Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass

MUC16/CA125 in cancer: new advances

MUC16/CA125 is a common diagnostic marker for many types of cancer. However, due to the widespread expression of MUC16 in cancer, its specificity and sensitivity as a target are poor, which severely limits its clinical application. In recent years, various studies have shown that the clinical application potential of MUC16/CA125 has been greatly improved. The update of detection technology improves the accuracy and range of detection, and improves the early diagnosis rate of cancer. Targeting MUC16/CA125 is an important strategy for tumor therapy. Targeting residual amino acids, n-glycoylation structures or other targets on the surface of MUC16 cells can greatly improve the accuracy of detection and therapy. The new drug delivery method broke through the original technical shackles, targeted MUC16 positive cells more specifically and improved the drug efficacy. In this paper, the technological advances in detecting and identifying MUC16 targets and the great progress in cancer screening and treatment based on MUC16 as a target are described in detail, revealing the great potential of MUC16 as a target in cancer screening and treatment, and illustrating the potential clinical application value of MUC16.

Mucin-Producing Lobular Breast Carcinoma Metastasis to an Ovarian Fibroma: Histopathological and Immunohistochemical Analysis of a Rare Case and Literature Review

Breast cancer stands as the primary cause of cancer-related mortality among women worldwide, often presenting with distant metastases upon diagnosis. Ovarian metastases originating from breast cancer represent a range of 3-30% of all ovarian neoplasms. Case Report: Herein, we present the histopathological, histochemical, and immunohistochemical findings of a rare case involving mucin-producing lobular breast carcinoma metastasizing to an ovarian fibroma in an 82-year-old female previously diagnosed with lobular breast carcinoma. Histopathological examination of the excised tissues revealed a biphasic neoplasm characterized by tumor cells expressing AE-1/AE-3 cytokeratin, mammaglobin, GCDFP-15, inhibin, and calretinin. Positive mucin staining was observed using histochemical techniques, and reticulin fibers were demonstrated using the Gordon-Sweets technique. A final diagnosis of mucin-producing lobular breast carcinoma metastatic to a benign ovarian fibroma was rendered. Conclusion: The occurrence of metastatic breast carcinoma overlaid on an ovarian tumor represents a rare and diagnostically challenging scenario.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera.

METHODS

To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates.

RESULTS

We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions.

CONCLUSIONS

A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

OvaPrint-A Cell-free DNA Methylation Liquid Biopsy for the Risk Assessment of High-grade Serous Ovarian Cancer

PURPOSE

High-grade serous ovarian carcinoma (HGSOC) is the most lethal epithelial ovarian cancer (EOC) and is often diagnosed at late stage. In women with a known pelvic mass, surgery followed by pathologic assessment is the most reliable way to diagnose EOC and there are still no effective screening tools in asymptomatic women. In the current study, we developed a cell-free DNA (cfDNA) methylation liquid biopsy for the risk assessment of early-stage HGSOC.

EXPERIMENTAL DESIGN

We performed reduced representation bisulfite sequencing to identify differentially methylated regions (DMR) between HGSOC and normal ovarian and fallopian tube tissue. Next, we performed hybridization probe capture for 1,677 DMRs and constructed a classifier (OvaPrint) on an independent set of cfDNA samples to discriminate HGSOC from benign masses. We also analyzed a series of non-HGSOC EOC, including low-grade and borderline samples to assess the generalizability of OvaPrint. A total of 372 samples (tissue n = 59, plasma n = 313) were analyzed in this study.

RESULTS

OvaPrint achieved a positive predictive value of 95% and a negative predictive value of 88% for discriminating HGSOC from benign masses, surpassing other commercial tests. OvaPrint was less sensitive for non-HGSOC EOC, albeit it may have potential utility for identifying low-grade and borderline tumors with higher malignant potential.

CONCLUSIONS

OvaPrint is a highly sensitive and specific test that can be used for the risk assessment of HGSOC in symptomatic women. Prospective studies are warranted to validate OvaPrint for HGSOC and further develop it for non-HGSOC EOC histotypes in both symptomatic and asymptomatic women with adnexal masses.

Improved Prediction of Ovarian Cancer Using Ensemble Classifier and Shaply Explainable AI

The importance of detecting and preventing ovarian cancer is of utmost significance for women's overall health and wellness. Referred to as the "silent killer," ovarian cancer exhibits inconspicuous symptoms during its initial phases, posing a challenge for timely identification. Identification of ovarian cancer during its advanced stages significantly diminishes the likelihood of effective treatment and survival. Regular screenings, such as pelvic exams, ultrasound, and blood tests for specific biomarkers, are essential tools for detecting the disease in its early, more treatable stages. This research makes use of the Soochow University ovarian cancer dataset, containing 50 features for the accurate detection of ovarian cancer. The proposed predictive model makes use of a stacked ensemble model, merging the strengths of bagging and boosting classifiers, and aims to enhance predictive accuracy and reliability. This combination harnesses the benefits of variance reduction and improved generalization, contributing to superior ovarian cancer prediction outcomes. The proposed model gives 96.87% accuracy, which is currently the highest model result obtained on this dataset so far using all features. Moreover, the outcomes are elucidated utilizing the explainable artificial intelligence method referred to as SHAPly. The excellence of the suggested model is demonstrated through a comparison of its performance with that of other cutting-edge models.

Potential Roles and Future Perspectives of Chitinase 3-like 1 in Macrophage Polarization and the Development of Diseases

Chitinase-3-like protein 1 (CHI3L1), a chitinase-like protein family member, is a secreted glycoprotein that mediates macrophage polarization, inflammation, apoptosis, angiogenesis, and carcinogenesis. Abnormal CHI3L1 expression has been associated with multiple metabolic and neurological disorders, including diabetes, atherosclerosis, and Alzheimer's disease. Aberrant CHI3L1 expression is also reportedly associated with tumor migration and metastasis, as well as contributions to immune escape, playing important roles in tumor progression. However, the physiological and pathophysiological roles of CHI3L1 in the development of metabolic and neurodegenerative diseases and cancer remain unclear. Understanding the polarization relationship between CHI3L1 and macrophages is crucial for disease progression. Recent research has uncovered the complex mechanisms of CHI3L1 in different diseases, highlighting its close association with macrophage functional polarization. In this article, we review recent findings regarding the various disease types and summarize the relationship between macrophages and CHI3L1. Furthermore, this article also provides a brief overview of the various mechanisms and inhibitors employed to inhibit CHI3L1 and disrupt its interaction with receptors. These endeavors highlight the pivotal roles of CHI3L1 and suggest therapeutic approaches targeting CHI3L1 in the development of metabolic diseases, neurodegenerative diseases, and cancers.

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Comparison of Human Epididymis Protein 4, Cancer Antigen 125, and Ultrasound Prediction Model in Differentiating Benign from Malignant Adnexal Masses

Background

This study aimed to compare the diagnostic performance of carcinogenic antigen (CA) 125, (HE)-4 (Human epididymis protein 4), and ultrasound (International Ovarian Tumor Analysis [IOTA]) Simple Rules individually and to derive a composite score in the differentiating ovarian cancer from benign ovarian mass.

Subjects and Methods

Consecutive patients (n = 100) with pelvic mass admitted during February 2018-August 2019 were included prospectively. Patients with either known case of epithelial ovarian cancer (EOC) or metastatic EOC were excluded. The primary outcome was to assess the sensitivity and specificity of CA-125, HE-4, and IOTA Simple Rules in predicting benign from malignant mass independently, while secondary outcome was derivation of a new model incorporating these variables using multivariate logistic regression analysis to predict benign from malignant lesions. Receiver operator curve (ROC) was drawn to redefine the best-performing cutoff values and difference between area under the ROC (AUROC) were compared by DeLong's method.

Results

Out of 100 cases of adnexal mass selected, the sensitivity and specificity of CA-125 were 73.8% and 77.6%, HE-4 were 90.5% and 87.9%, and IOTA Simple Rules were 92.9% and 81.0%. CA-125, HE-4, and IOTA Simple Rules were independently associated with the likelihood of malignancy/borderline (P < 0.001). The area under the curve for the "composite score" (AUC = 0.93) was the highest and was significantly better than that of CA-125 (AUC = 0.786) (P = 0.004 using DeLong's test) and comparable with HE-4 (AUROC = 0.90; P = 0.128 using DeLong's Test).

Conclusion

The sensitivity and specificity of HE-4 and IOTA Simple Rules for predicting malignant ovarian tumor was better than those of CA-125. The diagnostic performance of "composite score" was comparable to those of either HE-4 or IOTA Simple Rules and significantly better than CA-125.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker - located on the mucin protein MUC16 - is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies - OC125, M11, "OC125-like," and "M11-like" - to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Point-of-care testing: a disposable label-free electrochemical CA125 and HE4 immunosensors for early detection of ovarian cancer

Cancer antigen 125 (CA125) and human epididymal secretory protein 4 (HE4) are critical biomarkers for ovarian cancer diagnosis and progression monitoring; therefore, sensitive determination of their levels in body fluids is crucial. In recent study, label-free CA125 and HE4 immunosensors were prepared using disposable screen-printed carbon electrodes modified with reduced graphene oxide, polythionine, and gold nanoparticles for the sensitive, fast, and practical determination of CA125 and HE4. Differential pulse voltammetry, square wave voltammetry, and electrochemical impedance spectroscopy methods were used for the electrochemical determination of antigens in four different linear ranges (1-100 pg mL^- 1, 0.01-10 ng mL^- 1, 10-50 ng mL^- 1, and 50-500 ng mL^- 1). High sensitivity, low limit of detection, and limit of quantification were obtained for each linear range with a correlation coefficient above 0.99. The application stability of CA125 and HE4 immunosensors was determined as 60 days, and the storage stability was determined as 16 weeks. Immunosensors showed high selectivity in nine different antigen mixtures. The reusability of the immunosensors has been tested up to 9 cycles. The Risk of Ovarian Malignancy Algorithm score% values were calculated using the concentration of CA125 and HE4 in the blood serum and evaluated in terms of ovarian cancer risk. For the point-of-care testing, CA125 and HE4 levels at pg mL^- 1 concentration were measured in blood serum samples using the developed immunosensors and a hand-held electrochemical reader in approximately 20-30 s, and high recoveries were obtained. These disposable label-free immunosensors are user-friendly and can be used in point-of-care tests for rapid and practical detection of CA125 and HE4 with high selectivity, sensitivity, and repeatability.

HE4 overexpression in mice leads to leydig cell hyperplasia and spermatogensis impairment: Pathological implications for oligospermia

Previous studies have shown that HE4 cancer biomarker promoted cancer cell proliferation and tumor growth in mouse xenograft models. Interestingly, HE4 levels are significantly increased in the seminal plasma of oligoasthenospermia patients, raising a question on HE4 role(s) in spermatogenesis. We constructed an HE4 overexpression mouse model (HE4-OE), and observed that HE4-OE male adult mice had small testes, low sperm counts, and elevated serum/testis testosterone levels. These mice exhibited disorganized seminiferous tubules and impaired spermatogenesis. HE4 overexpression concentrated in Leydig cells, and these cells had hyperplasia and increased testosterone biosynthesis. Mechanistic studies indicated that the impaired spermatogenesis was likely caused by a local and direct action of HE4 in the testis rather than by a hypothalamus/pituitary-initiated dysregulation. The new findings reveal a novel HE4 function in male reproductive system, and suggest the existence of a subtype of primary oligoasthenospermia characterized by HE4 overexpression, Leydig cell hyperplasia, and elevated testosterone levels.

A label-free dual immunosensor for the simultaneous electrochemical determination of CA125 and HE4 biomarkers for the early diagnosis of ovarian cancer

The blood levels of cancer antigen 125 (CA125) and human epididymal secretory protein 4 (HE4) are measured in the diagnosis and progression monitoring of ovarian cancer (OC), and the Risk of Ovarian Malignancy Algorithm (ROMA) score% values are calculated for cancer risk assessment. For the first time, disposable dual screen-printed carbon electrodes modified with reduced graphene oxide, polythionine, and gold nanoparticles were used to fabricate label-free electrochemical dual CA125-HE4 immunosensors for the sensitive, fast, and practical simultaneous determination of CA125 and HE4. DPV and SWV methods were used to simultaneously determine antigens in two different linear ranges (1-100 pg mL^-1 and 1-50 ng mL^-1). High sensitivity, low LOD, and LOQ were obtained for two linear ranges with a correlation coefficient above 0.99. The application stability of the dual CA125-HE4 immunosensors was determined as 60 days, and the storage stability was determined as 16 weeks. The dual immunosensors exhibited high selectivity in eight different antigen mixtures. The reusability of the dual immunosensors has been tested up to 9 cycles. ROMA score% values for pre-menopausal and post-menopausal status were calculated using the concentration of CA125 and HE4 in the blood serum and assessing OC risk. The disposable dual immunosensors can be used in point-of-care tests for rapid and practical simultaneous determination of CA125 and HE4 with high selectivity, sensitivity, and repeatability.

Copenhagen index (CPH-I) is more favorable than CA125, HE4, and risk of ovarian malignancy algorithm (ROMA): Nomogram prediction models with clinical-ultrasonographic feature for diagnosing ovarian neoplasms

Background

We aimed to analyze the benign and malignant identification efficiency of CA125, HE4, risk of ovarian malignancy algorithm (ROMA), Copenhagen Index (CPH-I) in ovarian neoplasms and establish a nomogram to improve the preoperative evaluation value of ovarian neoplasms.

Methods

A total of 3,042 patients with ovarian neoplasms were retrospectively classified according to postoperative pathological diagnosis [benign, n = 2389; epithelial ovarian cancer (EOC), n = 653]. The patients were randomly divided into training and test cohorts at a ratio of 7:3. Using CA125, HE4, ROMA, and CPH-I, Receiver operating characteristic (ROC) curves corresponding to different truncation values were calculated and compared, and optimal truncation values were selected. Clinical and imaging risk factors were calculated using univariate regression, and significant variables were selected for multivariate regression analysis combined with ROMA and CPH-I. Nomograms were constructed to predict the occurrence of EOC, and the accuracy was assessed by external validation.

Results

When the cutoff value of CA125, HE4, ROMA, and CPH-I was 100 U/ml, 70 pmol/L, 12.5/14.4% (premenopausal/postmenopausal) and 5%, respectively, the AUC was 0.674, 0.721, 0.750 and 0.769, respectively. From univariate regression, the clinical risk factors were older age, menopausal status, higher birth rate, hypertension, and diabetes; imaging risk factors were multilocular tumors, solid nodules, bilateral tumors, larger tumor diameter, and ascites. The AUC of the nomogram containing ROMA and CPH-I was 0.8914 and 0.9114, respectively, which was better than the prediction accuracies of CA125, HE4, ROMA, and CPH-I alone. The nomogram with CPH-I was significantly better than that with ROMA (P < 0.001), and a nomogram decision curve analysis (DCA) containing CPH-I seemed to have better clinical benefits than ROMA. For external validation of this nomogram containing ROMA and CPH-I, the C-indices were 0.889 and 0.900, and the calibration curves were close to 45°, showing good agreement with the predicted values.

Conclusion

We conclude that CPH-I and ROMA have higher diagnostic values in the preoperative diagnosis of EOC than other single tumor markers like CA125 or HE4. A nomogram based on CPH-I and ROMA with clinical and ultrasonic indicators had a better diagnostic value, and the CPH-I nomogram had the highest diagnostic efficacy.

Diagnostic and prognostic role of circulating neutrophil extracellular trap markers and prekallikrein in patients with high-grade serous ovarian cancer

Objective

Tumor-promoting inflammation is among the hallmarks of cancer. Prekallikrein is among the acute-phase reactants in the inflammatory response; moreover, neutrophils release nuclear contents into the extracellular space to create neutrophil extracellular traps (NET). We aimed to investigate the diagnostic and prognostic utilities of circulating plasma NET markers and prekallikrein for high-grade serous ovarian cancer (HGSOC).

Methods

Circulating levels of three NET markers (histone-DNA complex, cell-free DNA, and neutrophil elastase) and prekallikrein were measured in 75 patients with HGSOC and 23 healthy controls. We used an area under the receiver operating characteristic curve (AUC) analysis to investigate their diagnostic and prognostic utilities for HGSOC.

Results

Compared with healthy controls, patients with HGSOC showed significantly higher levels of the three NET markers and prekallikrein. Patients with advanced-stage HGSOC showed significantly higher levels of the cell-free DNA (87.4 vs. 79.5 ng/ml; P = 0.013), compared with those with early-stage HGSOC. Further, the levels of histone-DNA complex, neutrophil elastase, and prekallikrein did not significantly differ according to the cancer stage. All markers showed significant diagnostic utility. Notably, a logistic regression-based model that comprised all four markers showed the strongest diagnostic power (AUC, 0.966; 95% confidence interval [CI], 0.933-1.000). Specifically, neutrophil elastase was identified as an independent poor prognostic factor for overall survival (adjusted hazard ratio [aHR], 10.17; 95% CI, 1.09-94.97; P = 0.042) and progression-free survival (aHR, 14.47; 95% CI, 1.52-137.35; P = 0.020) in patients with HGSOC.

Conclusions

The levels of the three NET markers and prekallikrein might be novel diagnostic and prognostic markers for HGSOC.

Diagnostics of Ovarian Tumors in Postmenopausal Patients

Early diagnosis of ovarian cancer remains an urgent issue owing to the continuing trend towards increasing incidence along with only marginal improvements in mortality and 5-year survival rates. Furthermore, there is a lack of a clear formulation of the concept of pathogenesis. The diagnostic values of tumor markers, their potential advantages and disadvantages, and their combination with radiation imaging methods and transvaginal sonography are discussed. More advanced imaging techniques, such as computed tomography and magnetic resonance imaging have proven too expensive for widespread use. According to the World Health Organization, more than half of the world’s population does not have access to diagnostic imaging. Consequently, there is high demand for a low-cost, reliable, and safe imaging system for detecting and monitoring cancer. Currently, there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and for determining surgical access and optimal surgical intervention measures in postmenopausal patients are lacking. Medical microwave radiometry shows promising results yielding an accuracy of 90%.

Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer

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.

Early-Stage Detection of Ovarian Cancer Based on Clinical Data Using Machine Learning Approaches

One of the common types of cancer for women is ovarian cancer. Still, at present, there are no drug therapies that can properly cure this deadly disease. However, early-stage detection could boost the life expectancy of the patients. The main aim of this work is to apply machine learning models along with statistical methods to the clinical data obtained from 349 patient individuals to conduct predictive analytics for early diagnosis. In statistical analysis, Student’s t-test as well as log fold changes of two groups are used to find the significant blood biomarkers. Furthermore, a set of machine learning models including Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Extreme Gradient Boosting Machine (XGBoost), Logistic Regression (LR), Gradient Boosting Machine (GBM) and Light Gradient Boosting Machine (LGBM) are used to build classification models to stratify benign-vs.-malignant ovarian cancer patients. Both of the analysis techniques recognized that the serumsamples carbohydrate antigen 125, carbohydrate antigen 19-9, carcinoembryonic antigen and human epididymis protein 4 are the top-most significant biomarkers as well as neutrophil ratio, thrombocytocrit, hematocrit blood samples, alanine aminotransferase, calcium, indirect bilirubin, uric acid, natriumas as general chemistry tests. Moreover, the results from predictive analysis suggest that the machine learning models can classify malignant patients from benign patients with accuracy as good as 91%. Since generally, early-stage detection is not available, machine learning detection could play a significant role in cancer diagnosis.

Tissue factor pathway inhibitor 2: A potential diagnostic marker for discriminating benign from malignant ovarian tumors

OBJECTIVES

Carbohydrate antigen 125 (CA125), CA19-9, carcinoembryonic antigen (CEA), human epididymis protein 4 (HE4), and the Risk of Ovarian Malignancy Algorithm (ROMA) are widely used as tumor markers and algorithms for the diagnosis of ovarian cancer (OC). Tissue factor pathway inhibitor 2 (TFPI2) has been developed as a potential serodiagnostic marker for OC in Japan. The aim of this study is to evaluate the diagnostic accuracy of the six markers alone and in combination to find the best marker for discriminating between benign and malignant ovarian tumors.

METHODS

Frozen serum samples collected from 484 patients were divided into three groups based on histopathological results: OC (n = 119), borderline ovarian tumors (BR) (n = 48), and benign ovarian tumors (BN) (n = 317). Diagnostic accuracy was calculated with an area under a receiver operating characteristic (AUC) curve.

RESULTS

TFPI2 achieved the highest discrimination between the OC + BR group versus the BN group (AUC 0.8076). ROMA values best discriminated patients with OC from those with BN (AUC, 0.8966), which was equivalent to TFPI2 (AUC, 0.8937). For discriminating the OC group from the BR + BN group, the highest AUC value was achieved by ROMA values (AUC, 0.8884), and TFPI2 also showed comparable diagnostic accuracy (AUC, 0.8845). Combining TFPI2 with ROMA had the highest AUC (0.8420-0.9357).

CONCLUSION

TFPI2 may be a clinically useful single marker comparable to conventional ROMA values for discriminating between benign and malignant ovarian tumors.

Biomarkers for Early Diagnosis of Ovarian Carcinoma

The leading cause of gynecological cancer-related morbidity and mortality is ovarian cancer (OC), which is dubbed a silent killer. Currently, OC is a target of intense biomarker research, because it is often not discovered until the disease is advanced. The goal of OC research is to develop effective tests using biomarkers that can detect the disease at the earliest stages, which would eventually decrease the mortality, thereby preventing recurrence. Therefore, there is a pressing need to revisit the existing biomarkers to recognize the potential biomarkers that can lead to efficient predictors for the OC diagnosis. This Perspective covers an update on the currently available biomarkers used in the triaging of OC to gain certain insights into the potential role of these biomarkers and their estimation that are crucial to the understanding of neoplasm progression, diagnostics, and therapy.

Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis

Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and clinical practice are urgently needed. The last decade has seen increasingly rapid advances in sequencing and biotechnological methodologies. Consequently, multiple omics technologies, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra, have been widely applied to analyze tissue- and liquid-derived samples from OC patients. The integration of multi-omics data has increased our knowledge of the disease and identified valuable OC biomarkers. In this review, we summarize the recent advances and perspectives in the use of multi-omics technologies in OC research and highlight potential applications of multi-omics for identifying novel biomarkers and improving clinical assessments.

The Association between Human Epididymis Secretory Protein 4 and Metabolic Syndrome

Individuals with metabolic syndrome (MetS) are known to have an increased risk of carcinogenesis. Human epididymis protein 4 (HE4) is a tumor marker and prognostic factor for epithelial ovarian carcinoma (EOC) patients. However, no studies have evaluated the association between MetS and HE4 levels. This study aimed to evaluate the relationship between HE4 levels and MetS in the National Health and Nutrition Examination Survey (NHANES 2001−2002). This cross-sectional analysis assessed all five components of MetS and HE4 levels in 2104 females (age ≥20 years) from the NHANES dataset. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII) criteria. The analysis indicated MetS in 593 individuals, and the β coefficient of their HE4 levels was 0.097 (95% CIs, 0.028−0.166, p = 0.006). Specifically, the β coefficients of the HE4 levels of participants with 1, 2, 3, and ≥4 features of MetS were 0.072 (95% confidence interval (CI): −0.015−0.159), 0.125 (95% CI: 0.030−0.220), 0.161 (95% CI: 0.053−0.270), and 0.242 (95% CI: 0.117−0.368), respectively, and all p values were <0.001. The p-value for the trend was <0.001. There was a significant association between the presence of MetS and HE4 levels. There were positive relationships between HE4 levels and an increased number of MetS components (with 1, 2, 3, and ≥4 features of MetS, all p values <0.001). Among the MetS components, low high-density lipoprotein levels and high triglyceride levels were independently associated with HE4 levels.

Comparison of HE4, CA125, ROMA and CPH-I for Preoperative Assessment of Adnexal Tumors

(1) OBJECTIVE: To assess the performance of CA125, HE4, ROMA index and CPH-I index to preoperatively identify epithelial ovarian cancer (EOC) or metastatic cancer in the ovary (MCO). (2) METHODS: single center retrospective study, including women with a diagnosis of adnexal mass. We obtained the AUC, sensitivity, specificity and predictive values were of HE4, CA125, ROMA and CPH-I for the diagnosis of EOC and MCO. Subgroup analysis for women harboring adnexal masses with inconclusive diagnosis of malignancy by ultrasound features and Stage I EOC was performed. (3) RESULTS: 1071 patients were included, 852 (79.6%) presented benign/borderline tumors and 219 (20.4%) presented EOC/MCO. AUC for HE4 was higher than for CA125 (0.91 vs. 0.87). No differences were seen between AUC of ROMA and CPH-I, but they were both higher than HE4 AUC. None of the tumor markers alone achieved a sensitivity of 90%; HE4 was highly specific (93.5%). ROMA showed a sensitivity and specificity of 91.1% and 84.6% respectively, while CPH-I showed a sensitivity of 91.1% with 79.2% specificity. For patients with inconclusive diagnosis of malignancy by ultrasound features and with Stage I EOC, ROMA showed the best diagnostic performance (4) CONCLUSIONS: ROMA and CPH-I perform better than tumor markers alone to identify patients harboring EOC or MCO. They can be helpful to assess the risk of malignancy of adnexal masses, especially in cases where ultrasonographic diagnosis is challenging (stage I EOC, inconclusive diagnosis of malignancy by ultrasound features).

[Clinical use and evolution of circulating biomarkers in the era of personalized oncology: From protein markers to bioclinical scores]

In oncology, the identification of targets that correlate with a type of cancer has led to a profound change in the notion of "tumor markers". Technological advances, in particular the development of high-throughput sequencing, have led to the emergence of a new generation of molecular biomarkers for tumors. Despite their limited utility for screening and diagnosis, conventional tumor markers remain interesting for evaluation of prognoses, the choice and optimization of treatments, as well as for monitoring the effectiveness of those treatments. In this article, we revisit the conventional serum markers that are enjoying a 'come back' thanks to the development of high-performance scores based on biological, cytological, clinical, or radiological criteria.

Chemokine expression in patients with ovarian cancer or benign ovarian tumors

INTRODUCTION

Chemokines play a crucial role in tumor growth and progression according to proangiogenic and immunosuppressive action. The aim of this study was to investigate the serum levels of selected chemokines in patients with ovarian cancer or benign ovarian tumors to assess their role in tumorigenesis and their potential use in preoperative diagnosis of an adnexal mass.

MATERIAL AND METHODS

The study group consisted of 59 women with ovarian cancer: 17 epithelial ovarian cancer (EOC) patients and 42 women with benign ovarian tumors. We measured in sera obtained preoperatively the level of CA125 and a panel of 5 chemokines - CX3CL1/fractalkine, CXCL1/GRO-α, CXCL12/SDF-1, CCL20/MIP-3α and IL-17F - using the chemiluminescence method with multiplexed bead based immunoassay.

RESULTS

CX3CL1 was significantly elevated in sera of advanced ovarian cancer patients compared to women with benign ovarian tumors. The significant elevation of CXCL1 was also observed (both early and advanced stages). A similar pattern was present with the standard ovarian cancer marker CA125. In our patients with endometriotic cysts CA125 levels were significantly higher than in women with other benign tumors, whereas all analyzed chemokines had similar serum titers in patients with endometriotic vs. other benign ovarian cysts.

CONCLUSIONS

CX3CL1 and CXCL1 are elevated in sera of EOC patients, which indicates their role in cancer development. Moreover, they might be useful in preoperative differential diagnosis of ovarian tumors, especially as they were not elevated in cases of endometriosis.

Analysis of serum HE4 levels in various histologic subtypes of epithelial ovarian cancer and other malignant tumors

BACKGROUND: The measurement of serum HE4 levels has emerged as a sensitive and specific biomarker for epithelial ovarian cancers (EOCs). However, serum levels in women diagnosed with various histologic subtypes of EOC and in women with metastatic non-ovarian primary malignancies have not been widely reported. OBJECTIVE: The goal of this study was to identify how serum HE4 levels vary in women diagnosed with different histologic subtypes of EOC and non-ovarian malignancies. METHODS: Data from six prospective pelvic mass clinical trials was combined and an evaluation of serum HE4 levels in women diagnosed with a malignancy was performed. For all patients, serum was obtained prior to surgery and final pathology, including primary tumor site, histologic subtype, grade and stage, were recorded. The mean, median, standard deviation, maximum, and minimum HE4 levels were determined for each group. RESULTS: A total of 984 patients were included in this study, with the average patient age being 60 years old. There were 230 premenopausal and 754 postmenopausal patients. Serum HE4 levels were elevated (≥70.0 pMol) in 85%of EOCs, 40%of LMP tumors, 21%of non-EOCs (germ cell tumors), 25%of cervical cancers, and 47%of non-gynecologic metastatic cancers. Analysis of histologic subtypes revealed 90%(n = 391) of serous, 85%(n = 73) of endometrioid, 45%(n = 42) of mucinous, 86%(n = 51) of mixed tumors, and 69%(n = 36) of clear cell tumors had elevated serum HE4 levels. CONCLUSIONS: Serum HE4 levels are most often elevated in women with high grade serous and endometrioid EOCs, and though serum elevations are seen more often with advanced stage disease, HE4 is also often elevated in early stage disease and lower grade tumors.

New Trends in the Detection of Gynecological Precancerous Lesions and Early-Stage Cancers

The prevention and early diagnostics of precancerous stages are key aspects of contemporary oncology. In cervical cancer, well-organized screening and vaccination programs, especially in developed countries, are responsible for the dramatic decline of invasive cancer incidence and mortality. Cytological screening has a long and successful history, and the ongoing implementation of HPV triage with increased sensitivity can further decrease mortality. On the other hand, endometrial and ovarian cancers are characterized by a poor accessibility to specimen collection, which represents a major complication for early diagnostics. Therefore, despite relatively promising data from evaluating the combined effects of genetic variants, population screening does not exist, and the implementation of new biomarkers is, thus, necessary. The introduction of various circulating biomarkers is of potential interest due to the considerable heterogeneity of cancer, as highlighted in this review, which focuses exclusively on the most common tumors of the genital tract, namely, cervical, endometrial, and ovarian cancers. However, it is clearly shown that these malignancies represent different entities that evolve in different ways, and it is therefore necessary to use different methods for their diagnosis and treatment.

Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer

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.

Low serum T3 levels are associated with false-positive results when using the risk of ovarian malignancy algorithm (ROMA) in women with benign ovarian disease

OBJECTIVE

We investigated factors that could cause false-positive results when using the risk of ovarian malignancy algorithm (ROMA) for assessing ovarian cancer risk.

MATERIALS AND METHODS

ROMA scores were calculated from patients followed surgery to remove a pelvic mass. We compared a false-positive group with a true-negative group of ROMA scores.

RESULTS

We analyzed 324 patients using medical records. There were 22 with an epithelial ovarian cancer (EOC), 15 with a borderline ovarian tumor, and 287 with benign disease. Twenty-nine (10.1%) of the patients with benign disease showed high-risk ROMA score (false positive) and 13/37 (35%) patients with EOC, or borderline ovarian tumor showed low ROMA scores (false negatives). The median serum triiodothyronine (T3) level of the false-positive ROMA group in patients with benign disease was lower than in the true-negative ROMA group (p < 0.001) and the estimated glomerular filtration rate (eGFR) was also lower (p = 0.001) in the false-positive ROMA group. Median serum T3 levels in the true-positive ROMA group among patients with EOC, or borderline ovarian tumor were lower than in the false-negative ROMA group (p = 0.043).

CONCLUSION

Median serum T3 level and eGFR in the false-positive ROMA group in patients with benign ovarian disease were lower than in the true-negative group.

Guideline No. 403: Initial Investigation and Management of Adnexal Masses

OBJECTIVES

To aid primary care physicians, emergency medicine physicians, and gynaecologists in the initial investigation of adnexal masses, defined as lumps that appear near the uterus or in or around ovaries, fallopian tubes, or surrounding connective tissue, and to outline recommendations for identifying women who would benefit from a referral to a gynaecologic oncologist for further management.

INTENDED USERS

Gynaecologists, obstetricians, family physicians, general surgeons, emergency medicine specialists, radiologists, sonographers, nurses, medical learners, residents, and fellows.

TARGET POPULATION

Adult women 18 years of age and older presenting for the evaluation of an adnexal mass.

OPTIONS

Women with adnexal masses should be assessed for personal risk factors, history, and physical findings. Initial evaluation should also include imaging and laboratory testing to triage women for management of their care either by a gynaecologic oncologist or as per SOGC guideline no. 404 on the initial investigation and management of benign ovarian masses.

EVIDENCE

A search of PubMed, Cochrane Wiley, and the Cochrane systematic reviews was conducted in January 2018 for English-language materials involving human subjects published since 2000 using three sets of terms: (i) ovarian cancer, ovarian carcinoma, adnexal disease, ovarian neoplasm, adnexal mass, fallopian tube disease, fallopian tube neoplasm, ovarian cyst, and ovarian tumour; (ii) the above terms in combination with predict neoplasm staging, follow-up, and staging; and (iii) the above two sets of terms in combination with ultrasound, tumour marker, CA 125, CEA, CA19-9, HE4, multivariable-index-assay, risk-of-ovarian-malignancy-algorithm, risk-of-malignancy-index, diagnostic imaging, CT, MRI, and PET. Relevant evidence was selected for inclusion in descending order of quality of evidence as follows: meta-analyses, systematic reviews, guidelines, randomized controlled trials, prospective cohort studies, observational studies, non-systematic reviews, case series, and reports. Additional articles were identified through cross-referencing the identified reviews. The total number of studies identified was 2350, with 59 being included in this review.

VALIDATION METHODS

The content and recommendations were drafted and agreed upon by the authors. The Executive and Board of the Society of Gynecologic Oncology of Canada reviewed the content and submitted comments for consideration. The Board of Directors of the Society of Obstetricians and Gynaecologists of Canada approved the final draft for publication. The quality of evidence was rated using the criteria described in the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology framework (Table A1 of Online Appendix A). See Table A2 of Online Appendix A for the interpretation of strong and weak recommendations. The summary of findings is available upon request.

BENEFITS, HARMS, COSTS

Adnexal masses are common, and guidelines on how to triage them and manage the care of patients presenting with adnexal masses will continue to guide the practice of primary care providers and gynaecologists. Ovarian cancer outcomes are improved when initial surgery is performed by a gynaecologic oncologist, likely as a result of complete surgical staging and optimal cytoreduction. Given these superior outcomes, guidelines to assist in the triage of adnexal masses and the referral and management of the care of patients with an adnexal mass are critical.

SUMMARY STATEMENTS (GRADE RATINGS IN PARENTHESES)

RECOMMENDATIONS (GRADE RATINGS IN PARENTHESES).

Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.

Epidemiologic and biologic correlates of serum HE4 and CA125 in women from the National Health and Nutritional Survey (NHANES)

OBJECTIVES

In women with ovarian cancer, tumor features largely determine serum HE4 and CA125 levels, but non-tumor factors may also influence levels and be better understood by studying determinants in a well-characterized sample of women without cancer.

METHODS

Serum HE4 and CA125 were measured in 2302 women from the 2001-2002 cohort of the National Heath and Nutritional Survey (NHANES). Publicly-available data on this cohort included demographic/reproductive variables, blood counts, and measurements of C-reactive protein (CRP), total homocysteine (tHcy), cotinine, and creatinine which were examined as predictors of HE4 and CA125 using multivariate models and correlational analyses.

RESULTS

HE4 increased non-linearly by age and current smokers had higher HE4. CA125 was lower in postmenopausal women and non-whites and trended downward with increasing BMI. Current-users of oral contraceptives (OCs) had lower HE4 and CA125; and a downward trend for CA125 was seen with increasing OC use. Pregnant women had higher CA125 and nursing women higher HE4. HE4 and CA125 were positively correlated with neutrophils, monocytes, and the neutrophil-to-lymphocyte ratio and inversely correlated with lymphocytes and the lymphocyte-to-monocyte ratio. CRP was positively correlated with both HE4 and CA125 in postmenopausal women. Strong positive correlations existed for HE4 with both tHcy and creatinine.

CONCLUSIONS

Serum levels of HE4 and CA125 are influenced by several hormonal or environmental stimuli which affect non-cancerous tissues normally expressing HE4 or CA125. Cytokine co-expression in those tissues may, in turn, affect white cell counts and account for their correlation with HE4 or CA125 levels.

Racial/ethnic differences in average CA125 and CA15.3 values and its correlates among postmenopausal women in the USA

PURPOSE

Among healthy postmenopausal women, levels of CA125 and CA15.3 are influenced by demographic and reproductive factors, including race/ethnicity. In this study, we sought to examine the interaction between race/ethnicity and other correlates of these biomarkers and whether the racial differences observed are simply determined by other correlates with racial differences.

METHODS

In archived sera from 946 postmenopausal women who participated in the 2001-2002 cycle of the National Health and Nutrition Examination Survey, we measured CA125 and CA15.3 and examined their associations with health survey and examination data available in this cohort. We used multivariable linear regression to examine the association between CA125 and CA15.3 and race/ethnicity. We then calculated geometric means of these markers by demographic and reproductive factors stratified by race/ethnicity and used likelihood ratio tests to evaluate heterogeneity.

RESULTS

Non-white race was associated with lower CA125, with Non-Hispanic Black women being associated with - 29.0% (95% CI - 42.5%, - 12.2%) difference and Mexican American women being associated with - 6.4% (95% CI - 18.1%, 6.9%) difference on average compared to Non-Hispanic White women. Associations between CA125 and age and parity varied by race/ethnicity. Non-Hispanic Black women were associated with higher CA15.3 compared to Non-Hispanic White women, with 17.3% (95% CI - 0.5%, 38.3%) differences on average. Associations between CA15.3 and age, number of births, and age at natural menopause varied by race/ethnicity.

CONCLUSIONS

Among postmenopausal women, Non-Hispanic Black women were associated with lower CA125 and higher CA15.3 levels compared to Non-Hispanic White women. Our results support that race/ethnicity should be considered when assigning thresholds for these biomarkers being tested for diagnostic or screening purposes.

CA125 and Ovarian Cancer: A Comprehensive Review

Simple Summary

CA125 has been the most promising biomarker for screening ovarian cancer; however, it still does not have an acceptable accuracy in population-based screening for ovarian cancer. In this review article, we have discussed the role of CA125 in diagnosis, evaluating response to treatment and prognosis of ovarian cancer and provided some suggestions in improving the clinical utility of this biomarker in the early diagnosis of aggressive ovarian cancers. These include using CA125 to screen individuals with symptoms who seek medical care rather than screening the general population, increasing the cutoff point for the CA125 level in the plasma and performing the test at point-of-care rather than laboratory testing. By these strategies, we would detect more aggressive ovarian cancer patients in stages that the tumour can be completely removed by surgery, which is the most important factor in redusing recurrence rate and improving the survival of the patients with ovarian cancer.

Abstract

Ovarian cancer is the second most lethal gynecological malignancy. The tumour biomarker CA125 has been used as the primary ovarian cancer marker for the past four decades. The focus on diagnosing ovarian cancer in stages I and II using CA125 as a diagnostic biomarker has not improved patients’ survival. Therefore, screening average-risk asymptomatic women with CA125 is not recommended by any professional society. The dualistic model of ovarian cancer carcinogenesis suggests that type II tumours are responsible for the majority of ovarian cancer mortality. However, type II tumours are rarely diagnosed in stages I and II. The recent shift of focus to the diagnosis of low volume type II ovarian cancer in its early stages of evolution provides a new and valuable target for screening. Type II ovarian cancers are usually diagnosed in advanced stages and have significantly higher CA125 levels than type I tumours. The detection of low volume type II carcinomas in stage IIIa/b is associated with a higher likelihood for optimal cytoreduction, the most robust prognostic indicator for ovarian cancer patients. The diagnosis of type II ovarian cancer in the early substages of stage III with CA125 may be possible using a higher cutoff point rather than the traditionally used 35 U/mL through the use of point-of-care CA125 assays in primary care facilities. Rapid point-of-care testing also has the potential for effective longitudinal screening and quick monitoring of ovarian cancer patients during and after treatment. This review covers the role of CA125 in the diagnosis and management of ovarian cancer and explores novel and more effective screening strategies with CA125.

The Early Detection Research Network: A National Infrastructure to Support the Discovery, Development, and Validation of Cancer Biomarkers

In 2000, the NCI (Rockville, MD) established the Early Detection Research Network (EDRN) to identify, develop, and validate biomarkers to improve the detection of early-stage cancers and risk assessment. This consortium of more than 300 investigators at academic institutions and in the private sector is working collaboratively to bring biomarkers and imaging methods to clinical fruition. Although significant roadblocks have hindered the field of biomarker discovery and validation, the EDRN has helped overcome many of them by setting well-defined strategies and milestones focused on solving defined unmet clinical needs. The EDRN has implemented measures to improve biomarker discovery and validation, such as data sharing, use of common data elements, generating multidisciplinary and multi-institutional collaborations within a cohesive and productive team environment, and putting emphasis on quality control and data replication for all candidate biomarkers for reaching a "go" or "no go" decision. A measure of the success of the EDRN is the number of biomarkers tests or devices approved by the FDA to which EDRN investigators have made significant contributions and the number of biomarkers tests developed by EDRN investigators that are available in Clinical Laboratory Improvement Amendments laboratories.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

A multiplex biomarker assay improves the diagnostic performance of HE4 and CA125 in ovarian tumor patients

OBJECTIVE

Survival in epithelial ovarian cancer (EOC) remains poor. Most patients are diagnosed in late stages. Early diagnosis increases the chance of survival. We used the proximity extension assay from Olink Proteomics to search for new protein biomarkers with the potential to improve the diagnostic performance of CA125 and HE4 in patients with ovarian tumors.

MATERIAL AND METHODS

Plasma samples were obtained from 180 women with ovarian tumors; 30 cases of benign tumor, 28 cases with borderline tumors, 25 early EOC cases (FIGO stage I) and 97 advanced EOC cases (FIGO stages II-IV). Proteins were measured using the Olink® Oncology II and Inflammation panels. For statistical analyses, patients were categorized into benign tumors versus cancer and benign tumors versus borderline + cancer, respectively.

RESULTS

We analyzed 177 biomarkers. Thirty-four proteins had ROC AUC > 0.7 for discrimination between benign tumors and cancer. Fifteen proteins had ROC AUC > 0.7 for discrimination between benign tumors and borderline tumors + cancer. HE4 ranked highest for both comparisons. A reference model with HE4, CA125 and age (AUC 0.838 for benign tumors vs. cancer and AUC 0.770 for benign tumors vs. borderline tumors + cancer) was compared to the reference model with the addition of each of the remaining proteins with AUC > 0.7. ITGAV was the only individual biomarker found to improve diagnostic performance of the reference model, to AUC 0.874 for benign tumors vs. cancer and AUC 0.818 for benign tumors vs. borderline tumors + cancer (p < 0.05). Cross-validation and LASSO regression was combined to select multiple biomarker combinations. The best performing model for discrimination between benign tumors and borderline tumors + cancer was a 6-biomarker combination (HE4, CA125, ITGAV, CXCL1, CEACAM1, IL-10RB) and age (AUC 0.868, sensitivity 0.86 and specificity 0.82, p = 0.016 for comparison with the reference model).

CONCLUSION

HE4 was the best performing individual biomarker for discrimination between benign ovarian tumors and EOC including borderline tumors. The addition of other carcinogenesis-related biomarkers in a multiplex biomarker panel can improve the diagnostic performance of the established biomarkers HE4 and CA125.

High-throughput approaches for precision medicine in high-grade serous ovarian cancer

High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC.

Differential blood count as triage tool in evaluation of pelvic masses

OBJECTIVE

Triaging patients with presumptive ovarian cancer to the appropriate specialist may improve survival. Therefore, there is increasing interest in complementary diagnostic markers to the standard serum CA125. In patients with pelvic masses, we examined the ability of epidemiologic variables and preoperative differential blood counts to improve detection of ovarian cancer over CA125 alone.

METHODS

From pathology reports, patients were classified as having: epithelial ovarian cancer (n=743), including fallopian tube and primary peritoneal cancer, non-epithelial ovarian cancers (n=46), non-ovarian cancers (n=122), or benign disease (1,129). From women with epithelial ovarian cancer, we excluded those who received prior neoadjuvant chemotherapy (n=19). Women were also excluded if they did not have a serum CA125 or complete blood count measured within 180 days prior to surgery (n=1099) or did not have both tests within 90 days of each other (n=13). Categorizing patients by menopausal status, we calculated Pearson correlations between differential counts or ratios and CA125, and used t tests to identity univariate predictors of malignancy and stepwise logistic regression and likelihood ratio tests to create models best distinguishing epithelial ovarian cancer from benign disease.

RESULTS

337 women with epithelial ovarian cancer and 365 with benign disease were included in the analysis. Compared with cancers, women with benign disease had lower average: age, 52.5 versus 58.4 years (p<0.0001); serum CA125, 20 versus 239 U/mL (p<0.0001), neutrophil-to-lymphocyte ratio, 2.4 versus 3.5 (p<0.0001); and platelet-to-lymphocyte ratio, 158 versus 222 (p<0.0001); but greater average body mass index, 28.5 versus 26.8 kg/m² (p=0.004), and lymphocyte-to-monocyte ratio, 5.6 versus 3.9 (p<0.0001). Correlations between counts and ratios and serum CA125 were seen in both epithelial ovarian cancer and benign disease groups and differed by menopausal status. In premenopausal women, a multivariate model including serum CA125, smoking, family history, lymphocytes, and monocytes performed similarly to the model with lymphocyte-to-monocyte ratio replacing counts. In postmenopausal women, a model including body mass index, parity, monocytes, and basophils performed similarly to the model replacing counts with platelet-to-lymphocyte ratio and lymphocyte-to-monocyte ratio. Models including epidemiologic variables and either counts or ratios were better at fitting data than models with serum CA125 and menopausal status alone. A single model applying to all women overstated performance for premenopausal women and understated performance for postmenopausal women.

CONCLUSIONS

Epidemiologic variables and differential counts or ratios better distinguished between benign and malignant disease when compared with serum CA125 alone using separate models for pre- and postmenopausal women.

Using machine learning to predict ovarian cancer

OBJECTIVE

Ovarian cancer (OC) is one of the most common types of cancer in women. Accurately prediction of benign ovarian tumors (BOT) and OC has important practical value.

METHODS

Our dataset consists of 349 Chinese patients with 49 variables including demographics, blood routine test, general chemistry, and tumor markers. Machine learning Minimum Redundancy - Maximum Relevance (MRMR) feature selection method was applied on the 235 patients' data (89 BOT and 146 OC) to select the most relevant features, with which a simple decision tree model was constructed. The model was tested on the rest of 114 patients (89 BOT and 25 OC). The results were compared with the predictions produced by using the risk of ovarian malignancy algorithm (ROMA) and logistic regression model.

RESULTS

Eight notable features were selected by MRMR, among which two were identified as the top features by the decision tree model: human epididymis protein 4 (HE4) and carcinoembryonic antigen (CEA). Particularly, CEA is a valuable marker for OC prediction in patients with low HE4. The model also yields better prediction result than ROMA.

CONCLUSION

Machine learning approaches were able to accurately classify BOT and OC. Our goal is to derive a simple predictive model which also carries a good performance. Using our approach, we obtained a model that consists of just two biomarkers, HE4 and CEA. The model is simple to interpret and outperforms the existing OC prediction methods. It demonstrates that the machine learning approach has good potential in predictive modeling for the complex diseases.

Scoring systems for the evaluation of adnexal masses nature: current knowledge and clinical applications

Adnexal masses are a common finding in women, with 20% of them developing at least one pelvic mass during their lifetime. There are more than 30 different subtypes of adnexal tumours, with multiple different subcategories, and the correct characterisation of the pelvic masses is of paramount importance to guide the correct management. On that basis, different algorithms and scoring systems have been developed to guide the clinical assessment. The first scoring system implemented into the clinical practice was the Risk of Malignancy Index, which combines ultrasound evaluation, menopausal status, and serum CA-125 levels. Today, current guidelines regarding female patients with adnexal masses include the application of International Ovarian Tumours Analysis simple rules, logistic regression model 1 (LR1) and LR2, OVERA, cancer ovarii non-invasive assessment of treating strategy, and assessment of Different Neoplasias in the adnexa. In this scenario, the choice of the scoring system for the discrimination between benign and malignant ovarian tumours can be complex when approaching patients with adnexal masses. This review aims to summarise the available evidence regarding the different scoring systems to provide a complete overview of the topic.

Comparison of the predictive performance of risk of malignancy indexes 1-4, HE4 and risk of malignancy algorithm in the triage of adnexal masses

OBJECTIVES

For patients presenting with adnexal mass, it is important to correctly distinguish whether the mass is benign or malignant for the purpose of precise and timely referral and implication of correct line of management. The objective of this study was to evaluate the performance of Risk of malignancy Indexes (RMI) 1-4, Human Epididymis Protein 4 (HE4) and Risk of Malignancy Algorithm (ROMA) in differentiating the adnexal mass into benign and malignant.

METHODS

A retrospective study using 155 patients diagnosed with adnexal mass between January 2014 to December 2014 in The First Affiliated Hospital of Zhengzhou University was conducted. The patient records were assessed for age, menopausal status, serum CA125 and HE4 levels, ultrasound characteristics of the pelvic mass and the final pathological diagnosis of the mass. RMI1, RMI2, RMI3, RMI4, ROMA were calculated for each patient and the sensitivity, specificity and the Receiver Operating Characteristics (ROC) curves were determined for each test to evaluate their performance.

RESULTS

Among 155 patients with adnexal masses meeting inclusion criteria, 120 (77.4%) were benign, 8 (5.2%) borderline and 27 (17.4%) were malignant. RMI2 and RMI4 had the highest sensitivity (66.7%) while HE4 had the highest specificity (96.9%).Although ROMA had the highest area under the curve (AUC) of 0.886 it was not found to be statistically superior to the other tests. For epithelial ovarian cancers, ROMA (80%), HE4 (96.9%) and RMI 4 (0.868) had the highest sensitivity, specificity and AUC respectively however, the AUC characteristics were not statistically significant between any groups. Compared to the postmenopausal group (sensitivity 72.2-77.8%) all the tests showed lower sensitivity (42.9%) for the premenopausal group of patients.

CONCLUSIONS

RMI 1-4, ROMA and HE4 were all found to be useful for differentiating benign/borderline adnexal masses from malignant ones for deciding optimal therapy, however no test was found to be significantly better than the other. None were able to differentiate between benign and borderline tumors. All of the tests demonstrated increased sensitivity when borderline tumors were considered low-risk, and when only epithelial ovarian cancers were considered.

Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors

To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors, we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016. Age, menopausal status, histopathology, the International Federation of Gynecology and Obstetrics (FIGO) stages, tumor biomarker levels, and detailed ultrasound reports of patients were collected. The area under the curve (AUC), sensitivity, and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve. Of the 719 patients, 531 had benign lesions, 119 had epithelial ovarian cancers (EOC), 44 had borderline ovarian tumors (BOT), and 25 had non-EOC. AUCs and the sensitivity of cancer antigen 125 (CA125), human epididymis-specific protein 4 (HE4), Risk of Ovarian Malignancy Algorithm (ROMA), Risk of Malignancy Index (RMI1), HE4 model, and Rajavithi-Ovarian Cancer Predictive Score (R-OPS) in the overall population were 0.792, 0.854, 0.856, 0.872, 0.893, 0.852, and 70.2%, 56.9%, 69.1%, 60.6%, 77.1%, 71.3%, respectively. For distinguishing EOC from benign tumors, the AUCs and sensitivity of the above mentioned predictors were 0.888, 0.946, 0.947, 0.949, 0.967, 0.966, and 84.0%, 79.8%, 87.4%, 84.9%, 90.8%, 89.1%, respectively. Their specificity in predicting benign diseases was 72.9%, 94.4%, 87.6%, 95.9%, 86.3%, 90.8%, respectively. Therefore, we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.

Pre-operative sera interleukin-6 in the diagnosis of high-grade serous ovarian cancer

Pre-operative discrimination of malignant masses is crucial for accurate diagnosis and prompt referral to a gynae oncology centre for optimal surgical intervention. HGSOC progression is correlated with local and systemic inflammation. We hypothesised that inclusion of inflammatory biomarkers in sera may improve diagnostic tests. In the training cohort, we tested four existing clinical tests (RMI score and ROMA, CA125 and HE4) and a panel of 28 immune soluble biomarkers in sera from 66 patients undergoing surgery for suspected ovarian cancer. Six promising immune biomarkers alone, or in combination with conventional tests, were subsequently analysed in an independent validation cohort (n = 69). IL-6 was identified as the main driver of variability followed closely by conventional diagnostic tests. Median sera IL-6 was higher in HGSOC patients compared to those with a benign mass or controls with normal ovaries (28.3 vs 7.3 vs 1.2 pg/ml, p < 0.0001). The combination of IL-6 further improved the overall predictive probability of the conventional tests. Modelling a two-step triage of women with a suspicious ovarian mass, with IL-6 > 3.75 pg/ml as primary triage followed by conventional tests (CA125 or RMI score) identified ovarian cancer in patients with a misclassification rate of 4.54–3.03%, superior to the use of CA125 or RMI alone (9.09 to 10.60). The validation cohort demonstrated a similar improvement in the diagnostic sensitivity following addition of IL-6. IL-6 in combination with conventional tests may be a useful clinical biomarker for triage of patients with a suspected malignant ovarian mass.

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

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.

A diagnostic approach for differentiating abdominal tuberculosis from ovarian malignancy: a case series and literature review

Background

Abdominal tuberculosis is an uncommon variant of extrapulmonary tuberculosis. It accounts for 3.5% of extrapulmonary tuberculosis. Diagnosis of abdominal tuberculosis is still a challenge due to its non-specific symptoms. Abdominal tuberculosis and ovarian cancer may show similar symptoms, laboratory and imaging features. The goal of our report is to emphasize for the need of a diagnostic approach based on clinical manifestations, laboratory, imaging findings, and additional tests for considering a diagnosis of abdominal tuberculosis rather than ovarian cancer.

Case presentation

We report 3 cases of abdominal tuberculosis in our Onco-gynaecology Division, Department of Obstetrics and Gynaecology, Sardjito Hospital, Yogyakarta, Indonesia in 2018 which were previously diagnosed as ovarian malignancy and managed surgically. All of our patients experienced abdominal pain and enlargement but only two of them had significant weight loss. The general symptoms were typically found in onco-gynaecology patients, especially in those with ovarian malignancy. Ultrasound examination showed multilocular masses, 2 of them with solid parts and ascites. Cancer antigen 125 (CA-125) levels were found increasing in those three patients. All of them were treated surgically and diagnosis of abdominal tuberculosis was established through the histopathological result of tissue biopsy. Based on our cases and literature, we consider the need of a diagnostic approach to differentiate abdominal tuberculosis from ovarian malignancy, an attempt to avoid unnecessary invasive procedures that put burden risk for the patients.

Conclusion

Minimally invasive tests to establish the diagnosis of abdominal tuberculosis should be optimized to reduce the burden risk of laparotomy. Careful diagnostic steps should be followed to avoid wrong diagnosis.

Detection of Epithelial Ovarian Cancer using C8Magnetic Bead Separation and MALDI-TOF Plasma Proteome Profiling in Egyptian Females

Background:

Ovarian cancer is the seventh most common cancer in females with the highest mortality rate of all gynecological cancers due to its late discovery and ambiguous symptoms. Thus, there is a need for new promising strategies to diagnose ovarian cancer. We aimed at finding a characteristic plasma proteome pattern that could be used for the detection of epithelial ovarian cancer, in comparison with benign ovarian masses and healthy controls. We also aimed at differentiating between profiling of plasma proteins in early and advanced stages of ovarian cancer and between serous and non-serous histopathological types.

Methods:

The combination of MagSi-proteomics C8 beads, Ultraflextreme MALDI-TOF and ClinPro Tools software was used to compare the plasma protein spectra from 50 patients with epithelial ovarian cancer, 20 patients with benign ovarian masses and 50 age matched healthy females.

Results:

A plasma proteome profile of 21 peaks differentiated patients with epithelial ovarian cancer from healthy controls with a sensitivity of 73 % and a specificity of 82.8% upon external validation, while a 5-peak profile differentiated patients with epithelial ovarian cancer from patients with benign ovarian masses with a sensitivity of 81% and a specificity of 73.7%. A 20 peak profile was generated to discriminate between early and late stages of the disease with 88.3% recognition capability and 70% cross validation.

Conclusion:

MALDI-TOF proteomic profiling represents a promising potential tool for diagnosing epithelial ovarian cancer, discriminating between early and advanced stages and between serous and non- serous types.

CPH-I and HE4 Are More Favorable Than CA125 in Differentiating Borderline Ovarian Tumors from Epithelial Ovarian Cancer at Early Stages

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.

Diagnostic plasma miRNA-profiles for ovarian cancer in patients with pelvic mass

Background

Ovarian cancer is the fifth most common cancer in women worldwide. Moreover, there are no reliable minimal invasive tests to secure the diagnosis of malignant pelvic masses. Cell-free, circulating microRNAs have the potential as diagnostic biomarkers in cancer. Here, we performed and validated a miRNA panel with the potential to distinguish OC from benign pelvic masses.

Methods

The profile of plasma microRNA was determined with a panel of 46 candidates in a discovery group and a validation group, each consisting of 190 pre-surgery plasma samples from age-matched patients with malignant (n = 95) and benign pelvic mass (n = 95), by real time RT-qPCR.

Results

Four up-regulated (miR-200c-3p, miR-221-3p, miR-21-5p, and miR-484) and two down-regulated (miR-195-5p and miR-451a) microRNAs were discovered. From those, miR-200c-3p and miR-221-3p were further confirmed in a validation cohort. A combination of these 2 microRNAs together with CA-125 yielded an overall diagnostic accuracy of AUC = 0.96.

Conclusions

We showed consistent plasma microRNA profiles that provide independent diagnostic information of late stage OC.