HE4, CA125 and risk of ovarian malignancy algorithm (ROMA) as diagnostic tools for ovarian cancer in patients with a pelvic mass: An Italian multicenter study. Gynecol Oncol. 2016;141:303-311. [PMID: 26801941 DOI: 10.1016/j.ygyno.2016.01.016]

Immunogenic Biomarkers HMGB1 and sRAGE Are Potential Diagnostic Tools for Ovarian Malignancies

BACKGROUND

High mobility group box 1 (HMGB1), soluble receptor of advanced glycation end products (sRAGE) and programmed cell death markers PD-1 and PD-L1 are immunogenic serum biomarkers that may serve as novel diagnostic tools for cancer diagnosis.

METHODS

We investigated the four markers in sera of 231 women, among them 76 with ovarian cancer, 87 with benign diseases and 68 healthy controls, using enzyme immunoassays. Discrimination between groups was calculated using receiver operating characteristic (ROC) curves and sensitivities at fixed 90% and 95% specificities.

RESULTS

HMGB1 levels were significantly elevated and sRAGE levels were decreased in cancer patients as compared to benign and healthy controls. In consequence, the ratio of HMGB1 and sRAGE discriminated best between diagnostic groups. The areas under the curve (AUCs) of the ROC curves for differentiation of cancer vs. healthy were 0.77 for HMGB1, 0.65 for sRAGE and 0.78 for the HMGB1/sRAGE ratio, and slightly lower for the differentiation of cancer vs. benigns with 0.72 for HMGB1, 0.61 for sRAGE and 0.74 for the ratio of both. The highest sensitivities for cancer detection at 90% specificity versus benign diseases were achieved using HMGB1 with 41.3% and the HMGB1/sRAGE ratio with 39.2%, followed by sRAGE with 18.9%. PD-1 showed only minor and PD-L1 no power for discrimination between ovarian cancer and benign diseases.

CONCLUSION

HMGB1 and sRAGE have differential diagnostic potential for ovarian cancer detection and warrant inclusion in further validation studies.

Diagnostic value of CA125, HE4, and systemic immune-inflammation index in the preoperative investigation of ovarian masses

This study aimed to ascertain the diagnostic accuracy of CA125, HE4, systemic immune-inflammation index (SII), fibrinogen-to-albumin ratio (FAR), prognostic nutritional index (PNI), and their combination for ovarian cancer (OC) to discover an optimal combined diagnostic index for early diagnosis of OC. A thorough investigation was conducted to ascertain the correlation between these markers and the pathological characteristics of OC, thereby providing a foundation for early identification and treatment of this disorder. One hundred seventy patients with documented OC and benign ovarian tumors (BOTs) treated at Hebei General Hospital between January 2019 and December 2022 were included in this retrospective study. Data analysis was conducted using IBM SPSS Statistics version V26.0, MedCalc Statistical Software version 19.4.0, and the R Environment for Statistical Computing software (R Foundation for Statistical Computing). Isolated CA125 showed the best application value for differentiating benign ovarian tumors from OC when the defined variables were compared separately. The combination of CA125, HE4, FAR, SII, and PNI displayed a greater area under the operating characteristic curve curve than any one of them or other combinations of the 5 variables. Compared to CA125 alone, the combination of CA125, HE4, FAR, SII, and PNI showed a slight gain in sensitivity (83.91%), negative predictive value (83.91%), accuracy (85.88%), and a decrease in negative likelihood ratio (0.180%). Higher preoperative CA125, HE4, SII, and FAR levels, and lower PNI levels predicted a higher probability of advanced OC progression and lymph node metastasis. FAR has better application value than other inflammation-related markers (PNI and SII). This study suggests that preoperative serum SII, PNI, and FAR may be clinically valuable markers in patients with OC. FAR has better application value than other inflammation-related markers (PNI and SII). As we delve deeper into the inflammatory mechanisms associated with tumors, we may discover more effective combinations of tumor and inflammatory biomarkers.

Are ROMA and HE4 More Accurate than CA-125, in Predicting of Ovarian Epithelial Carcinoma?

Background

Evaluation of ovarian tumors based on tumor markers could have high clinical importance. In this study, we aimed to assess the predictive value of HE4 and Risk of Ovarian Malignancy Algorithm (ROMA) compared to CA-125 in the Malignancy of ovarian epithelial masses.

Materials and Methods

This cross-sectional study was performed in 2020-2021 including 203 patients. Serum HE4 and CA-125 levels were checked before surgery. According to the pathology report (benign, borderline, or malignant epithelial mass), the predictive values of the three markers were evaluated.

Results

About 146 cases were benign; 14 cases were borderline and 43 cases were malignant. Most patients (69.8%) in the malignant group were in stage 3. Significantly higher levels of all three markers (CA-125, HE4, and ROMA) were found in patients with malignant tumors compared to benign or borderline tumors (P < 0.001 for all). The sensitivity of CA-125 was the highest (90.7%) in pre- and post-menopausal patients but the specificity of HE4 and ROMA were higher than CA-125 (98.1% and 97.5%, respectively, versus 86.9% for CA-125). In post-menopausal patients, both sensitivities of HE4 and ROMA were 90.5% and the specificity and sensitivity of CA-125 were the highest (95.2% and 100%). In premenopausal patients, the sensitivity of ROMA (90.9%) and the specificity of HE4 (100%) were the highest.

Conclusions

HE4 and ROMA are not necessary for postmenopausal patients in low-resource areas and a check of serum CA-125 will be enough. The higher-cost, ROMA, and HE4 checks are recommended in premenopausal people because they are more sensitive.

The Application of an Extracellular Vesicle-Based Biosensor in Early Diagnosis and Prediction of Chemoresponsiveness in Ovarian Cancer

BACKGROUND

Ovarian cancer (OVCA) is the most fatal gynecological cancer with late diagnosis and plasma gelsolin (pGSN)-mediated chemoresistance representing the main obstacles to treatment success. Since there is no reliable approach to diagnosing patients at an early stage as well as predicting chemoresponsiveness, there is an urgent need to develop a diagnostic platform for such purposes. Small extracellular vesicles (sEVs) are attractive biomarkers given their potential accuracy for targeting tumor sites.

METHODS

We have developed a novel biosensor which utilizes cysteine-functionalized gold nanoparticles that simultaneously bind to cisplatin (CDDP) and plasma/cell-derived EVs, affording us the advantage of predicting OVCA chemoresponsiveness, and early diagnosis using surface-enhanced Raman spectroscopy.

RESULTS

We found that pGSN regulates cortactin (CTTN) content resulting in the formation of nuclear- and cytoplasmic-dense granules facilitating the secretion of sEVs carrying CDDP; a strategy used by resistant cells to survive CDDP action. The clinical utility of the biosensor was tested and subsequently revealed that the sEV/CA125 ratio outperformed CA125 and sEV individually in predicting early stage, chemoresistance, residual disease, tumor recurrence, and patient survival.

CONCLUSION

These findings highlight pGSN as a potential therapeutic target and provide a potential diagnostic platform to detect OVCA earlier and predict chemoresistance; an intervention that will positively impact patient-survival outcomes.

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis

OBJECTIVE

Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identify biomarkers at an early stage. Biomarker discovery is challenging, yet essential for improving drug discovery and clinical care. Machine learning (ML) techniques are invaluable for recognising complex patterns in biomarkers compared to conventional methods, yet they can lack physical insights into diagnosis. eXplainable Artificial Intelligence (XAI) is capable of providing deeper insights into the decision-making of complex ML algorithms increasing their applicability. We aim to introduce best practice for combining ML and XAI techniques for biomarker validation tasks.

METHODS

We focused on classification tasks and a game theoretic approach based on Shapley values to build and evaluate models and visualise results. We described the workflow and apply the pipeline in a case study using the CDAS PLCO Ovarian Biomarkers dataset to demonstrate the potential for accuracy and utility.

RESULTS

The case study results demonstrate the efficacy of the ML pipeline, its consistency, and advantages compared to conventional statistical approaches.

CONCLUSION

The resulting guidelines provide a general framework for practical application of XAI in medical research that can inform clinicians and validate and explain cancer biomarkers.

Magnetic resonance imaging radiomics to differentiate ovarian sex cord-stromal tumors and primary epithelial ovarian cancers

Objective

To evaluate the diagnostic ability of magnetic resonance imaging (MRI) based radiomics and traditional characteristics to differentiate between Ovarian sex cord-stromal tumors (SCSTs) and epithelial ovarian cancers (EOCs).

Methods

We consecutively included a total of 148 patients with 173 tumors (81 SCSTs in 73 patients and 92 EOCs in 75 patients), who were randomly divided into development and testing cohorts at a ratio of 8:2. Radiomics features were extracted from each tumor, 5-fold cross-validation was conducted for the selection of stable features based on development cohort, and we built radiomics model based on these selected features. Univariate and multivariate analyses were used to identify the independent predictors in clinical features and conventional MR parameters for differentiating SCSTs and EOCs. And nomogram was used to visualized the ultimately predictive models. All models were constructed based on the logistic regression (LR) classifier. The performance of each model was evaluated by the receiver operating characteristic (ROC) curve. Calibration and decision curves analysis (DCA) were used to evaluate the performance of models.

Results

The final radiomics model was constructed by nine radiomics features, which exhibited superior predictive ability with AUCs of 0.915 (95%CI: 0.869-0.962) and 0.867 (95%CI: 0.732-1.000) in the development and testing cohorts, respectively. The mixed model which combining the radiomics signatures and traditional parameters achieved the best performance, with AUCs of 0.934 (95%CI: 0.892-0.976) and 0.875 (95%CI: 0.743-1.000) in the development and testing cohorts, respectively.

Conclusion

We believe that the radiomics approach could be a more objective and accurate way to distinguish between SCSTs and EOCs, and the mixed model developed in our study could provide a comprehensive, effective method for clinicians to develop an appropriate management strategy.

The clinical role of glycobiology on ovarian cancer progression

Diverse carbohydrate (glycan) structures are located on lipids and proteins that cover the surface of human cells known as the glycocalyx. Research over many decades have illustrated that the glycan structures located in the glycocalyx change dramatically with cancer contributing to the early development and progression of tumors. New therapeutic and diagnostic applications for cancers based on targeting glycan changes are now in development and in early stage clinical trials. There is an abundance of research for ovarian cancer indicating that certain glycoproteins and glycolipids play major roles in the progression, recurrence, and chemoresistance of this disease. This review is focused on discussion of these biomarkers and how translational medicine for ovarian cancer can be further defined focusing on targeting glycans, glycoproteins, and glycan-mediated interactions.

Predicting value of HE4 and CA125 markers for optimal cytoreductive surgery in ovarian cancer patients

We conducted a cross-sectional study to evaluate the role of serum levels of CA125 and HE4 in predicting optimal cytoreductive surgery. Eligible women who had been diagnosed with ovarian cancer based on both clinical and imaging criteria were enrolled in this study. Serum levels of CA 125 and HE4 were checked before surgery and all patients underwent complete surgical staging. After completion of the pathological evaluation, data were entered in SPSS version 23. One hundred and ten individuals were enrolled in our study. We divided cases between two groups: stage I to Ш b and stage Шc to IV. Serum level of HE4 >170 pmol/L can predict optimal cytoreductive surgery before operation. (sensitivity:80% and specificity 70%) and serum level of CA 125 > 320 UI/mL can predict optimal cytoreductive surgery before operation. (sensitivity:80% and specificity 70%). Our data demonstrated a negative predictive value of about 80% for both HE4 and CA125. Based on these cut-off, unnecessary surgery can be avoided in many cases, however, it is unwise to ignore clinical performance and radiological findings. Nevertheless, we can say the evaluation of tumor markers is feasible and helpful in predicting optimal surgery.

HE4 as a serum biomarker for the diagnosis of pelvic masses: a prospective, multicenter study in 965 patients

Background

To evaluate the diagnostic value of adding human epididymis protein 4 (HE4), cancer antigen 125 (CA125) and risk of malignancy algorithm (ROMA) to ultrasound for detecting ovarian cancer in patients with a pelvic mass.

Methods

This was a prospective, observational, multicenter study. Patients aged > 18 years who were scheduled to undergo surgery for a suspicious pelvic mass had CA125 and HE4 levels measured prior to surgery, in addition to a routine transvaginal ultrasound scan. The diagnostic performance of CA125, HE4 and ROMA for distinguishing between benign and malignant adnexal masses was assessed using receiver operating characteristic (ROC) analysis and the corresponding area under the curve (AUC).

Results

Of 965 evaluable patients, 804 were diagnosed with benign tumors and 161 were diagnosed with ovarian cancer. In late-stage ovarian cancer, CA125, HE4 and ROMA all had an excellent diagnostic performance (AUC > 0.92), whereas in stage I and II, diagnostic performance of all three biomarkers was less adequate (AUC < 0.77). In the differential diagnosis of ovarian cancer and endometriosis, ROMA and HE4 performed better than CA125 with 99 and 98.1% versus 75.0% sensitivity, respectively, at 75.4% specificity.

Conclusions

ROMA and HE4 could be valuable biomarkers to help with the diagnosis of ovarian cancer in premenopausal patients in order to differentiate from endometriosis, whereas CA125 may be more adequate for postmenopausal patients.

• Serum biomarkers can help to distinguish benign from malignant pelvic masses

• We evaluated the diagnostic value of adding HE4, CA125 and ROMA to ultrasound for detecting ovarian cancer

• In stage III and IV ovarian cancer all three biomarkers showed excellent performance

• ROMA and HE4 performed better than CA125 in the differential diagnosis of ovarian cancer and endometriosis

Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women

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.

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.

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.

Association between Rheumatoid Arthritis Disease Activity and Risk of Ovarian Malignancy in Middle-Aged and Elderly Women

Objective

To investigate the risk of ovarian malignancy in middle-aged and elderly women with rheumatoid arthritis (RA) and its correlation with disease activity.

Methods

219 middle-aged and elderly (age ≥ 40) female RA patients who were treated at the Department of Rheumatology and Immunology of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine from August 2019 to September 2020 were selected. Their general information such as age and medical history was collected. RA disease activity-related indicators include rheumatoid factor (RF), anticyclic citrullinated peptide antibody (ACPA), ESR, CRP, and ovarian malignancy risk-related indicators including alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA199, and human epididymis protein 4 (HE4) were detected. According to Risk of Ovarian Malignancy Algorithm (ROMA), they were divided into a low-risk group (ROMA-low, premenopausal: ROMA ≤ 11.4%, postmenopausal: ROMA ≤ 29.9%) and a high-risk group (ROMA-high, premenopausal: ROMA > 11.4%, postmenopausal: ROMA > 29.9%) for ovarian malignancy. Meanwhile, according to the DAS28-ESR, they were divided into the general disease activity group (DAS28-ESR ≤ 5.1) and the high disease activity group (DAS28-ESR > 5.1). SPSS 25.0 software was used to compare the differences among groups and to analyze the correlation between ovarian malignancy risk and RA disease activity.

Results

Compared with the ROMA-low group, the levels of RF, ACCP, CDAI, SDAI, DAS28-ESR, and DAS28-CRP in the ROMA-high group were significantly increased (P < 0.05). HE4 and ROMA in the high disease activity group were significantly higher than general disease activity group (P < 0.05). Spearman correlation analysis showed that age (r = 0.472), RF (r = 0.221), ACPA (r = 0.156), CDAI (r = 0.226), SDAI (r = 0.221), DAS28-ESR (r = 0.254), DAS28-CRP (r = 0.208), medications (r = 0.189), and CA199 (r = 0.250) were correlated with ROMA (P < 0.05). Multivariate regression analysis showed that ESR (OR = 1.11), SDAI (OR = 1.02), DAS28-ESR (OR = 1.33), DAS28-CRP (OR = 1.26), and CA199 (OR = 1.03) were independent risk factors for high risk of ovarian malignancy (P < 0.05). Subgroup analysis showed that CA199 is an effect modification factor for DAS28-ESR (P < 0.05).

Conclusion

The risk of ovarian malignancy is significantly increased in middle-aged and elderly women with high disease activity with rheumatoid arthritis. In clinical, full attention should be paid to the risk of ovarian malignancy in this population. Screening in time, especially in patients with increased DAS28-ESR and CA199 at the same time, is needed.

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.

New Analytical Approach for the Alignment of Different HE4 Automated Immunometric Systems: An Italian Multicentric Study

Human epididymal secretory protein 4 (HE4) elevation has been studied as a crucial biomarker for malignant gynecological cancer, such us ovarian cancer (OC). However, there are conflicting reports regarding the optimal HE4 cut-off. Thus, the goal of this study was to develop an analytical approach to harmonize HE4 values obtained with different laboratory resources. To this regard, six highly qualified Italian laboratories, using different analytical platforms (Abbott Alinity I, Fujirebio Lumipulse G1200 and G600, Roche Cobas 601 and Abbott Architett), have joined this project. In the first step of our study, a common reference calibration curve (designed through progressive HE4 dilutions) was tested by all members attending the workshop. This first evaluation underlined the presence of analytical bias in different devices. Next, following bias correction, we started to analyze biomarkers values collected in a common database (1509 patients). A two-sided p-value < 0.05 was considered statistically significant. In post-menopausal women stratified between those with malignant gynecological diseases vs. non-malignant gynecological diseases and healthy women, dichotomous HE4 showed a significantly better accuracy than dichotomous Ca125 (AUC 0.81 vs. 0.74, p = 0.001 for age ≤ 60; AUC 0.78 vs. 0.72, p = 0.024 for age > 60). Still, in post-menopausal status, similar results were confirmed in patients with malignant gynecological diseases vs. patients with benign gynecological diseases, both under and over 60 years (AUC 0.79 vs. 0.73, p = 0.006; AUC 0.76 vs. 0.71, p = 0.036, respectively). Interestingly, in pre-menopausal status women over 40 years, HE4 showed a higher accuracy than Ca125 (AUC 0.73 vs. 0.66, p = 0.027), thus opening new perspective for the clinical management of fertile patients with malignant neoplasms, such as ovarian cancer. In summary, this model hinted at a new approach for identifying the optimal cut-off to align data detected with different HE4 diagnostic tools.

ADAM17-A Potential Blood-Based Biomarker for Detection of Early-Stage Ovarian Cancer

Simple Summary

Ovarian cancer has the highest lethality among gynecological tumors. Therefore, it is essential to find reliable biomarkers to improve early detection. This is the first report describing ADAM17 detection in serum and ascites fluid of ovarian cancer patients. A high ADAM17 concentration in serum at primary diagnosis is associated with early FIGO stages and predicts complete resection of the tumor mass. In addition, ADAM17 and CA-125 complement each other, especially in the diagnosis of early stages. In summary, ADAM17 appears to be a promising screening marker for detecting early-stage ovarian cancer.

Abstract

Ovarian cancer has the highest mortality rate among gynecological tumors. This is based on late diagnosis and the lack of early symptoms. To improve early detection, it is essential to find reliable biomarkers. The metalloprotease ADAM17 could be a potential marker, as it is highly expressed in many solid tumors, including ovarian and breast cancer. The aim of this work is to evaluate the relevance of ADAM17 as a potential diagnostic blood-based biomarker in ovarian cancer. Ovarian cancer cell lines IGROV-1 and A2780, as well as primary patient-derived tumor cells obtained from tumor tissue and ascitic fluid, were cultured to analyze ADAM17 abundance in the culture supernatant. In a translational approach, a cohort of 117 well-characterized ovarian cancer patients was assembled and ADAM17 levels in serum and corresponding ascitic fluid were determined at primary diagnosis. ADAM17 was quantified by enzyme-linked immunosorbent assay (ELISA). In the present study, ADAM17 was detected in the culture supernatant of ovarian cancer cell lines and primary cells. In addition, ADAM17 was found in serum and ascites of ovarian cancer patients. ADAM17 level was significantly increased in ovarian cancer patients compared to an age-matched control group (p < 0.0001). Importantly early FIGO I/II stages, which would not have been detected by CA-125, were associated with higher ADAM17 concentrations (p = 0.007). This is the first study proposing ADAM17 as a serum tumor marker in the setting of a gynecological tumor disease. Usage of ADAM17 in combination with CA-125 and other markers could help detect early stages of ovarian cancer.

Modified HE4, CA125, and ROMA cut-off values and predicted probability of ovarian tumor in Chinese patients

BACKGROUND

Most prior studies investigating the risk of ovarian malignancy algorithm (ROMA) with cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) have involved Caucasian population or other populations. To date, there have been no unique calculations of predicted probability (PP) risk specifically for Chinese populations to help physicians in primary care settings.

METHODS

A group of 534 women with ovarian tumor diagnoses were enrolled and serum HE4 and CA125 were measured in each individual. Modified cut-off values were obtained by maximizing area under the curve (AUC) values and adjusted by using logistic regression with corresponding sensitivity (SN), specificity (SP), Youden index (YI), positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

By utilizing the ideal PPV, NPV, and AUC values, in premenopausal women modified HE4, CA125, ROMA, and PP cut-off values were 73.87 pmol/L, 61.60 U/mL, 18.47%, and 0.168, respectively. The same test values for postmenopausal women were 120.90 pmol/L, 76.21 U/mL, 26.48%, and 0.485, respectively. The SN for HE4 with the modified cut-off value was significantly lower than that for CA125 (P=0.040) in premenopausal women and lower than that for ROMA (P=0.001) and PP (P=0.044) in postmenopausal women. The AUC values for CA125, ROMA, and PP were all significantly higher than that for HE4 (P=0.006, 0.007, and 0.002, respectively) in postmenopausal women.

CONCLUSIONS

The modified cut-off values for HE4, CA125, ROMA, and PP with ideal SN, SP, YI, NPV, PPV were useful of ruling out ovarian malignancy among both pre- and post-menopausal women. In premenopausal women modified HE4, CA125, ROMA, and PP cut-off values were 73.87 pmol/L, 61.60 U/mL, 18.47%, and 0.168, respectively and in postmenopausal women were 120.90 pmol/L, 76.21 U/mL, 26.48%, and 0.485, respectively.

Carbohydrate antigen 125, carbohydrate antigen 15-3 and low-density lipoprotein as risk factors for intraocular metastases in postmenopausal breast cancer

The prognosis of patients with postmenopausal breast cancer (PBC) could be improved by the early detection of intraocular metastases (IOMs). However, serum biomarkers for IOMs in PBC remain elusive. In the current study, we investigated patients with PBC, and compared serum parameters in an IOM and a non-IOM group, and then differentiated the risk factors related to IOMs. A comparison between an IOM and a non-IOM (NIOM) group was performed using Student t-test and a Chi-Squared test. After constructing a Poisson regression model to identify risk factors, we plotted receiver operating characteristic curves to evaluate the predictive value of significant risk factors in detecting IOMs. The incidence of IOMs in PBC was 1.16%. The histopathology results were not significantly different between the 2 groups. The levels of serum carbohydrate antigen 125 (CA-125), carbohydrate antigen 15-3 (CA15-3) and alkaline phosphatase were significantly elevated in IOMs compared with NIOMs (P = .082, P < .001, and P < .001, respectively). Compared with NIOMs, age, carbohydrate antigen 19 to 9, hemoglobin, calcium, total cholesterol, low-density lipoprotein (LDL) and apolipoprotein A1 were remarkably lower in IOMs (P = .038, P < .001, P < .001, P = .032, P = .041, P < .001, and P = .001, respectively). Poisson regression suggested that CA-125, CA15-3 and LDL were contributing to IOMs in PBC as risk factors (OR = 1.003, 95% CI: 1.001-1.005; OR = 1.025, 95% CI: 1.019-1.033; OR = 0.238, 95% CI: 0.112-0.505, respectively). A receiver operating characteristic curve revealed that the cut-off values for CA-125, CA15-3 and LDL were 16.78 0 U/mL, 63.175 U/mL, and 2.415 mmol/L, respectively. The combination of CA-125 and CA15-3 showed significant diagnostic value (area under the curve [AUC] = 0.982, P < .001). Our investigation suggests that CA-125, CA15-3 and LDL remarkably predict IOMs in PBC as risk factors, and the combination of CA-125 and CA15-3 shows considerable diagnostic value.

Predictive Value of Serum Cytokeratin 19 Level for the Feasibility of Conserving Ovaries in Endometrial Cancer

Objective: To determine the predictive value of cytokeratin 19 (CK19) for evaluating the safety of ovarian preservation in patients with endometrial cancer (EC).

Methods: Five hundred and seventeen EC patients hospitalized from November 2010 to June 2016 were reviewed retrospectively. Pre-operative tumor biomarkers including CA125, HE4, CK19, and CA19-9 were obtained. Predictive biomarkers associated with ovarian metastasis were selected using univariate and multivariate Logistic regression. The cut-off values were determined by receiver operating characteristic (ROC) curves. Kaplan-Meier method and Cox multivariate regression model was used to perform survival analysis.

Results: Among clinical parameters and biomarkers included, age > 65, type II EC, CA125 ≥ 35 u/ml, CK19 > 3.3 ng/ml, and myometrial invasion ≥ 50% depth appeared as significant predictors of the risk of ovarian involvement in univariable logistic analysis. In multivariable analysis, CK19 > 3.3 ng/ml (OR = 11.541, 95%CI: 1.968–67.668, P = 0.007) and Type II EC (OR = 8.336, 95%CI: 1.456–47.722, P = 0.017) were independent risk predictors of ovarian metastasis in pre-menopausal women. In pre-menopausal women with Type I EC (n = 142), CK19 level could satisfactorily predict the risk of ovarian metastasis (AUC = 0.860, 95%CI: 0.792–0.912, P < 0.001), and when the cut-off point was set as 2.45 ng/ml, the negative predictive value and negative likelihood ratio were 99% and 0.19, with the maximum Youden index of 0.598.

Conclusions: The present study advocates the necessity of incorporating serum CK19 measurement into the pre-operative evaluation of EC, especially as extension of current standard approach with ovarian preservation counseling.

Future Screening Prospects for Ovarian Cancer

Simple Summary

Ovarian cancer (OC) has the highest mortality rate of all gynecological cancers. It is usually diagnosed in late stages (FIGO III-IV), and therefore, overall survival is very poor. If diagnosed at the early stages, ovarian cancer has a 90% five-year survival rate. Liquid biopsy has a good potential to improve early ovarian cancer detection and is discussed in this review.

Abstract

Current diagnostic tools used in clinical practice such as transvaginal ultrasound, CA 125, and HE4 are not sensitive and specific enough to diagnose OC in the early stages. A lack of early symptoms and an effective asymptomatic population screening strategy leads to a poor prognosis in OC. New diagnostic and screening methods are urgently needed for early OC diagnosis. Liquid biopsies have been considered as a new noninvasive and promising method, using plasma/serum, uterine lavage, and urine samples for early cancer detection. We analyzed recent studies on molecular biomarkers with specific emphasis on liquid biopsy methods and diagnostic efficacy for OC through the detection of circulating tumor cells, circulating cell-free DNA, small noncoding RNAs, and tumor-educated platelets.

A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index

Simple Summary

Ovarian Endometrioma (OE) is a precancerous condition for endometriosis-associated ovarian cancer (EAOC). For many clinicians observing OE outpatients, setting the appropriate time for surgery can be a challenge because there is no suggestive milestone. Out of the fear of malignant transformation, many patients have surgery conducted according to respective faculty standards. This study aims to investigate a novel, noninvasive method not requiring an MRI device. This study partly helps to lift the above restrictions, and has the potential to suggest intervention-appropriate timing to the physician.

Abstract

Background: Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate between ovarian endometrioma (OE) and endometriosis-associated ovarian cancer (EAOC), with a sensitivity and specificity of 86% and 94%, respectively. MRI models that can measure R2 values are limited, and the R2 values differ between MRI models. This study aims to extract the factors contributing to the R2 value, and to make a formula for estimating the R2 values, and to assess whether the R2 predictive index calculated by the formula could discriminate EAOC from OE. Methods: This retrospective study was conducted at our institution from November 2012 to February 2019. A total of 247 patients were included in this study. Patients with benign ovarian tumors mainly received laparoscopic surgery, and the patients suspected of having malignant tumors underwent laparotomy. Information from a chart review of the patients’ medical records was collected. Results: In the investigative cohort, among potential factors correlated with the R2 value, multiple regression analyses revealed that tumor diameter and CEA could predict the R2 value. In the validation cohort, multivariate analysis confirmed that age, CRP, and the R2 predictive index were the independent factors. Conclusions: The R2 predictive index is useful and valuable to the detection of the malignant transformation of endometrioma.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumors

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.

The chronological change in transvaginal ultrasound images of a hemorrhagic ovarian cyst observed during infertility treatment: A case report and literature review

Insights gained from chronological ultrasonogram images in the current case report will provide useful information for diagnosing and conservatively treating HOC. This could help avoid unnecessary laparotomy.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumours

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.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors

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.

Screening and Identification of a Specific Binding Peptide to Ovarian Cancer Cells from a Phage-Displayed Peptide Library

To select specific binding peptides for imaging and detection of human ovarian cancer. The phage 12-mer peptide library was used to select specific phage clones to ovarian cancer cells. After four rounds of biopanning, the binding specificity of randomly selected phage clones to ovarian cancer cells was determined by enzyme-linked immunosorbent assay (ELISA). DNA sequencing and homology analysis were performed on specifically bound phages. The binding ability of the selected peptides to SKOV3 cells was confirmed by fluorescence microscopy and flow cytometry. After four rounds of optimized biological panning, phage recovery was 34-fold higher than that of the first round, and the specific phage clones bound to SKOV3 cells were significantly enriched. A total of 32 positive phage clones were preliminarily identified by ELISA from 54 randomly selected clones, and the positive rate was 59.3%. S36 was identified as the clone with best affinity to SKOV3 cells via fluorescence microscopy and flow cytometry. A representative clone of OSP2, S36 is expected to be an effective probe for diagnosis and treatment of ovarian cancer.

Diagnostic Performance of F-18 FDG PET/CT Compared with CA125, HE4, and ROMA for Epithelial Ovarian Cancer

OBJECTIVE

This study aimed to examine the diagnostic performance of F-18 fluorodeoxyglucose positron emission tomography with computed tomography (F-18 FDG PET/CT) compared with cancer antigen 125 (CA125), human epididymis protein 4 (HE4), and risk of ovarian malignancy algorithm (ROMA) score to distinguish epithelial ovarian cancer from benign tumors.

METHODS

A total of 46 patients with pelvic masses, who underwent F-18 FDG PET/CT, CA125, and HE4 before surgery between January 2015 and December 2018, were included in this retrospective study. The diagnostic performance of CA125, HE4, ROMA score, and maximum standardized uptake value (SUVmax) to differentiate epithelial ovarian cancer from benign pelvic tumors was examined by receiver operating characteristic curve analysis.

RESULTS

Among the 46 patients, 28 were cases of ovarian cancers and 18 were of benign. The mean values of CA125, HE4, ROMA score, and SUVmax were significantly higher in the ovarian cancer group than the benign group. In early cancer stages (stages I and II), Area under the curve for SUVmax was significantly higher than CA125 and ROMA score (0.778 for CA125, 0.753 for HE4, 0.682 for ROMA score, and 0.922 for SUVmax).

CONCLUSION

SUVmax using F-18 FDG PET/CT showed a high diagnostic accuracy for differentiating epithelial ovarian cancer from benign pelvic tumors, including early stage ovarian cancer. F-18 FDG PET/CT can be a useful modality for the assessment of pelvic mass.<br />.

Relaxin as a potential diagnostic biomarker for ovarian cancer- A prospective study

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.

Liquid biopsy in ovarian cancer: Catching the silent killer before it strikes

Epithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy in the western world. The majority of women presenting with the disease are asymptomatic and it has been dubbed the "silent killer". To date there is no effective minimally invasive method of stratifying those with the disease or screening for the disease in the general population. Recent molecular and pathological discoveries, along with the advancement of scientific technology, means there is a real possibility of having disease-specific liquid biopsies available within the clinical environment in the near future. In this review we discuss these discoveries, particularly in relation to the most common and aggressive form of EOC, and their role in making this possibility a reality.

Novel gene signatures for prognosis prediction in ovarian cancer

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.

Prognostic value of serum HE4 in patients with advanced ovarian, fallopian tube, and peritoneal carcinoma

PURPOSE

In this study, the prognostic value of serum HE4 was investigated in patients with advanced ovarian, fallopian tube, and peritoneal carcinoma.

METHODS

Serum HE4 and CA125 levels were measured in both patients and controls, and the response of treatment and the detection of recurrence were evaluated by serum HE4 and CA125 levels in the patients.

RESULTS

The results showed that the levels of serum HE4 and CA125 were significantly higher in advanced patients than those seen in benign disease controls (p < 0.001). Compared with CA125, HE4 had higher specificity, but lower sensitivity. Furthermore, serum HE4 was closely associated with the response of treatment and recurrence, the effective response rate for therapy treatment showed by HE4 was higher than CA125, and a serum HE4 level was correlated with a sensitivity of 82.8% and a specificity of 99%, a positive predictive value (PPV) of 97.7%, and a negative predictive value (NPV) of 77.9% to show the presence of recurrence; the accuracy of HE4 for recurrence prediction after treatment was 88.6%.

CONCLUSIONS

Our study indicated that serum HE4 levels are effective for diagnosis, evaluating the response of treatment and predicting recurrence in patients with advanced ovarian, fallopian tube, and peritoneal carcinoma.

Is HE4 Superior over CA-125 in the Follow-up of Patients with Epithelial Ovarian Cancer?

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.

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.

Comparison of CA 125 alone and risk of ovarian malignancy algorithm (ROMA) in patients with adnexal mass: A multicenter study

BACKGROUND

This multicenter study aimed to evaluate the performance of CA 125 and risk of ovarian malignancy algorithm (ROMA) in differentiating epithelial ovarian cancer (EOC) from benign adnexal mass. We consecutively enrolled 782 patients referred to tertiary hospitals with adnexal mass requiring surgical treatment. A total 322 of patients with benign adnexal disease and 327 patients with EOC were included in the analysis. Using reference cut-off values in premenopausal women, ROMA had better specificity (0.926 vs. 0.787, P < 0.001) and accuracy (0.875 vs. 0.777, P < 0.001) than CA 125 alone and comparable sensitivity (0.707 vs. 0.747, P = 0.549). Using optimum cut-off values in premenopausal women, CA 125 and ROMA had comparable specificity (0.922 vs. 0.947, P < 0.001) and accuracy (0.871 vs. 0.868, P = 0.879); however, sensitivity for CA 125 was inferior to that of ROMA (0.707 vs. 0.613, P = 0.039). In postmenopausal women, sensitivity, specificity, and accuracy were comparable between CA 125 alone and ROMA using either reference cut-off values or optimum cut-off values.ROMA showed better diagnostic performance in differentiating EOC from benign adnexal tumors among premenopausal women. However, in postmenopausal women, ROMA did not show any benefit over CA 125 alone.

Efficacy of HE4, CA125, Risk of Malignancy Index and Risk of Ovarian Malignancy Index to Detect Ovarian Cancer in Women with Presumed Benign Ovarian Tumours: A Prospective, Multicentre Trial

BACKGROUND

Presumed benign ovarian tumours (PBOT) are defined by the International Ovarian Tumour Analysis (IOTA) group, without suspected sonographic criteria of cancer, without ascites or metastasis. The aim is to evaluate the efficacy of human epididymis protein 4 (HE4), cancer antigen 125 (CA125), the risk of malignancy index (RMI) and the risk of ovarian malignancy index (ROMA) to predict ovarian cancer in women with PBOT.

METHODS

It is a prospective, observational, multicentre, laboratory-based study including women with PBOT in four hospitals from 11 May 2015 through 12 May 2016. Preoperative CA125 and HE4 plasma levels were measured for all women. The primary endpoint was the specificity of CA125 and HE4 for diagnosing ovarian cancer. The main secondary endpoints were specificity and likelihood ratio of RMI, ROMA and tumours markers.

RESULTS

Two hundred and fifty patients were initially enrolled and 221 patients were finally analysed, including 209 benign ovarian tumours (94.6%) and 12 malignant ovarian tumours (5.4%). The malignant group had significantly higher mean values of HE4, CA125, RMI and ROMA compared to the benign group (p < 0.001). Specificity was significantly higher using a combination of HE4 and CA125 (99.5%) compared to either HE4 or CA125 alone (90.4% and 91.4%, respectively, p < 0.001). Moreover, the positive likelihood ratio for combination HE4 and CA125 was significantly higher (104.5; 95% CI 13.6-800.0) compared to HE4 alone (5.81; 95% CI 2.83-11.90) or CA125 alone (6.97; 95% CI 3.91-12.41).

CONCLUSIONS

The combination of HE4 and CA125 represents the best tool to predict the risk of ovarian cancer in patients with a PBOT.

The difference in prognosis of stage II and III colorectal cancer based on preoperative serum tumor markers

Background: Preoperative serum tumor markers have been widely used to predict prognosis in stage II and III colorectal cancer (CRC). However, few previous studies addressed the effect of increased preoperative numbers of tumor markers.

Methods: Patients with stage II and III CRC who underwent curative resection were included from January 2009 to October 2015. The relationship between serum tumor markers and clinicopathological parameters was analyzed. DFS and OS were compared in stage II and III CRC.

Results: The median follow-up was 45 months. In this study, 735 enrolled patients were assessed based on the numbers of increased tumor markers. We found that these increased tumor markers were closely associated with clinical stage, T stage, N stage, tumor location, pathology type, differentiation, lymphatic invasion and vascular invasion (all p values < 0.05). Furthermore, the number of increased tumor markers directly affected the survival of patients with CRC after curative surgery. The 3-year DFS and OS of patients with a score of 0 were 84.0% and 91.0%, respectively, which are much higher than those of patients with a score of 4 (42.9% and 37.8%, respectively) (p < 0.05). The 5-year DFS and OS of patients with a score of 0 were 75.9% and 77.9%, respectively, which are much higher than those of patients with a score of 4 (31.7% and 23.6%, respectively). Interestingly, our results suggested that stage III CRC patients with a score of 0 had longer DFS and OS times than stage II patients with scores of 3 and 4. Further analysis revealed statistically significant differences in OS (p < 0.05) but not in DFS.

Conclusions: The number of increased tumor markers could significantly predict prognosis in stage II and III CRC. In addition, these increased tumor markers had direct impacts on metastasis as well as the recurrence status and survival time of stage II and III CRC patients.

Ovarian carcinomas express HE4 epitopes independently of each other

BACKGROUND

The gene encoding HE4 undergoes alternative splicing to yield multiple protein isoforms. We investigated anti-HE4 mAbs which recognize epitopes on the C (2H5 and 3D8) or N (12A2 and 14E2) terminals.

METHODS

A Luminex assay was applied to determine mAb affinity. Binding of mAbs to sections from formaline fixed ovarian carcinomas was determined by immunohistology, binding to cultured ovarian carcinoma cells was tested by flow cytometry and immunocytochemistry, and HE4 secretion to patient serum or supernatants of cultured ovarian carcinoma was assayed by ELISA.

RESULTS

mAb 12A2 bound to formalin-fixed sections from 18 of 19 ovarian carcinomas, while 14E2, 2H5 and 3D8 bound to sections from 14, 7 and 4 patients, respectively. The mAbs bound independently of each other, i.e. a sample bound one mAb most strongly while another sample with similar affinity strongest bound another mAb. The intensity of binding to sections did not significantly correlate with the serum level of HE4 except for mAb 14E2, but there was a significant correlation between HE4 expression and its detection in supernatants of cultured ovarian carcinomas.

CONCLUSIONS

HE4 epitopes are expressed independently of each other and their expression of HE4 by cultured ovarian carcinoma cells correlates with the release of HE4 into culture supernatants. he epitope recognized by mAb 14E2 was significantly more expressed by platinum resistant tumors.

IMPACT

Expression of HE4 by most ovarian carcinomas makes it an excellent biomarker.. Further studies are needed to investigate the clinical relevance of overexpression of a particular epitope.

Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Clinical Practice at a Single Hospital in Korea

Background

The risk of ovarian malignancy algorithm (ROMA) is used for assessing ovarian cancer risk in women with a pelvic mass. Its diagnostic accuracy is variable. We investigated whether the clinically acceptable minimal sensitivity of >80.0% could be obtained with the suggested cutoff of 7.4%/25.3% for pre/postmenopausal women and with adjusted cutoffs set to a specificity of ≥75.0% or a sensitivity of 95.0%, in a hospital with a lower ovarian cancer (OC) prevalence than previously reported.

Methods

ROMA scores were calculated from measurements of human epididymis protein 4 and cancer antigen 125 in blood specimens from 443 patients with a pelvic mass. The ROMA-based risk group was compared against biopsy (N=309) or clinical follow-up with imaging (N=134) results. The ROMA sensitivity and specificity for predicting epithelial OC (EOC) and borderline ovarian tumor (BOT) were calculated for the suggested and adjusted cutoff values.

Results

When targeting BOT and EOC, the prevalence was 7.4% and sensitivity and specificity at the suggested cutoff were 63.6% and 90.7%, respectively. Sensitivity was 81.8% at the 4.65%/13.71% cutoff set to a specificity of 75.0%. When targeting only EOC, the prevalence was 4.1% and sensitivity and specificity at the suggested cutoff were 77.8% and 89.4%, respectively. Sensitivity was 88.9% at the 4.78%/14.35% cutoff set to a specificity of 75.0%.

Conclusions

The sensitivity of ROMA was lower than expected when using the suggested cutoff. When using the adjusted cutoff, its sensitivity reached 80.0%.

Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review

Ovarian cancer is the 5th leading cause of death for women with cancer worldwide. In more than 70% of cases, it is only diagnosed at an advanced stage. Our study aims to give an update on the biological markers for diagnosing ovarian cancer, specifically HE4, CA 125, RMI and ROMA algorithms.

Serum CA125 assay has low sensitivity in the early stages and can be increased in certain conditions such as menstruation or endometriosis. The level of HE4 is overexpressed in ovarian tumors. Its specificity is 94% and its level is not affected by endometriosis cysts. The combined measures of CA125 and HE4 have proved to be highly efficient with an area under the curve (AUC) of up to 0.96. Furthermore, this combined measure of CA125 can correct the variations in HE4 which are due to smoking or contraception combining estrogen plus progestin. While the specificity of RMI sometimes reaches 92%, the rather low AUC of 0.86 does not make it the best diagnostic tool. The specificity of ROMA is lower than HE4 (84% compared to 94%).

To date, the most efficient biological diagnostic tool to diagnose ovarian cancer is the combination of CA125 and HE4.

Expression of miR-26b in ovarian carcinoma tissues and its correlation with clinicopathology

The expression of microRNA (miR)-26b in ovarian carcinoma tissues, its correlation with clinicopathology, and its effect on diagnostic value and prognosis of ovarian cancer was investigated. A total of 74 patients with ovarian cancer (the study group) and 30 patients with benign ovarian tumors (the control group) in the Affiliated Hospital of Inner Mongolia Medical University from July 2011 to June 2013 were retrospectively analyzed. The expression of miR-26b in ovarian carcinoma tissues was detected by fluorescence reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and the correlation between the expression of miR-26b and the pathological features of ovarian carcinoma tissues and prognosis of patients was analyzed. The expression level of miR-26b in the study group (0.28±0.07) was significantly lower than that in the control group (0.54±0.11; P<0.050). There was no significant correlation between miR-26b expression and age, tumor type, exercise habit, smoking habit of patients with ovarian cancer (P>0.050), but there was close correlation between the miR-26b expression and lymph node metastasis, differentiation degree and pathological stage of patients with ovarian cancer (P<0.001). ROC curve showed that the area under curve (AUC) was 0.839, and when the maximum cut-off value was 0.815, the sensitivity and specificity of miR-26b in diagnosing the ovary was 84.932% and 77.936%, respectively. The 5-year overall survival rate in the low-expression group (61.54%) was significantly lower than that in the high-expression group (84.85; P=0.028). miR-26b is under-expressed in the ovary and has a close relationship with pathological stage, differentiation degree, and lymph node metastasis of ovarian cancer, which indicates that miR-26b is involved in the occurrence and development of ovarian cancer and is expected to be an effective indicator for treatment and diagnosis of ovarian cancer and the prognosis of patients.

Ovarian cancer: screening and future directions

Ovarian cancer carries a lifetime risk of approximately 2% for women and is the leading cause of death from any gynecologic malignancy. Currently, no screening program for ovarian cancer exists for the general population in the UK. This review focuses on the evidence surrounding the efficacy of current markers and discusses future improvements in screening for this disease. One-off cancer antigen 125 (CA125) measurements for detecting ovarian cancer have been well researched. However, studies have highlighted low positive predictive values (5%) and high false positive rates leading to patient anxiety and unnecessary invasive follow-up. Commonly, in the UK, CA125 is combined with transvaginal ultrasound, but there is little evidence that this approach can decrease mortality from ovarian cancer. Recently the Risk of Ovarian Cancer Algorithm, involving a combination of serial CA125 measurements and age, has been shown to detect more early stage cancers. Nevertheless, these measures are not robust in decreasing mortality from ovarian cancer and are costly to implement. Newer markers, such as human epididymis protein 4, have shown greater specificity. Its combination with CA125 and menopausal status in the Risk of Ovarian Malignancy Algorithm can predict the risk of malignancy but provides no additional benefit as a screening tool. Advanced techniques are emerging, including ultrasound molecular imaging techniques using microbubbles targeted to kinase domain receptors, and fallopian tube cytology. To reduce mortality from ovarian cancer, detection of pre-invasive lesions is imperative as ovarian cancer may develop in the fallopian tube and spread to the peritoneal cavity before being detected systemically. It seems that screening tools for ovarian cancer are currently not worthwhile for implementation into a national program. An emphasis on reducing false positives rates, associated anxiety and subsequent overdiagnosis is needed.

Systemic immune-inflammation index predicts prognosis in patients with epithelial ovarian cancer: A retrospective study

OBJECTIVE

The study aimed to investigate the prognostic value of the systemic immune-inflammation index (SII) in patients with epithelial ovarian cancer (EOC).

METHODS

A total of 553 EOC patients were retrospectively analyzed. 250 patients from West China Second University Hospital were assigned into the discovery cohort and 283 patients from The Affiliated Hospital of Southwest Medical University were assigned into the validation cohort. The correlation between SII and survival were analyzed using Cox regression analyses and Kaplan-Meier method. Prediction accuracy was evaluated with the receiver operating characteristics (ROC) curve.

RESULTS

The high SII (≥612) was correlated with advanced FIGO stage, lymph node metastasis, and tumor recurrence. In univariate Cox regression, patients with high SII (≥612) had a significantly shorter progression-free survival (PFS) and overall survival (OS) compared to low SII patients (<612) in both cohorts. In multivariate Cox regression analysis, SII was an independent prognostic indicator for PFS (HR = 7.61, 95% CI 3.34-17.35, P < 0.001) and OS (HR = 6.36, 95% CI 2.64-15.33, P < 0.001) in the discovery cohort. These results were verified in the validation cohort.

CONCLUSION

High SII was correlated with poor survival in patients with EOC. The SII was an independent prognostic factor for patients with EOC.

Deep Belief Network for the Enhancement of Ultrasound Images with Pelvic Lesions

It is well known that ultrasound images are cost-efficient and exhibit hassle-free usage. However, very few works have focused on exploiting the ultrasound modality for lesion diagnosis. Moreover, there is no reliable contribution reported in the literature for diagnosing pelvic lesions from the pelvic portion of humans, especially females. While few contributions are found for diagnosis of lesions in the pelvic region, no effort has been made on enhancing the images. Inspired from the neural network (NN), our methodology adopts deep belief NN for enhancing the ultrasound image with pelvic lesions. The higher-order statistical characteristics of image textures, such as entropy and autocorrelation, are considered to enhance the image from its noisy environment. The alignment problem is considered using skewness. The proposed method is compared with the existing NN method to demonstrate its enhancement performance.

Normalization of abnormal plasma amino acid profile-based indexes in patients with gynecological malignant tumors after curative treatment

BACKGROUND

We developed a novel plasma amino acid profile-based index (API) to detect ovarian, uterine, cervical, and endometrial cancers. In this study, we aimed to evaluate whether abnormal API values could be normalized after curative treatment in patients with gynecological malignant tumors.

METHODS

Patients with gynecological cancer with abnormal API values were included in this study. Pre-operative absolute API values were compared with those after curative treatment. The normalization rates of API values in patients negative for the expression of three well-known tumor markers (SCC, CA125, and CA19-9) were also evaluated. In addition, related amino acid profiles in healthy controls and patients under pre- and post-treatment conditions were analyzed.

RESULTS

Among 94 patients with abnormal pre-operative API values, the median API value was decreased from 9.52 to 2.17 after treatment (normalization rate: 88.3%). The decreased ranges were similar in patients with adenocarcinoma (6.28; 95% confidence interval [CI]: 5.43-6.95) and squamous carcinoma (7.44; 95% CI: 3.04-8.46). In 93.5% (43/46) of patients negative for tumor markers prior to operation, API values were normalized after the successful treatment. In addition, some pre-operative abnormal amino acid profiles, including Ile, Trp, and His, were reversibly normalized after treatment.

CONCLUSION

The API is a promising tumor marker in gynecological malignancies for the diagnosis of remission, particularly in patients negative for general tumor markers. Further studies are needed to explore the mechanisms related to the normalization of abnormal amino acid profiles.

Assessment of Diagnostic Values among CA-125, RMI, HE4, and ROMA for Cancer Prediction in Women with Nonfunctional Ovarian Cysts

Objectives

To evaluate the diagnostic performance among CA-125, RMI, HE4, and ROMA for cancer detection in women with nonfunctional ovarian cysts at King Chulalongkorn Memorial Hospital (KCMH). Secondary objective is to reconsider the proper cutoff value of HE4.

Methods

This is a prospective analytic study in women with nonfunctional ovarian cysts larger than 3 cm who scheduled for surgery at KCMH during 3^rd June 2015 to 31^st May 2016. Ultrasonogram and blood sample collection were completed before the operation. Patients' demographic information and pathologic results were obtained. SPSS software version 17 was used for statistical evaluation.

Results

A total of 281 participants were evaluated. 19.9% of them were malignant. Compared with CA-125, HE4 had lower sensitivity (53.4% vs. 87.9%) and NPV (89% vs. 93.6%) but higher specificity (97.8% vs. 46.2%) and PPV (86.1% vs. 29.8%). ROMA had slightly lower sensitivity (79.3% vs. 87.9%) and similar NPV (93.7% vs. 93.6%), but higher specificity (79.8% vs. 46.2%) and PPV (50.5% vs. 29.8%) compared with CA-125. The model that achieves the highest area under the ROC curve in differentiating benign versus malignant ovarian tumor was ROMA. Cutoff value of HE4 at 70 pMol/L (from 150 pMol/L) would give sensitivity 74.1% and specificity 86.5% that are comparable with ROMA.

Conclusions

HE4 and ROMA had better performance (higher specificity, PPV) compared to CA-125 and RMI. HE4 at 70 pMol/L could be the new cutoff value for Thai women with ovarian cysts, giving higher sensitivity and specificity.