOC and Conference Proceedings Citation Index (Web of Knowledge). We searched reference lists of included studies and published systematic reviews. SELECTION CRITERIA We included cross-sectional diagnostic test accuracy studies evaluating single tests or comparing two or more tests, randomised trials comparing two or more tests, and studies validating multivariable models for the diagnosis of OC investigating test combinations, compared with a reference standard of histological confirmation or clinical follow-up in women with a pelvic mass (detected clinically or through USS) suspicious for OC. DATA COLLECTION AND ANALYSIS Two review authors independently extracted data and assessed quality using QUADAS-2. We used the bivariate hierarchical model to indirectly compare tests at commonly reported thresholds in pre- and postmenopausal women separately. We indirectly compared tests across all thresholds and estimated sensitivity at fixed specificities of 80% and 90% by fitting hierarchical summary receiver operating characteristic (HSROC) models in pre- and postmenopausal women separately. MAIN RESULTS We included 59 studies (32,059 women, 9545 cases of OC). Two tests evaluated the accuracy of a combination of menopausal status and USS findings (IOTA Logistic Regression Model 2 (LR2) and the Assessment of Different NEoplasias in the adneXa model (ADNEX)); one test evaluated the accuracy of a combination of menopausal status, USS findings and serum biomarker CA125 (Risk of Malignancy Index (RMI)); and one test evaluated the accuracy of a combination of menopausal status and two serum biomarkers (CA125 and HE4) (Risk of Ovarian Malignancy Algorithm (ROMA)). Most studies were at high or unclear risk of bias in participant, reference standard, and flow and timing domains. All studies were in hospital settings. Prevalence was 16% (RMI, ROMA), 22% (LR2) and 27% (ADNEX) in premenopausal women and 38% (RMI), 45% (ROMA), 52% (LR2) and 55% (ADNEX) in postmenopausal women. The prevalence of OC in the studies was considerably higher than would be expected in symptomatic women presenting in community-based settings, or in women referred from the community to hospital with a suspicion of OC. Studies were at high or unclear applicability because presenting features were not reported, or USS was performed by experienced ultrasonographers for RMI, LR2 and ADNEX. The higher sensitivity and lower specificity observed in postmenopausal compared to premenopausal women across all index tests and at all thresholds may reflect highly selected patient cohorts in the included studies. In premenopausal women, ROMA at a threshold of 13.1 (± 2), LR2 at a threshold to achieve a post-test probability of OC of 10% and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 77.4%, 95% CI 72.7% to 81.5%; LR2: 83.3%, 95% CI 74.7% to 89.5%; ADNEX: 95.5%, 95% CI 91.0% to 97.8%) compared to RMI (57.2%, 95% CI 50.3% to 63.8%). The specificity of ROMA and ADNEX were lower in premenopausal women (ROMA: 84.3%, 95% CI 81.2% to 87.0%; ADNEX: 77.8%, 95% CI 67.4% to 85.5%) compared to RMI 92.5% (95% CI 90.3% to 94.2%). The specificity of LR2 was comparable to RMI (90.4%, 95% CI 84.6% to 94.1%). In postmenopausal women, ROMA at a threshold of 27.7 (± 2), LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 90.3%, 95% CI 87.5% to 92.6%; LR2: 94.8%, 95% CI 92.3% to 96.6%; ADNEX: 97.6%, 95% CI 95.6% to 98.7%) compared to RMI (78.4%, 95% CI 74.6% to 81.7%). Specificity of ROMA at a threshold of 27.7 (± 2) (81.5, 95% CI 76.5% to 85.5%) was comparable to RMI (85.4%, 95% CI 82.0% to 88.2%), whereas for LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) specificity was lower (LR2: 60.6%, 95% CI 50.5% to 69.9%; ADNEX: 55.0%, 95% CI 42.8% to 66.6%). AUTHORS' CONCLUSIONS In specialist healthcare settings in both premenopausal and postmenopausal women, RMI has poor sensitivity. In premenopausal women, ROMA, LR2 and ADNEX offer better sensitivity (fewer missed cancers), but for ROMA and ADNEX this is off-set by a decrease in specificity and increase in false positives. In postmenopausal women, ROMA demonstrates a higher sensitivity and comparable specificity to RMI. ADNEX has the highest sensitivity in postmenopausal women, but reduced specificity. The prevalence of OC in included studies is representative of a highly selected referred population, rather than a population in whom referral is being considered. The comparative accuracy of tests observed here may not be transferable to non-specialist settings. Ultimately health systems need to balance accuracy and resource implications to identify the most suitable test.
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Affiliation(s)
- Clare Davenport
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Nirmala Rai
- School of Cancer Sciences, University of Birmingham, Birmingham, UK
| | - Pawana Sharma
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Sarah Berhane
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Sue Mallett
- UCL Centre for Medical Imaging, Division of Medicine, Faculty of Medical Sciences, University College London, London, UK
| | - Pratyusha Saha
- Medical School, University of Birmingham, Birmingham, UK
| | - Rita Champaneria
- Systematic Review Initiative, NHS Blood and Transplant, Oxford, UK
| | - Susan E Bayliss
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Kym Ie Snell
- Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Keele, UK
| | - Sudha Sundar
- School of Cancer Sciences, University of Birmingham , Birmingham, UK
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Zhou J, Cao W, Wang L, Pan Z, Fu Y. Application of artificial intelligence in the diagnosis and prognostic prediction of ovarian cancer. Comput Biol Med 2022; 146:105608. [PMID: 35584585 DOI: 10.1016/j.compbiomed.2022.105608] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/08/2022] [Accepted: 05/09/2022] [Indexed: 11/03/2022]
Abstract
In recent years, the wide application of artificial intelligence (AI) has dramatically improved the work efficiency of clinicians and reduced their workload. This review provides a glance at the latest advances in AI-assisted diagnosis and prognostic prediction of ovarian cancer (OC). We performed an advanced search in PubMed and IEEE/IET Electronic Library, and included 39 articles in this review. A comprehensive and objective criterion was built to assess the reliability and quality of all studies from four aspects: the size of datasets for model development, research design, the division of training sets and test sets, and the type of quantitative performance indicators. This review analyzed the construction of AI models, including data pre-processing methods, feature selection techniques, AI classifiers, or algorithms. Additionally, we compared the performance of these models built on different datasets, which may support researchers for further iteration and development of AI. Finally, we discussed the challenges and future directions for AI application in medicine.
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Affiliation(s)
- Jingyang Zhou
- Queen Mary School, Medical Department, Nanchang University, Nanchang, 330031, Jiangxi Province, PR China
| | - Weiwei Cao
- Queen Mary School, Medical Department, Nanchang University, Nanchang, 330031, Jiangxi Province, PR China
| | - Lan Wang
- Queen Mary School, Medical Department, Nanchang University, Nanchang, 330031, Jiangxi Province, PR China
| | - Zezheng Pan
- Faculty of Basic Medical Science, Nanchang University, Nanchang, 330006, Jiangxi Province, PR China
| | - Ying Fu
- The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, PR China.
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22
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Kumarasamy G, Kaur G. Protein biomarkers in gynecological cancers: The need for translational research towards clinical applications. CLINICA E INVESTIGACION EN GINECOLOGIA Y OBSTETRICIA 2022. [DOI: 10.1016/j.gine.2021.100735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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23
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Serum markers, morphological index, RMI, and ROMA in preoperative diagnosis of ovarian cancer. JOURNAL OF SURGERY AND MEDICINE 2022. [DOI: 10.28982/josam.960550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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24
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Gyllensten U, Hedlund-Lindberg J, Svensson J, Manninen J, Öst T, Ramsell J, Åslin M, Ivansson E, Lomnytska M, Lycke M, Axelsson T, Liljedahl U, Nordlund J, Edqvist PH, Sjöblom T, Uhlén M, Stålberg K, Sundfeldt K, Åberg M, Enroth S. Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer. Cancers (Basel) 2022; 14:cancers14071757. [PMID: 35406529 PMCID: PMC8997113 DOI: 10.3390/cancers14071757] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 03/22/2022] [Accepted: 03/25/2022] [Indexed: 12/19/2022] Open
Abstract
Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4–7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Abstract Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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Affiliation(s)
- Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
- Stellenbosch Institute for Advanced Study (STIAS), Marais Rd., Mostertsdrift, Stellenbosch 7600, South Africa
| | - Julia Hedlund-Lindberg
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
| | - Johanna Svensson
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Johanna Manninen
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Torbjörn Öst
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Jon Ramsell
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Matilda Åslin
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Emma Ivansson
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
| | - Marta Lomnytska
- Department of Women’s and Children’s Health, Uppsala University, SE-75185 Uppsala, Sweden; (M.L.); (K.S.)
| | - Maria Lycke
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-41685 Gothenburg, Sweden; (M.L.); (K.S.)
| | - Tomas Axelsson
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Ulrika Liljedahl
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Jessica Nordlund
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Per-Henrik Edqvist
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
| | - Tobias Sjöblom
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
| | - Mathias Uhlén
- Science for Life Laboratory, KTH-Royal Institute of Technology, SE-17165 Stockholm, Sweden;
| | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, SE-75185 Uppsala, Sweden; (M.L.); (K.S.)
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-41685 Gothenburg, Sweden; (M.L.); (K.S.)
| | - Mikael Åberg
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, SE-75237 Uppsala, Sweden; (J.S.); (J.M.); (T.Ö.); (J.R.); (M.Å.); (T.A.); (U.L.); (J.N.); (M.Å.)
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University, SE-75108 Uppsala, Sweden; (U.G.); (J.H.-L.); (E.I.); (P.-H.E.); (T.S.)
- Swedish Collegium for Advanced Study, Thunbergsvägen 2, SE-752 38 Uppsala, Sweden
- Correspondence: ; Tel.: +46-(0)-18-4710000
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Mikdadi D, O'Connell KA, Meacham PJ, Dugan MA, Ojiere MO, Carlson TB, Klenk JA. Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery. Cancer Biomark 2022; 33:173-184. [PMID: 35213360 DOI: 10.3233/cbm-210301] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Artificial intelligence (AI), including machine learning (ML) and deep learning, has the potential to revolutionize biomedical research. Defined as the ability to "mimic" human intelligence by machines executing trained algorithms, AI methods are deployed for biomarker discovery. OBJECTIVE We detail the advancements and challenges in the use of AI for biomarker discovery in ovarian and pancreatic cancer. We also provide an overview of associated regulatory and ethical considerations. METHODS We conducted a literature review using PubMed and Google Scholar to survey the published findings on the use of AI in ovarian cancer, pancreatic cancer, and cancer biomarkers. RESULTS Most AI models associated with ovarian and pancreatic cancer have yet to be applied in clinical settings, and imaging data in many studies are not publicly available. Low disease prevalence and asymptomatic disease limits data availability required for AI models. The FDA has yet to qualify imaging biomarkers as effective diagnostic tools for these cancers. CONCLUSIONS Challenges associated with data availability, quality, bias, as well as AI transparency and explainability, will likely persist. Explainable and trustworthy AI efforts will need to continue so that the research community can better understand and construct effective models for biomarker discovery in rare cancers.
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Affiliation(s)
- Dina Mikdadi
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
| | - Kyle A O'Connell
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA.,Department of Biology, George Washington University, Washington, DC, USA
| | - Philip J Meacham
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
| | - Madeleine A Dugan
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
| | - Michael O Ojiere
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
| | - Thaddeus B Carlson
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
| | - Juergen A Klenk
- Biomedical Data Science Lab, Deloitte Consulting LLP, Arlington, VA, USA
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Plasma circN4BP2L2 is a promising novel diagnostic biomarker for epithelial ovarian cancer. BMC Cancer 2022; 22:6. [PMID: 34980005 PMCID: PMC8721970 DOI: 10.1186/s12885-021-09073-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/17/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Circular RNAs (circRNAs) are more stable than linear RNA molecules, which makes them promising diagnostic biomarkers for diseases. By circRNA-sequencing analysis, we previously found that circN4BP2L2 was significantly decreased in epithelial ovarian cancer (EOC) tissues, and was predictive of disease progression. The aim of this study was to evaluate the diagnostic value of plasma circN4BP2L2 in EOC. METHODS Three hundred seventy-eight plasma samples were acquired prior to surgery. Samples were obtained from 126 EOC patients, 126 benign ovarian cyst patients, and 126 healthy volunteers. CircN4BP2L2 was assessed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were assessed using enzyme-linked immunosorbent assay (ELISA). EOC cells were transfected with small interference RNAs (siRNAs) and cell proliferation, migration, invasion, cell cycle and cell apoptosis were performed to assess the effect of circN4BP2L2 in EOC. Receiver operating curve (ROC), the area under the curve (AUC), sensitivity and specificity were estimated. RESULTS Plasma circN4BP2L2 was significantly downregulated in EOC patients. Decreased circN4BP2L2 was significantly associated with advanced tumor stage, worse histological grade, lymph node metastasis and distant metastasis in EOC. CircN4BP2L2 inhibited tumor cell migration and invasion in vitro. CircN4BP2L2 could significantly separate EOC from benign (AUC = 0.82, P < 0.01) or normal (AUC = 0.90, P < 0.01) cohort. Early stage EOC vs benign (AUC = 0.81, P < 0.01) or normal (AUC = 0.90, P < 0.01) cohort could also be distinguished by circN4BP2L2. In discrimination between EOC cohort and benign or normal cohort, circN4BP2L2 performed equally well in both pre- and post-menopausal women. The combination of circN4BP2L2, CA125 and HE4 showed high sensitivity and specificity in detecting EOC cases. CONCLUSIONS Plasma circN4BP2L2 is significantly downregulated in EOC and might serve as a promising novel diagnostic biomarker for EOC patients, especially in early stage EOC cases. CircN4BP2L2 might act as an adjunct to CA125 and HE4 in detecting EOC. Further large-scale studies are warranted to verify our results.
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Ashmore AA, Gnanachandran C, Luqman I, Horrocks K. One-stop clinic for patients with suspected ovarian cancer: results from a retrospective outcome study of the referral pathway. BMC Womens Health 2021; 21:429. [PMID: 34961545 PMCID: PMC8712104 DOI: 10.1186/s12905-021-01540-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 11/12/2021] [Indexed: 11/12/2022] Open
Abstract
Background Women with abdominal pain and bloating frequently have their Ca-125 levels investigated for suspected ovarian cancer and this has led to a significant increase in referrals to the ovarian cancer service. We have conducted this study to help improve the efficiency in which these patients are investigated and to improve future pathways within the referral service. Methods This was a retrospective observational outcome study. Data were collected from electronic documents of patients’ referrals, assessments, and clinical correspondences over 48 months. The study was conducted in a secondary gynaecology cancer centre with direct referrals from primary care. The pelvic mass clinic was set up to include a consultation and an ultrasound scan with support available for patients if required. All patients included were referred directly from primary care for suspected ovarian cancer with Ca-125 result over a period of 2 years. Results 286 were referred from primary care according to the NICE guidelines of ‘2-week wait for ovarian cancer’. Only 223 patients who had a Ca-125 result reported at the time of their referral were included in the analysis. Out of the 223 patients, 126 patients were discharged with or without a repeat Ca-125 after the initial assessment. 18 patients were diagnosed with cancer following the referral, but only 12 of them had a primary ovarian malignancy. The malignancy rate in women under 50 years of age was 22% (4/18) and 78% (14/18) in women aged 50 or above. Conclusion One-stop focused gynaecology ultrasound clinics where clinicians may assess patients and perform ultrasound scans for suspected cancer, may be better for managing this patient population due to improved efficiencies in waiting times, same day diagnosis and a reduction in waiting times to first appointment. Secondly, the majority of the patients with Ca-125 of more than 35 U/mL, who were referred through this pathway, did not have cancer. This review queries the future value of using Ca-125 as the basis for referrals from primary care for suspected ovarian malignancy. Further studies are required to assess whether a higher Ca-125 cut off may be used as the basis of referrals for premenopausal women.
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Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer. Cancers (Basel) 2021; 13:cancers13225713. [PMID: 34830868 PMCID: PMC8616310 DOI: 10.3390/cancers13225713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 11/05/2021] [Accepted: 11/08/2021] [Indexed: 12/05/2022] Open
Abstract
Simple Summary Ovarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this study we have, based on prior discoveries, constructed a multiplexed targeted selected-reaction-monitoring assay to detect peptides from 177 proteins in only 20 µL of plasma. The assay was evaluated in patients with a focus on early-stages and all ovarian cancer histologies in separate groups. With multivariate analysis, we found the highest predictive value in the benign vs. low-grade serous (Q2 = 0.615) and mucinous (Q2 = 0.611) early stage compared to all malignant (Q2 = 0.226) or late stage (Q2 = 0.43) ovarian cancers. The results show that each ovarian cancer histology subgroup can be identified by a unique panel of proteins. Abstract Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes.
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Diagnostic measures comparison for ovarian malignancy risk in Epithelial ovarian cancer patients: a meta-analysis. Sci Rep 2021; 11:17308. [PMID: 34453074 PMCID: PMC8397730 DOI: 10.1038/s41598-021-96552-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 08/09/2021] [Indexed: 11/30/2022] Open
Abstract
Epithelial ovarian cancer has become the most frequent cause of deaths among gynecologic malignancies. Our study elucidates the diagnostic performance of Risk of Ovarian Malignancy Algorithm (ROMA), Human epididymis secretory protein 4 (HE4) and cancer antigen (CA125). To compare the diagnostic accuracy of ROMA, HE-4 and CA125 in the early diagnosis and screening of Epithelial Ovarian Cancer. Literature search in electronic databases such as Medicine: MEDLINE (through PUBMED interface), EMBASE, Google Scholar, Science Direct and Cochrane library from January 2011 to August 2020. Studies that evaluated the diagnostic measures of ROMA, HE4 and CA125 by using Chemilumincence immunoassay or electrochemiluminescence immunoassay (CLIA or ECLIA) as index tests. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2).
We included 32 studies in our meta-analysis. We calculated AUC by SROC, pooled estimated like sensitivity, specificity, likelihood ratio, diagnostic odds ratio (DOR), Tau square, Cochran Q through random effect analysis and meta-regression. Data was retrieved from 32 studies. The number of studies included for HE4, CA125 and ROMA tests was 25, 26 and 22 respectively. The patients with EOC were taken as cases, and women with benign ovarian mass were taken as control, which was 2233/5682, 2315/5875 and 2281/5068 respectively for the markers or algorithm.
The pooled estimates of the markers or algorithm were sensitivity: ROMA (postmenopausal) (0.88, 95% CI 0.86–0.89) > ROMA (premenopausal) 0.80, 95% CI 0.78–0.83 > CA-125(0.84, 95% CI 0.82–0.85) > HE4 (0.73, 95% CI 0.71–0.75) specificity: HE4 (0.90, 95% CI 0.89–0.91) > ROMA (postmenopausal) (0.83, 95% CI 0.81–0.84) > ROMA (premenopausal) (0.80, 95% CI 0.79–0.82) > CA125 (0.73, 95%CI 0.72–0.74), Diagnostic odd’s ratio ROMA (postmenopausal) 44.04, 95% CI 31.27–62.03, ROMA (premenopausal)-18.93, 95% CI 13.04–27.48, CA-125-13.44, 95% CI 9.97–18.13, HE4-41.03, 95% CI 27.96–60.21 AUC(SE): ROMA (postmenopausal) 0.94(0.01), ROMA (premenopausal)-0.88(0.01), HE4 0.91(0.01), CA125-0.86(0.02) through bivariate random effects model considering the heterogeneity. Our study found ROMA as the best marker to differentiate EOC from benign ovarian masses with greater diagnostic accuracy as compared to HE4 and CA125 in postmenopausal women. In premenopausal women, HE4 is a promising predictor of Epithelial ovarian cancer; however, its utilisation requires further exploration.
Our study elucidates the diagnostic performance of ROMA, HE4 and CA125 in EOC. ROMA is a promising diagnostic marker of Epithelial ovarian cancers in postmenopausal women, while HE4 is the best diagnostic predictor of EOC in the premenopausal group. Our study had only EOC patients as cases and those with benign ovarian masses as controls. Further, we considered the studies estimated using the markers by the same index test: CLIA or ECLIA. The good number of studies with strict inclusion criteria reduced bias because of the pooling of studies with different analytical methods, especially for HE4. We did not consider the studies published in foreign languages. Since a few studies were available for HE4 and CA125 in the premenopausal and postmenopausal group separately, data were inadequate for sub-group analysis. Further, we did not assess these markers' diagnostic efficiency stratified by the stage and type of tumour due to insufficient studies.
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Lycke M, Ulfenborg B, Malchau Lauesgaard J, Kristjansdottir B, Sundfeldt K. Consideration should be given to smoking, endometriosis, renal function (eGFR) and age when interpreting CA125 and HE4 in ovarian tumor diagnostics. Clin Chem Lab Med 2021; 59:1954-1962. [PMID: 34388324 DOI: 10.1515/cclm-2021-0510] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 08/03/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES To evaluate the impact of different biologic, histopathologic and lifestyle factors on serum levels of human epididymis protein 4 (HE4) and Cancer antigen 125 (CA125) in the diagnostic work up of women with an ovarian cyst or pelvic tumor. METHODS The statistical evaluation was performed on a population of 445 women diagnosed with a benign ovarian disease, included in a large Swedish multicenter trial (ClinicalTrials.gov NCT03193671). Multivariable logistic regression analyses were performed to distinguish between the true negatives and false positives through adjusting for biologic, histopathologic and lifestyle factors on serum samples of CA125 and HE4 separately. The likelihood ratio test was used to determine statistical significance and Benjamini-Hochberg correction to adjust for multiple testing. RESULTS A total of 31% of the women had false positive CA125 but only 9% had false positive results of HE4. Smoking (OR 6.62 95% CI 2.93-15.12) and impaired renal function, measured by eGFR (OR 0.18 95% CI 0.08-0.39), were independently predictive of falsely elevated serum levels of HE4. Endometriosis was the only variable predictive of falsely elevated serum levels of CA125 (OR 7.96 95% CI 4.53-14.39). Age correlated with increased serum levels of HE4. CONCLUSIONS Smoking, renal failure, age and endometriosis are factors that independently should be considered when assessing serum levels of HE4 and CA125 in women with an ovarian cyst or pelvic mass to avoid false indications of malignant disease.
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Affiliation(s)
- Maria Lycke
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg and Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | | | - Jacob Malchau Lauesgaard
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg and Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Björg Kristjansdottir
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg and Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Karin Sundfeldt
- Department of Obstetrics and Gynecology, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg and Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
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Zhang C, Hu H, Wang X, Zhu Y, Jiang M. WFDC Protein: A Promising Diagnosis Biomarker of Ovarian Cancer. J Cancer 2021; 12:5404-5412. [PMID: 34405003 PMCID: PMC8364637 DOI: 10.7150/jca.57880] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 05/23/2021] [Indexed: 02/06/2023] Open
Abstract
An initial diagnosis of cancer is usually based on symptoms, abnormal physical examination and imaging tests. Ovarian cancer is difficult to be diagnosed timely due to the nonspecific symptoms, thus resulting in the high-risk mortality. Despite of the various diagnostic methods, there is still no reliable diagnostic test. Clinically, carbohydrate antigen 125(CA125) is widely recognized as a diagnosis biomarker of ovary cancer. However, CA125 is not sensitive to detect the ovary cancer at the early stage. It is essential to explore other potential biomarkers. Human epididymis protein 4 (HE4) in the whey/four-disulfide core (WFDC) proteins family shows satisfactory sensitivity in the early diagnosis of ovary cancer. In this present review, we summarized the important effects of WFDC family proteins on the proliferation, apoptosis and migration of ovary cancer and intended to provide more evidence to explore the possibility of WFDC protein as a diagnosis biomarker.
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Affiliation(s)
- Chen Zhang
- State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Haoyue Hu
- Lung Cancer Center, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Xiaoyan Wang
- State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Yajuan Zhu
- State Key Laboratory of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Ming Jiang
- West China Hospital, Sichuan University, Chengdu, People's Republic of China
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Timmerman D, Planchamp F, Bourne T, Landolfo C, du Bois A, Chiva L, Cibula D, Concin N, Fischerova D, Froyman W, Gallardo G, Lemley B, Loft A, Mereu L, Morice P, Querleu D, Testa AC, Vergote I, Vandecaveye V, Scambia G, Fotopoulou C. ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumors. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2021; 58:148-168. [PMID: 33794043 DOI: 10.1002/uog.23635] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumors, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.
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Affiliation(s)
- D Timmerman
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Department of Obstetrics and Gynecology, University Hospitals Leuven, Leuven, Belgium
| | - F Planchamp
- Clinical Research Unit, Institut Bergonie, Bordeaux, France
| | - T Bourne
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Department of Obstetrics and Gynecology, University Hospitals Leuven, Leuven, Belgium
- Department of Metabolism, Digestion and Reproduction, Queen Charlotte's & Chelsea Hospital, Imperial College, London, UK
| | - C Landolfo
- Department of Woman, Child and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - A du Bois
- Department of Gynaecology and Gynaecological Oncology, Evangelische Kliniken Essen-Mitte, Essen, Germany
| | - L Chiva
- Department of Gynaecology and Obstetrics, University Clinic of Navarra, Madrid, Spain
| | - D Cibula
- Department of Obstetrics and Gynaecology, First Faculty of Medicine, Charles University, General University Hospital in Prague, Prague, Czech Republic
| | - N Concin
- Department of Gynaecology and Gynaecological Oncology, Evangelische Kliniken Essen-Mitte, Essen, Germany
- Department of Obstetrics and Gynecology, Medical University of Innsbruck, Innsbruck, Austria
| | - D Fischerova
- Department of Obstetrics and Gynaecology, First Faculty of Medicine, Charles University, General University Hospital in Prague, Prague, Czech Republic
| | - W Froyman
- Department of Obstetrics and Gynecology, University Hospitals KU Leuven, Leuven, Belgium
| | - G Gallardo
- Department of Radiology, University Clinic of Navarra, Madrid, Spain
| | - B Lemley
- Patient Representative, President of Kraefti Underlivet (KIU), Denmark
- Chair Clinical Trial Project of the European Network of Gynaecological Cancer Advocacy Groups, ENGAGe
| | - A Loft
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - L Mereu
- Department of Gynecology and Obstetrics, Gynecologic Oncology Unit, Santa Chiara Hospital, Trento, Italy
| | - P Morice
- Department of Gynaecological Surgery, Institut Gustave Roussy, Villejuif, France
| | - D Querleu
- Division of Gynecologic Oncology, Fondazione Policlinico Universitario A Gemelli IRCCS, Rome, Italy
- Department of Obstetrics and Gynecologic Oncology, University Hospital, Strasbourg, France
| | - A C Testa
- Department of Woman, Child and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Institute of Obstetrics and Gynecology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - I Vergote
- Department of Obstetrics and Gynaecology and Gynaecologic Oncology, University Hospital Leuven, Leuven Cancer Institute, Leuven, Belgium
| | - V Vandecaveye
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
- Division of Translational MRI, Department of Imaging & Pathology KU Leuven, Leuven, Belgium
| | - G Scambia
- Department of Woman, Child and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Institute of Obstetrics and Gynecology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - C Fotopoulou
- Department of Gynecologic Oncology, Hammersmith Hospital, Imperial College, London, UK
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Timmerman D, Planchamp F, Bourne T, Landolfo C, du Bois A, Chiva L, Cibula D, Concin N, Fischerova D, Froyman W, Gallardo Madueño G, Lemley B, Loft A, Mereu L, Morice P, Querleu D, Testa AC, Vergote I, Vandecaveye V, Scambia G, Fotopoulou C. ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors. Int J Gynecol Cancer 2021; 31:961-982. [PMID: 34112736 PMCID: PMC8273689 DOI: 10.1136/ijgc-2021-002565] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/08/2021] [Indexed: 02/06/2023] Open
Abstract
The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.
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Affiliation(s)
- Dirk Timmerman
- Gynecology and Obstetrics, University Hospitals KU Leuven, Leuven, Belgium .,Development and Regeneration, KU Leuven, Leuven, Belgium
| | | | - Tom Bourne
- Gynecology and Obstetrics, University Hospitals KU Leuven, Leuven, Belgium.,Development and Regeneration, KU Leuven, Leuven, Belgium.,Metabolism Digestion and Reproduction, Queen Charlotte's & Chelsea Hospital, Imperial College, London, UK
| | - Chiara Landolfo
- Woman, Child and Public Health, Fondazione Policlinico Universitario A Gemelli IRCCS, Rome, Italy
| | - Andreas du Bois
- Gynaecology and Gynaecological Oncology, Evangelische Kliniken Essen-Mitte, Essen, Germany
| | - Luis Chiva
- Gynaecology and Obstetrics, University Clinic of Navarra, Madrid, Spain
| | - David Cibula
- Obstetrics and Gynaecology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Nicole Concin
- Gynaecology and Gynaecological Oncology, Evangelische Kliniken Essen-Mitte, Essen, Germany.,Obstetrics and Gynecology, Medical University of Innsbruck, Innsbruck, Austria
| | - Daniela Fischerova
- Obstetrics and Gynaecology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Wouter Froyman
- Gynecology and Obstetrics, University Hospitals KU Leuven, Leuven, Belgium
| | | | - Birthe Lemley
- European Network of Gynaecological Cancers Advocacy Groups (ENGAGe) Executive Group, Prague, Czech Republic.,KIU - Patient Organisation for Women with Gynaecological Cancer, Copenhagen, Denmark
| | - Annika Loft
- Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Liliana Mereu
- Gynecology and Obstetrics, Gynecologic Oncology Unit, Santa Chiara Hospital, Trento, Italy
| | - Philippe Morice
- Gynaecological Surgery, Institut Gustave Roussy, Villejuif, France
| | - Denis Querleu
- Gynecologic Oncology, Fondazione Policlinico Universitario A Gemelli IRCCS, Rome, Italy.,Obstetrics and Gynecologic Oncology, University Hospital, Strasbourg, France
| | - Antonia Carla Testa
- Woman, Child and Public Health, Fondazione Policlinico Universitario A Gemelli IRCCS, Rome, Italy.,Obstetrics and Gynecology, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Ignace Vergote
- Obstetrics and Gynaecology and Gynaecologic Oncology, University Hospital Leuven, Leuven Cancer Institute, Leuven, Belgium
| | - Vincent Vandecaveye
- Radiology, University Hospitals Leuven, Leuven, Belgium.,Division of Translational MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Giovanni Scambia
- Woman, Child and Public Health, Fondazione Policlinico Universitario A Gemelli IRCCS, Rome, Italy.,Obstetrics and Gynecology, Università Cattolica del Sacro Cuore, Rome, Italy
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Timmerman D, Planchamp F, Bourne T, Landolfo C, du Bois A, Chiva L, Cibula D, Concin N, Fischerova D, Froyman W, Gallardo G, Lemley B, Loft A, Mereu L, Morice P, Querleu D, Testa C, Vergote I, Vandecaveye V, Scambia G, Fotopoulou C. ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumours. Facts Views Vis Obgyn 2021; 13:107-130. [PMID: 34107646 PMCID: PMC8291986 DOI: 10.52054/fvvo.13.2.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumours, including imaging techniques, biomarkers and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumours and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumours and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.
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Review of biomarker systems as an alternative for early diagnosis of ovarian carcinoma. Clin Transl Oncol 2021; 23:1967-1978. [PMID: 33840014 DOI: 10.1007/s12094-021-02604-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 03/19/2021] [Indexed: 10/21/2022]
Abstract
Early diagnosis of ovarian carcinoma is bound to boost the long-term endurance rate of the patients. Most ovarian tumors happen post menopause when the ovaries have no vital operation and therefore irregular ovarian role causes no signs. According to Muinao T. et al. (Heliyon. 5(12):e02826, 2019), if we consider the frequency of ovarian carcinoma to be moderate, a screening technique must accomplish a base specificity of 99.6% and sensitivity of over 75%. The classification and approval of early diagnostic biomarkers explicit to ovarian carcinoma are essentially required. Prevailing methods for early diagnosis of ovarian carcinoma incorporate TVS, biological marker examination, or a blend of the two or other. In recent years, it has been revealed that a combination of at least two biomarkers has beaten single biomarkers in measures for early diagnosis of the illness. In the present document, we survey the ongoing exploration of innovative characteristic methodologies and possible panels of carcinoma biological markers for the early diagnosis of ovarian carcinoma and discuss biomarkers as the plausible apparatus for model improvement and other progressed approaches as an effective alternative to the prevailing methods for early diagnosis of this dreadful disease to evade bogus analysis and inordinate expense.
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Gkrozou F, Pappa C, Tsonis O, Dimitriou E, Paschopoulos M. Relaxin as a potential diagnostic biomarker for ovarian cancer- A prospective study. Eur J Obstet Gynecol Reprod Biol 2021; 260:99-104. [PMID: 33752121 DOI: 10.1016/j.ejogrb.2021.03.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/25/2021] [Accepted: 03/06/2021] [Indexed: 11/18/2022]
Abstract
Ovarian cancer is a leading cause of female mortality worldwide. Although novel approaches on this disease have been developed, overall survival rates remain moderate due to the lack of scientific evidence promoting screening at early stages of the disease. A number of biomarkers have been suggested as predictive for this type of cancer. The role of relaxin in endometrial cancer is well documented but the scientific evidence is lacking with regards to ovarian cancer. We studied patients with ovarian cancer, benign ovarian cyst and healthy patients too. The levels of relaxin have been found to be an adequate diagnostic biomarker for ovarian cancer. We also presented the different range of Ca125, HE4 and ROMA in these three groups. Randomised control trials need to be conducted though, in order to elucidate the true role of relaxin in these cases.
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Affiliation(s)
- F Gkrozou
- Department of Obstetrics and Gynaecology, University Hospitals of Birmingham, UK.
| | - C Pappa
- Department of Obstetrics and Gynaecology, General Hospital "Hatzikosta", Ioannina, Greece
| | - O Tsonis
- Department of Obstetrics and Gynaecology, University Hospital of Ioannina, Greece
| | - E Dimitriou
- Department of Mathematics, University of Ioannina, Greece
| | - M Paschopoulos
- Department of Obstetrics and Gynaecology, University Hospital of Ioannina, Greece
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Solanki V, Singh P, Sharma C, Ghuman N, Sureka B, Shekhar S, Gothwal M, Yadav G. Predicting Malignancy in Adnexal Masses by the International Ovarian Tumor Analysis-Simple Rules. J Midlife Health 2020; 11:217-223. [PMID: 33767562 PMCID: PMC7978049 DOI: 10.4103/jmh.jmh_103_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 12/03/2020] [Accepted: 12/15/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Accurate prediction of adnexal tumors preoperatively is critical for optimal management of ovarian cancers. The International Ovarian Tumor Analysis Algorithms (IOTA) is a newer tool to characterize adnexal masses as benign or malignant. OBJECTIVE This study is aimed to predict malignancy in adnexal masses and differentiates benign from malignant, applying the sonography features of simple rules given by IOTA. METHODOLOGY A prospective study was carried out at AIIMS Jodhpur for 1½ years. Women presenting with adnexal masses planned for surgery were recruited. Ultrasonography-transabdominal combined with transvaginal was done, and pelvic masses were characterized using IOTA simple rules. Patients underwent their planned surgery. Histopathology is considered the gold standard and was compared with the IOTA simple rules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS One hundred and seventy-four women were included in the study, of which the majority (82.75%) were benign, the rest being frankly malignant or borderline cancer. The sensitivity of IOTA is 96.6%, specificity of 92.3%, PPV of 72.5%, NPV of 99.2%, where indeterminate cases were considered malignant. CONCLUSION IOTA simple rule is an effective tool for identifying malignant adnexal masses. It also suggests that IOTA-simple rules can be used as a diagnostic criterion for differentiating adnexal masses into benign and malignant on an out-patient department basis.
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Affiliation(s)
- Vrushti Solanki
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Pratibha Singh
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Charu Sharma
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Navdeep Ghuman
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Binit Sureka
- Department of Radiodiagnosis, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Shashank Shekhar
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Meenakshi Gothwal
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Garima Yadav
- Department of Obstetrics and Gynecology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
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Ekanayake CD, Munasinghe N, Kumarasinghe I, Rasnayake S. Elevated CA 125 level in a mucinous cystadenoma and a teratoma: a case report. J Med Case Rep 2020; 14:141. [PMID: 32878645 PMCID: PMC7469355 DOI: 10.1186/s13256-020-02458-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 07/23/2020] [Indexed: 11/10/2022] Open
Abstract
Background The presence of a suspicious ovarian cyst with elevated cancer antigen 125 level in a woman of reproductive age poses a serious therapeutic dilemma. Mature cystic teratomas and mucinous cystadenomas may also cause an increase in cancer antigen 125. Case presentation A 43-year-old Sinhalese woman with a history of anovulatory subfertility for 5 years presented with heavy menstrual bleeding and secondary dysmenorrhea of 6 months’ duration. Imaging (pelvic ultrasound and computed tomography of the abdomen and pelvis) revealed a hemorrhagic cyst (6 × 4 cm) on the right side and a multilocular cyst with solid areas (10 × 7 cm) on the left side. Her cancer antigen 125 level was 2715 U/ml. Following a multidisciplinary team meeting, a fertility-sparing staging laparotomy was performed, which included right cystectomy, left oophorectomy, infracolic omentectomy, and peritoneal washings. Histology revealed a mucinous cystadenoma of the right ovary and a mature cystic teratoma on the left ovary. No malignant cells were observed in peritoneal washings. The patient’s cancer antigen 125 level dropped to 74.8 U/ml 1 month after surgery. Conclusion Rarely, teratomas and mucinous cystadenomas may also give rise to an extremely high cancer antigen 125 level. The risk of malignancy index and risk of malignancy algorithm may both be misleading in these instances. Therefore, multidisciplinary input, fertility-sparing surgery, and follow-up are paramount to achieve optimal treatment and patient satisfaction.
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Affiliation(s)
- Chanil Deshan Ekanayake
- Department of Clinical Sciences, Faculty of Medicine, General Sir John Kotelawala Defence University, Ratmalana, Sri Lanka.
| | - Nayoman Munasinghe
- Department of Clinical Sciences, Faculty of Medicine, General Sir John Kotelawala Defence University, Ratmalana, Sri Lanka
| | - Iranthi Kumarasinghe
- Department of Paraclinical Sciences, Faculty of Medicine, General Sir John Kotelawala Defence University, Ratmalana, Sri Lanka
| | - Sachini Rasnayake
- Department of Clinical Sciences, Faculty of Medicine, General Sir John Kotelawala Defence University, Ratmalana, Sri Lanka
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Gyllensten U, Bosdotter Enroth S, Stålberg K, Sundfeldt K, Enroth S. Preoperative Fasting and General Anaesthesia Alter the Plasma Proteome. Cancers (Basel) 2020; 12:cancers12092439. [PMID: 32867270 PMCID: PMC7564209 DOI: 10.3390/cancers12092439] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 08/22/2020] [Accepted: 08/26/2020] [Indexed: 01/15/2023] Open
Abstract
Background: Blood plasma collected at time of surgery is an excellent source of patient material for investigations into disease aetiology and for the discovery of novel biomarkers. Previous studies on limited sets of proteins and patients have indicated that pre-operative fasting and anaesthesia can affect protein levels, but this has not been investigated on a larger scale. These effects could produce erroneous results in case-control studies if samples are not carefully matched. Methods: The proximity extension assay (PEA) was used to characterize 983 unique proteins in a total of 327 patients diagnosed with ovarian cancer and 50 age-matched healthy women. The samples were collected either at time of initial diagnosis or before surgery under general anaesthesia. Results: 421 of the investigated proteins (42.8%) showed statistically significant differences in plasma abundance levels comparing samples collected at time of diagnosis or just before surgery under anaesthesia. Conclusions: The abundance levels of the plasma proteome in samples collected before incision, i.e., after short-time fasting and under general anaesthesia differs greatly from levels in samples from awake patients. This emphasizes the need for careful matching of the pre-analytical conditions of samples collected from controls to cases at time of surgery in the discovery as well as clinical use of protein biomarkers.
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Affiliation(s)
- Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
| | | | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, SE-751 85 Uppsala, Sweden;
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-416 85 Gothenburg, Sweden;
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
- Correspondence: ; Tel.: +46-18-4714913
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Bao M, Zhang L, Hu Y. Novel gene signatures for prognosis prediction in ovarian cancer. J Cell Mol Med 2020; 24:9972-9984. [PMID: 32666642 PMCID: PMC7520318 DOI: 10.1111/jcmm.15601] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 06/01/2020] [Accepted: 06/07/2020] [Indexed: 12/24/2022] Open
Abstract
Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi‐gene signature based on the LASSO Cox regression model in the TCGA database and time‐dependent ROC curves showed good predictive accuracy for 1‐, 3‐ and 5‐year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi‐gene signature stratified patients into high‐risk and low‐risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi‐gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug‐gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.
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Affiliation(s)
- Mingyang Bao
- State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China
| | - Lihua Zhang
- Department of Gynecology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Yueqing Hu
- State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.,Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China
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Kim SI, Kang N, Leem S, Yang J, Jo H, Lee M, Kim HS, Dhanasekaran DN, Kim YK, Park T, Song YS. Metagenomic Analysis of Serum Microbe-Derived Extracellular Vesicles and Diagnostic Models to Differentiate Ovarian Cancer and Benign Ovarian Tumor. Cancers (Basel) 2020; 12:cancers12051309. [PMID: 32455705 PMCID: PMC7281409 DOI: 10.3390/cancers12051309] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 05/15/2020] [Accepted: 05/19/2020] [Indexed: 12/22/2022] Open
Abstract
We aimed to develop a diagnostic model identifying ovarian cancer (OC) from benign ovarian tumors using metagenomic data from serum microbe-derived extracellular vesicles (EVs). We obtained serum samples from 166 patients with pathologically confirmed OC and 76 patients with benign ovarian tumors. For model construction and validation, samples were randomly divided into training and test sets in the ratio 2:1. Isolation of microbial EVs from serum samples of the patients and 16S rDNA amplicon sequencing were carried out. Metagenomic and clinicopathologic data-based OC diagnostic models were constructed in the training set and then validated in the test set. There were significant differences in the metagenomic profiles between the OC and benign ovarian tumor groups; specifically, genus Acinetobacter was significantly more abundant in the OC group. More importantly, Acinetobacter was the only common genus identified by seven different statistical analysis methods. Among the various metagenomic and clinicopathologic data-based OC diagnostic models, the model consisting of age, serum CA-125 levels, and relative abundance of Acinetobacter showed the best diagnostic performance with the area under the receiver operating characteristic curve of 0.898 and 0.846 in the training and test sets, respectively. Thus, our findings establish a metagenomic analysis of serum microbe-derived EVs as a potential tool for the diagnosis of OC.
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Affiliation(s)
- Se Ik Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, Korea; (S.I.K.); (M.L.); (H.S.K.)
| | - Nayeon Kang
- Department of Statistics, Seoul National University, Seoul 08826, Korea;
| | - Sangseob Leem
- Department of Core Technology, R&D Center, LG Household & Healthcare, Seoul 07795, Korea;
| | - Jinho Yang
- MD Healthcare Inc., Seoul 03923, Korea; (J.Y.); (Y.-K.K.)
| | - HyunA Jo
- Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea;
| | - Maria Lee
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, Korea; (S.I.K.); (M.L.); (H.S.K.)
| | - Hee Seung Kim
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, Korea; (S.I.K.); (M.L.); (H.S.K.)
| | - Danny N. Dhanasekaran
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA;
| | - Yoon-Keun Kim
- MD Healthcare Inc., Seoul 03923, Korea; (J.Y.); (Y.-K.K.)
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul 08826, Korea;
- Correspondence: (T.P.); (Y.S.S.); Tel.: +82-2-880-8924 (T.P.); +82-2-2072-2822 (Y.S.S.)
| | - Yong Sang Song
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul 03080, Korea; (S.I.K.); (M.L.); (H.S.K.)
- Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea;
- Correspondence: (T.P.); (Y.S.S.); Tel.: +82-2-880-8924 (T.P.); +82-2-2072-2822 (Y.S.S.)
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Feng LY, Liao SB, Li L. Preoperative serum levels of HE4 and CA125 predict primary optimal cytoreduction in advanced epithelial ovarian cancer: a preliminary model study. J Ovarian Res 2020; 13:17. [PMID: 32050995 PMCID: PMC7014747 DOI: 10.1186/s13048-020-0614-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 01/22/2020] [Indexed: 12/18/2022] Open
Abstract
Objective The aim of this study is to establish a noninvasive preoperative model for predicting primary optimal cytoreduction in advanced epithelial ovarian cancer by HE4 and CA125 combined with clinicopathological parameters. Methods Clinical data including preoperative serum HE4 and CA125 level of 83 patients with advanced epithelial ovarian cancer were collected. The sensitivity, specificity, positive predictive value, negative predictive value and overall accuracy of each clinical parameter were calculated. The Predictive Index score model and the logistic model were constructed to predict the primary optimal cytoreduction. Results Optimal surgical cytoreduction was achieved in 62.65% (52/83) patients. Cutoff values of preoperative serum HE4 and CA125 were 777.10 pmol/L and 313.60 U/ml. (1) Patients with PIV ≥ 6 may not be able to achieve optimal surgical cytoreduction. The diagnostic accuracy, NPV, PPV and specificity for diagnosing suboptimal cytoreduction were 71, 100, 68, and 100%, respectively. (2) The logistic model was: logit p = 0.12 age − 2.38 preoperative serum CA125 level − 1.86 preoperative serum HE4 level-2.74 histological type-3.37. AUC of the logistic model in the validation group was 0.71(95%CI 0.54–0.88, P = 0.025). Sensitivity and specificity were 1.00 and 0.44, respectively. Conclusion Age, preoperative serum CA125 level and preoperative serum HE4 level are important non-invasive predictors of primary optimal surgical cytoreduction in advanced epithelial ovarian cancer. Our PIV and logistic model can be used for assessment before expensive and complex predictive methods including laparoscopy and diagnostic imaging. Further future clinical validation is needed.
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Affiliation(s)
- Li-Yuan Feng
- Department of Gynecologic oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning, Guangxi, 530021, People's Republic of China
| | - Sheng-Bin Liao
- Department of Gynecologic oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning, Guangxi, 530021, People's Republic of China
| | - Li Li
- Department of Gynecologic oncology, Guangxi Medical University Cancer Hospital, 71 Hedi Road, Nanning, Guangxi, 530021, People's Republic of China.
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Evaluation of adnexal tumours in the International Ovarian Tumor Analysis system in reference to histopathological results. MENOPAUSE REVIEW 2020; 18:141-145. [PMID: 31975980 PMCID: PMC6970421 DOI: 10.5114/pm.2019.90812] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 11/07/2019] [Indexed: 11/21/2022]
Abstract
Aim of the study To retrospectively evaluate how the International Ovarian Tumor Analysis (IOTA) simple rules used in ultrasound examinations estimate the probability of malignant and benign tumour occurrence in the studied population. Material and methods The study was performed on a group of 425 patients with ovarian tumours operated in the Clinic of Surgical and Oncological Gynecology at the Medical University of Lodz in the years 2014-2015. Adnexal tumours were rated according to IOTA simple rules, classifying them as probably malignant, probably benign, or unclassified. The results of the study were compared with final histopathological results. The statistical analysis was performed using STATISTICA 13 PL with Medical Pack. Results We analysed data on n = 43 (11%) patients with malignant, n = 346 (86%) patients with benign, and n = 12 (3%) patients with borderline tumours, respectively. Malignant tumour patients were significantly older (mean age 61.0 ±11.6 vs. 43.6 ±16.2 years, p< 0.001), had higher BMI (mean 27.3 ±7.0 vs. 25.2 ±5.2, p< 0.05), more pregnancies (median 2 vs. 1, p = 0.001), and higher cancer antigen 125 (CA 125) concentrations (median 251.5 vs. 18.5, p< 0.001) than patients with a benign tumour. Also, they more often suffered from diabetes mellitus (19% vs. 8%, p = 0.02) and arterial hypertension (60% vs. 42%, p< 0.01) than benign tumour patients. Conclusions In our study, IOTA performance in predicting or ruling out a malignant tumour was highly satisfactory and similar to that of CA 125. Both the methods may be complementary and used to assess the risk of malignant vs. benign ovarian neoplasm, although the context of other clinical variables may also be important.
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Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers. J Clin Med 2020; 9:jcm9020299. [PMID: 31973047 PMCID: PMC7073859 DOI: 10.3390/jcm9020299] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 01/10/2020] [Accepted: 01/18/2020] [Indexed: 12/26/2022] Open
Abstract
Ovarian cancer is the most lethal gynecologic cancer. Pre-diagnostic testing lacks sensitivity and specificity, and surgery is often the only way to secure the diagnosis. Exploring new biomarkers is of great importance, but the rationale of combining validated well-established biomarkers and algorithms could be a more effective way forward. We hypothesized that we can improve differential diagnostics and reduce false positives by combining (a) risk of malignancy index (RMI) with serum HE4, (b) risk of ovarian malignancy algorithm (ROMA) with a transvaginal ultrasound score or (c) adding HE4 to CA125 in a simple algorithm. With logistic regression modeling, new algorithms were explored and validated using leave-one-out cross validation. The analyses were performed in an existing cohort prospectively collected prior to surgery, 2013-2016. A total of 445 benign tumors and 135 ovarian cancers were included. All presented models improved specificity at cut-off compared to the original algorithm, and goodness of fit was significant (p < 0.001). Our findings confirm that HE4 is a marker that improves specificity without hampering sensitivity or diagnostic accuracy in adnexal tumors. We provide in this study "easy-to-use" algorithms that could aid in the triage of women to the most appropriate level of care when presenting with an unknown ovarian cyst or suspicious ovarian cancer.
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El Bairi K, Afqir S, Amrani M. Is HE4 Superior over CA-125 in the Follow-up of Patients with Epithelial Ovarian Cancer? Curr Drug Targets 2020; 21:1026-1033. [PMID: 32334501 DOI: 10.2174/1389450121666200425211732] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 03/19/2020] [Accepted: 03/30/2020] [Indexed: 02/08/2023]
Abstract
Notwithstanding important advances in the treatment of epithelial ovarian cancer (EOC), this disease is still a leading cause of global high mortality from gynecological malignancies. Recurrence in EOC is inevitable and it is responsible for poor survival rates. There is a critical need for novel effective biomarkers with improved accuracy compared to the standard carbohydrate antigen-125 (CA-125) for follow-up. The human epididymis protein 4 (HE4) is used for early detection of EOC (ROMA algorithm) as well as for predicting optimal cytoreduction after neoadjuvant chemotherapy and survival outcomes. Notably, the emerging HE4 is a promising prognostic biomarker that has displayed better accuracy in various recent studies for detecting recurrent disease. In this mini-review, we discussed the potential of HE4 as an accurate predictor of EOC recurrence.
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Affiliation(s)
- Khalid El Bairi
- Faculty of Medicine and Pharmacy, Mohamed Ist University, Oujda, Morocco
| | - Said Afqir
- Faculty of Medicine and Pharmacy, Mohamed Ist University, Oujda, Morocco
| | - Mariam Amrani
- Faculty of Medicine and Pharmacy, Mohamed V University, Rabat, Morocco
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Muinao T, Deka Boruah HP, Pal M. Multi-biomarker panel signature as the key to diagnosis of ovarian cancer. Heliyon 2019; 5:e02826. [PMID: 31867451 PMCID: PMC6906658 DOI: 10.1016/j.heliyon.2019.e02826] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 09/03/2019] [Accepted: 11/07/2019] [Indexed: 12/26/2022] Open
Abstract
Early detection of ovarian cancer has been a challenge to manage the high mortality rate caused by this deadly disease. The trends in mortality have been reduced by the scientific contributions from the corners across the globe, however accounting for the fifth leading cause of gynecological mortality. The complexities in the clinical presentation, origin of tumor, and gene expression profiles had added to much difficulty in understanding and diagnosis of the disease. Stage 1 diagnosis of ovarian cancer improves the 5-year survival rate to around 92%. Cancer antigen-125 (CA-125) is the gold standard tumor marker found at abnormally high levels in the blood of many women in ovarian cancer. However, many non-cancerous conditions exhibit high levels of CA-125 and several women have normal CA-125 level in the early stage of ovarian cancer, suggesting CA-125 biomarker is not specific enough for the screening of early stage ovarian cancer. In addition, several other biomarkers, including HE4 have been added in the diagnostic field for higher sensitivity and specificity in the diagnosis and progression of ovarian cancer. HE4 is a prospective single serum biomarker which has been approved by the FDA to monitor the disease progression in epithelial ovarian cancer. However, owing to low sensitivity and specificity, combination of a panel of biomarkers has been proposed in the diagnosis of the disease. Based on extensive biomarkers research findings, here we discuss current trends in diagnostic approaches and updated potential several panels of cancer biomarkers for early detection of ovarian cancer. It has been recently reported that CA125 in combinations with two or more biomarkers have outperformed single biomarker assays for early detection of the disease. Moreover, CA-125 with CA 19–9, EGFR, G-CSF, Eotaxin, IL-2R, cVCAM, MIF improved the sensitivity with 98.2 % and specificity of 98.7% in early stage detection of ovarian cancer. Overall, this review demonstrates a panel of biomarkers signature as the potential tool for prototype development in future and other advanced approaches for early diagnosis of ovarian cancer to avoid false-diagnosis and excessive cost.
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Affiliation(s)
- Thingreila Muinao
- Biotechnology Group, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India.,Academy of Scientific and Innovative Research, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India
| | - Hari Prasanna Deka Boruah
- Biotechnology Group, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India.,Academy of Scientific and Innovative Research, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India
| | - Mintu Pal
- Biotechnology Group, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India.,Academy of Scientific and Innovative Research, CSIR-North East Institute of Science and Technology, Jorhat, Assam, 785006, India
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CPH-I and HE4 Are More Favorable Than CA125 in Differentiating Borderline Ovarian Tumors from Epithelial Ovarian Cancer at Early Stages. DISEASE MARKERS 2019; 2019:6241743. [PMID: 31737130 PMCID: PMC6815620 DOI: 10.1155/2019/6241743] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 09/05/2019] [Indexed: 11/27/2022]
Abstract
Aim To evaluate the diagnosis value of serum human epididymis protein 4 (HE4), cancer antigen 125 (CA125), the Risk of Ovarian Malignancy Algorithm (ROMA), and Copenhagen Index (CPH-I) at early stages for differentiating borderline ovarian tumors from epithelial ovarian cancer. Methods We recruited 144 borderline ovarian tumors in FIGO stages I and II (BOT I+II), 108 epithelial ovarian cancers in FIGO stages I and II (EOC I+II), and 238 benign ovarian tumor patients with surgical treatment in the retrospective study. The concentration of HE4 and CA125 and the values of CPH-I and ROMA were assessed separately. Results The HE4 level and ROMA and CPH-I values of EOC I+II were all higher than that of BOT I+II and benign groups whether in all, pre-, or postmenopausal groups (P < 0.01). When distinguishing BOT I+II from EOC I+II, the AUC-ROC of CPH-I and HE4 were bigger than CA125 (P < 0.001), while the CPH-I has the highest sensitivities in all and postmenopausal groups (78.7%, 85.1%), and HE4 has the highest specificity and PPV (90.91%, 88.64%) in postmenopausal groups. Under pathological stratification, HE4, ROMA, and CPH-I of the serous EOC I+II were higher than that of BOT I+II (P < 0.001) and the AUC of the three indices were significantly bigger than CA125 (P < 0.001). However, the concentration of HE4 and CA125 and the values of CPH-I and ROMA have no significant difference between the two endometrioid subgroups. The index with the highest sensitivity and NPV among the four indices of different pathological subtype groups was CPH-I, and the index with the highest specificities and PPV was HE4. Conclusion CPH-I was more valuable than CA125 for differentiating BOT I+II from EOC I+II regardless of menopausal status, while HE4 might be better than CA125 for postmenopausal subgroups. HE4 and CPH-I were more favorable than CA125 for differentiating BOT I+II from EOC I+II in the case of unknown pathology or in serous type.
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Singh A, Gupta S, Sachan M. Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives. Front Cell Dev Biol 2019; 7:182. [PMID: 31608277 PMCID: PMC6761254 DOI: 10.3389/fcell.2019.00182] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 08/19/2019] [Indexed: 12/15/2022] Open
Abstract
Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.
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Affiliation(s)
- Alka Singh
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, India
| | - Sameer Gupta
- Department of Surgical Oncology, King George Medical University, Lucknow, India
| | - Manisha Sachan
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, India
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49
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Wang Y, Wang Z, Ding Y, Sun F, Ding X. The Application Value of Serum HE4 in the Diagnosis of Lung Cancer. Asian Pac J Cancer Prev 2019; 20:2405-2407. [PMID: 31450913 PMCID: PMC6852827 DOI: 10.31557/apjcp.2019.20.8.2405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Indexed: 11/25/2022] Open
Abstract
Background: To investigate the clinical value of HE4 detection in the diagnosis of lung cancer and the clinical significance of combined detection with CEA, NSE and CYFRA21-1. Methods: 90 cases of lung cancer, 30 cases of pulmonary tuberculosis, 30 cases of pneumonia and 30 cases of health physical examination were selected. The levels of serum HE4, CYFRA21-1, CEA and NSE were detected by electrochemiluminescence method. Statistical analysis was performed to observe the sensitivity and specificity. Results: The levels of serum HE4, CEA, NSE and CYFRA21-1 in lung cancer group were significantly higher than those in tuberculosis group and health physical examination group. There was no significant difference in the levels of HE4, CEA and NSE between the lung cancer group and the pneumonia group, the difference of CYFRA21-1 level was statistically significant (p<0.05).With health physical examination group as normal controls, the sensitivity and specificity of combined detection of HE4, CEA, NSE and CYFRA21-1 in the diagnosis of lung cancer were 82.2% and 90.0%,and the area under the curve (AUC) was 0.907, followed by HE4 (0.867), CYFRA21-1 (0.787), CEA (0.752) and NSE (0.747). Conclusion: HE4 can be used as a serological marker for the diagnosis of lung cancer. The combined detection of HE4, CEA, NSE and CYFRA21-1 can improve the diagnosis of lung cancer. Serum HE4 levels are highly specific in distinguishing between lung cancer patients and normal population, and are equivalent to CYFRA21-1; but they are less specific than CYFRA21-1 in distinguishing lung cancer patients from pneumonia patients.
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Affiliation(s)
- Yuhui Wang
- Weifang City People's Hospital, Weifang, China.
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A biosensor for determination of the circulating biomarker CA125/MUC16 by Surface Plasmon Resonance Imaging. Talanta 2019; 206:120187. [PMID: 31514860 DOI: 10.1016/j.talanta.2019.120187] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 07/23/2019] [Accepted: 07/28/2019] [Indexed: 12/17/2022]
Abstract
CA125/MUC16 is an ovarian tumor cell marker widely used as a biomarker in epithelial ovarian carcinoma. CA125/MUC16 is also used for evaluation of the ROMA (Risk of Ovarian Malignancy Algorithm) value. In this work, a Surface Plasmon Resonance Imaging (SPRI) biosensor for circulating CA125/MUC16 has been developed. The anti-MUC16 antibody was attached to a gold chip via a cysteamine linker. The EDS/NHS protocol was used for the covalent attachment of the antibody. The developed biosensor is specific for CA125/MUC16, and exhibits good recovery and acceptable precision. Its linear response range (2.2-150 U/ml) is well suited to determination of the marker in the blood serum of a healthy control group and, after appropriate dilution, of patients with ovarian cancer. CA125/MUC16 was determined in two series of real samples: blood serum from patients with ovarian cancer and endometrial cysts. The method was validated by parallel determination of the samples using the chemiluminescent Architect i2000 method.
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