Differential diagnosis of a pelvic mass: improved algorithms and novel biomarkers

Lipid metabolites abnormally expressed in pelvic fluid as potential biomarkers for ovarian cancer: A case-control study

BACKGROUND

Ovarian cancer is insidious and usually detected in advanced stages of the disease. As the ovaries are pelvic organs, changes in their pelvic fluid metabolites may be associated with ovarian cancer.

METHODS

Metabolomic changes in the pelvic fluid were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with ovarian cancer, ovarian cysts and uterine fibroids. Area under the curve (AUC) analysis was used to assess the diagnostic performance of lipid metabolites and blood tumor indices. The Pearson correlation algorithm was used to analyze the correlation between clinical characteristics and lipid metabolites in ovarian cancer patients.

RESULTS

There were 24 lipid metabolites significantly changed in the pelvic fluid of ovarian cancer patients (p < 0.05). Palmitoylcarnitine, lipoamide, lipid metabolites, and blood tumor indices (CA15-3 and CA125) showed AUC > 0.8, with palmitoylcarnitine reaching a high of 0.942. In addition, we found that some lipid metabolites were significantly associated with the clinical stage, abdominal water volume, lymphatic metastasis, and recurrence (p < 0.05, r > 0.5).

CONCLUSION

Levels of specific lipid metabolites are potential biomarkers of ovarian cancer and may play a key role in the early diagnosis and prognostic assessment of ovarian cancer.

SIGNIFICANCE

Our results showed that pelvic metabolites, especially some lipid metabolites, play an important role in the diagnosis of ovarian cancer. Meanwhile, partial lipid metabolites were closely associated with the clinical presentation and prognosis of patients with ovarian cancer. We believe that our study makes a significant contribution to the literature because it provides a potential approach that is more effective for ovarian cancer detection.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4

Ovarian cancer (OC) is the most lethal gynaecologic malignancy, attributed to its insidious growth, non-specific symptoms and late presentation. Unfortunately, current screening modalities are inadequate at detecting OC and many lack the appropriate specificity and sensitivity that is desired from a screening test. Nearly 70% of cases are diagnosed at stage III or IV with poor 5-year overall survival. Therefore, the development of a sensitive and specific biomarker for early diagnosis and screening for OC is of utmost importance. Currently, diagnosis is guided by CA125, the patient's menopausal status and imaging features on ultrasound scan. However, emerging evidence suggests that a combination of CA125 and HE4 (another serum biomarker) and patient characteristics in a multivariate index assay may provide a higher specificity and sensitivity than either CA125 and HE4 alone in the early detection of OC. Other attempts at combining various serum biomarkers into one multivariate index assay such as OVA1, ROMA and Overa have all shown promise. However, significant barriers exist before these biomarkers can be implemented in clinical practice. This article aims to provide an up-to-date review of potential biomarkers for screening and early diagnosis of OC which may have the potential to transform its diagnostic landscape.

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.

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%.

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass

OBJECTIVE

To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood.

METHODS

This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared.

RESULTS

A total of 183 evaluable patients were enrolled (average age 56 years, range 19-91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0-98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2-65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9-93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3-97.8%) for stage I-II and 98.9% (95% CI 96.7-100%) for stage III-IV patients with epithelial ovarian cancer.

CONCLUSION

Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT02781272.

FUNDING SOURCE

This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).

Effect of Serum Level of Human Epididymis Protein 4 and Interleukin-6 as Biomarkers in Patients with Adnexal Mass

Ovarian carcinoma is one of the most common types of neoplasms in women and the fifth leading cause of cancer death among women worldwide. Adnexal masses are classified as simple or complicated and can be benign or malignant. No single biomarker has demonstrated high sensitivity and specificity for detecting early ovarian cancer. Therefore, the current study was designed to investigate the influence of using two biomarkers as a tool for diagnosis in patients with an adnexal mass. This prospective case-control study was carried out on female patients diagnosed by ultrasound and magnetic resonance imaging with adnexal masses and scheduled for surgery and healthy women as a control group (n=50 each). The patients were in the age range of 16-80 years old and had attended the surgical rooms of Basrah hospitals, Basrah, Iraq, from January to July 2021. The levels of serum biomarkers were quantitatively assessed using the enzyme-linked immunosorbent assay. The serum concentration of the human epididymis protein 4 (HE4) biomarker exhibited significant differences between females with adnexal mass and healthy women. There was no significant association between neither the patient's age nor the menopausal state and the serum level of HE4. The serum level of HE4 had a sensitivity of 92% and a specificity of 66% as a serum marker for the presence of adnexal mass with a positive predictive value of 73% and a negative predictive value of 89%. In this study, serum interleukin-6 (IL-6) had a sensitivity of 30% and specificity of 64% in determining patients with adnexal mass pathology. It was found that the level of IL-6 was similar in all patients, compared to that in the control group. The median levels of serum HE4 showed high value in patients in the age groups of 21-40, 41-50, and >50 than in the control group; however, it was not statistically different (P=0.413). Human epididymis protein 4 was the top biomarker representing a higher concentration in adnexal mass; moreover, it demonstrated the highest performance in all samples with Adnexal mass. The results of our study showed that combining more than one marker measurement increased both the sensitivity and specificity of distinguishing patients with adnexal mass pathology.

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.

Unexpected malignancy at the time of hysterectomy performed for a benign indication: A retrospective review

Objective

To determine the proportion of patients undergoing hysterectomy for a benign indication who have unexpected malignancy (UM) on postoperative pathology and characterize the nature of UMs.

Methods

This was a multi-center, retrospective study of patients undergoing hysterectomy for a benign indication from July 2016 to December 2019 at 7 Ontario, Canada hospitals (4 academic, 3 community). Hysterectomies for invasive placentation, malignant, and premalignant indications were excluded. Primary outcome was rate of unexpected malignancy as defined by the number of patients with malignancy on final pathology divided by the total number of hysterectomy cases. Data was extracted from health records and electronic charts. Patient, surgical, and surgeon characteristics were compared between benign and UM groups using bivariate methods. Associations between UM status and perioperative variables were assessed using bivariate logistic regression.

Results

In the study period, 2779 hysterectomies were performed. UM incidence was 1.8% (51 malignancies/2779 cases), with one patient having two malignancies (total UMs = 52). The most common UM types were endometrial (27/52, 51.9%) and sarcoma (13/52, 25%). Patients with UM were older (57.2 ± 11.4 years vs. 52.8 ± 12.5 years, p = .015), had more previous laparotomies (2 (1.25, 2.0) vs. 1 (1.0, 1.0), p < .001), and higher BMI (29.7 ± 7.2 kg/m² vs. 28.0 ± 5.9 kg/m², p = .049) and ASA class (p < .028). Regarding surgical factors, patients with UM had more adhesions (p = .001), transfusions (p = .020), and blood loss (p = .006) compared to those with benign pathology. Patient characteristics most strongly associated with UM were age (OR 2.57, 95% CI 1.78–3.72, p < .001) and preoperative diagnosis of pelvic mass (OR 2.76, 95% CI 1.11–6.20, p = .019).

Conclusion

Incidence of UM at hysterectomy for benign indication was 1.8%. Several perioperative variables are associated with an increased chance of UM.

Quantitative global lipidomics analysis of patients with ovarian cancer versus benign adnexal mass

Altered lipid metabolism has emerged as an important feature of ovarian cancer (OC), yet the translational potential of lipid metabolites to aid in diagnosis and triage remains unproven. We conducted a multi-level interrogation of lipid metabolic phenotypes in patients with adnexal masses, integrating quantitative lipidomics profiling of plasma and ascites with publicly-available tumor transcriptome data. Using Sciex Lipidyzer, we assessed concentrations of > 500 plasma lipids in two patient cohorts-(i) a pilot set of 100 women with OC (50) or benign tumor (50), and (ii) an independent set of 118 women with malignant (60) or benign (58) adnexal mass. 249 lipid species and several lipid classes were significantly reduced in cases versus controls in both cohorts (FDR < 0.05). 23 metabolites-triacylglycerols, phosphatidylcholines, cholesterol esters-were validated at Bonferroni significance (P < 9.16 × 10-5). Certain lipids exhibited greater alterations in early- (diacylglycerols) or late-stage (lysophospholipids) cases, and multiple lipids in plasma and ascites were positively correlated. Lipoprotein receptor gene expression differed markedly in OC versus benign tumors. Importantly, several plasma lipid species, such as DAG(16:1/18:1), improved the accuracy of CA125 in differentiating early-stage OC cases from benign controls, and conferred a 15-20% increase in specificity at 90% sensitivity in multivariate models adjusted for age and BMI. This study provides novel insight into systemic and local lipid metabolic differences between OC and benign disease, further implicating altered lipid uptake in OC biology, and advancing plasma lipid metabolites as a complementary class of circulating biomarkers for OC diagnosis and triage.

Toll-like Receptor 2 as a Marker Molecule of Advanced Ovarian Cancer

Ovarian cancer is a global problem that affects women of all ages. Due to the lack of effective screening tests and the usually asymptomatic course of the disease in the early stages, the diagnosis is too late, with the result that less than half of the patients diagnosed with ovarian cancer (OC) survive more than five years after their diagnosis. In this study, we examined the expression of TLR2 in the peripheral blood of 50 previously untreated patients with newly diagnosed OC at various stages of the disease using flow cytometry. The studies aimed at demonstrating the usefulness of TLR2 as a biomarker in the advanced stage of ovarian cancer. In this study, we showed that TLR2 expression levels were significantly higher in women with more advanced OC than in women in the control group. Our research sheds light on the prognostic potential of TLR2 in developing new diagnostic approaches and thus in increasing survival in patients with confirmed ovarian cancer.

The role of inflammation biomarkers in differential diagnosis of pelvic tumours of ovarian origin: a single-centre observational study

Aim of the study

Our aim was to analyse the feasibility of white blood cell and platelet counts along with their ratios as a prognostic factor in patients who underwent surgery for ovarian mass.

Material and methods

We retrospectively studied the patients admitted in the Department of Gynaecology due to adnexal mass. The potential association of the neutrophil-to-lymphocyte-ratio (NLR), neutrophil-to-monocyte (NMR), platelet-to-lymphocyte (PLR), lymphocyte-to-monocyte (LMR), monocyte-to-platelet, and malignancy was evaluated.

Results

Patients with malignant tumours were found with significantly higher ratios of NLR (p < 0.001) and PLR (p < 0.001) and lower LMR ratio (p < 0.001) compared to those with benign tumours. Furthermore, higher lymphocyte count (p = 0.04) and platelet count (p = 0.004) were found in cancer patients when compared with borderline tumours. No significant variations were detected regarding white blood cell count (p = 0.238), NMR ratio (p = 0.28), platelet-to-neutrophil ratio (p = 0.12), and platelet-to-monocyte ratio (p = 0.34).

Conclusions

Inflammation biomarker ratios can easily and inexpensive assist in distinguishing malignant ovarian tumours from benign ones.

The value of human epididymis 4, D-dimer, and fibrinogen compared with CA 125 alone in triaging women presenting with pelvic masses: a retrospective cohort study

INTRODUCTION

CA 125, the biomarker in common clinical use for ovarian cancer, is limited by low sensitivity for early disease and high false positives. The aim of this study was to evaluate several candidate biomarkers, alone or in combination, compared with CA 125 in the prediction of malignant/borderline vs benign tumor status in premenopausal and postmenopausal women with pelvic masses.

MATERIAL AND METHODS

This was a retrospective observational cohort study set in St James's Hospital, a tertiary referral center for gynecological malignancy in Dublin, Ireland. Women undergoing surgery for pelvic masses between 2012 and 2018 were included. Preoperative human epididymis protein 4 (HE4), the Risk of Ovarian Malignancy Algorithm, the Risk of Malignancy Index I and II, D-dimer, and fibrinogen were assessed. Logistic regression models were fitted for each biomarker alone and in combination. Receiver operating characteristics-area under the curve (ROC-AUC) and partial AUCs in the 90%-100% specificity range were determined.

RESULTS

In all, 89 premenopausal and 185 postmenopausal women were included. In premenopausal women, no biomarker(s) outperformed CA 125 (AUC 0.73; 95% CI 0.63-0.84). In postmenopausal women, HE4 had a partial AUC (pAUC) of 0.71 (95% CI 0.64-0.79) compared with 0.57 (95% CI 0.51-0.69) for CA 125 (p = 0.009). HE4 + D-dimer had an improved pAUC of 0.74 (95% CI 0.68-0.81, p < 0.001) and HE4 + D-dimer + fibrinogen had a pAUC of 0.75 (95% CI 0.68-0.82).

CONCLUSIONS

A novel biomarker panel of HE4 ± D-dimer ± fibrinogen outperformed CA 125 alone as a high-specificity biomarker in postmenopausal women and could aid in the preoperative triaging of pelvic masses. No biomarker(s) outperformed CA 125 in premenopausal women.

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

Ovarian cancer remains one of the most common causes of death among gynecological malignancies afflicting women worldwide. Among the gynecological cancers, cervical and endometrial cancers confer the greatest burden to the developing and the developed world, respectively; however, the overall survival rates for patients with ovarian cancer are worse than the two aforementioned. The majority of patients with ovarian cancer are diagnosed at an advanced stage when cancer has metastasized to different body sites and the cure rates, including the five-year survival, are significantly diminished. The delay in diagnosis is due to the absence of or unspecific symptoms at the initial stages of cancer as well as a lack of effective screening and diagnostic biomarkers that can detect cancer at the early stages. This, therefore, provides an imperative to prospect for new biomarkers that will provide early diagnostic strategies allowing timely mitigative interventions. Glycosylation is a protein post-translational modification that is modified in cancer patients. In the current review, we document the state-of-the-art of blood-based glycomic biomarkers for early diagnosis of ovarian cancer and the technologies currently used in this endeavor.

Detection and analysis of multiple biomarkers in ovarian cancer: clinical significance in diagnosis, treatment, and prognosis evaluation

BACKGROUND

The purpose of this study was to explore the clinical significance of CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp in ovarian cancer.

METHODS

Ovarian cancer patients were recruited from Nantong Cancer Hospital between March 2006 and July 2011. The expressions of CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp were determined by immunohistochemistry (IHC).The chi-square test (χ2) was used to analyze the correlation between each index and the clinical characteristics of the patients. The patients were followed up to record the cancer recurrence time. The Kaplan-Meier method was used to map the cumulative recurrence-free survival (RFS) rate, and COX regression analysis was established for multivariate analysis.

RESULTS

The results of IHC showed that the positive expression rates of CA125, CK7, ER, C-erbb2, and P-gp in malignant ovarian cancer tissues were significantly higher than those in benign ovarian cancer tissues. CA125 expression in malignant ovarian cancer was significantly correlated with the age of patients and the Federation of International Gynecology and Obstetrics (FIGO) stage. CK7 expression in malignant ovarian cancer was significantly correlated with the age, tissue differentiation, and number of residual lesions. CK20 expression in malignant ovarian cancer was significantly correlated with the age and tissue differentiation of the patients. ER expression in malignant ovarian cancer was significantly correlated with the age of patients and FIGO stage. PR expression in malignant ovarian cancer was significantly correlated with the age of the patients. C-erbb2 expression in malignant ovarian cancer was significantly correlated with the age of the patients. P-gp expression in malignant ovarian cancer was significantly correlated with the patient age, pathological type, and tissue differentiation. The expression of CA125, CK7, CK20, C-erbb2, and P-gp had significant effects on the prognosis of patients with ovarian cancer. The COX regression analysis showed that P-gp was an independent risk factor for ovarian cancer.

CONCLUSIONS

In malignant ovarian cancer tissues, CA125, CK7, CK20, ER, PR, C-erbb2, and P-gp are over-expressed. The expression of P-gp is an independent risk factor for ovarian cancer, and it can be an important target for the treatment of malignant ovarian cancer.

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.

Development and validation of circulating CA125 prediction models in postmenopausal women

BACKGROUND

Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker.

METHODS

We developed and validated linear and dichotomous (≥35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC.

RESULT

The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset.

CONCLUSIONS

The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.

Technical Verification and Assessment of Independent Validation of Biomarker Models for Endometriosis

There is a great need for a noninvasive diagnosis for endometriosis. Several biomarkers and biomarker panels have been proposed. Biomarker models consisting of CA-125, VEGF, Annexin V, and glycodelin/sICAM-1 were previously developed by our group. The objective of our current study was to assess the impact of technical and biological variability on the performance of those previously developed prediction models in a technical verification and a validation setting. The technical verification cohort consisted of peripheral blood plasma samples from a subset of the patients included in the original study of Vodolazkaia et al. (99 women with and 37 women without endometriosis). The validation study was done in plasma samples of an independent patient cohort (170 women with and 86 women without endometriosis). Single immunoassays were used for CA-125, VEGF-A, sICAM-1, Annexin V, and glycodelin. Statistical analyses were done using univariate and multivariate (logistic regression) approaches. The previously reported prediction models for endometriosis had a low performance in both the technical verification and validation setting. New prediction models were developed, which included CA-125, Annexin V, and sICAM-1, but CA-125 was the only marker that was retained in the models across the technical verification and validation study. Overall, successful validation of a biomarker model depends on several factors such as patient selection, collection methods, assay selection/handling, stability of the marker, and statistical analysis and interpretation. There is a need for standardized studies in large, well-defined patient cohorts with robust assay methodologies.

Tumor markers: myths and facts unfolded

OBJECTIVE

The purpose of this article is to review the most commonly used tumor markers in abdominal and pelvic tumors, describe their limitations and explain how to use them in the context of known cancer in order to optimize multidisciplinary care of oncologic patients.

CONCLUSION

Tumor markers are important for the diagnosis, staging, monitoring of treatment and detection of recurrence in many cancers. This knowledge is crucial in the daily interpretation of images of oncologic and non-oncologic patients. However, radiologists should also be aware of the limitations of the most commonly used tumor markers and they should not be used solely, but interpreted in conjunction with diagnostic imaging, clinical history and physical examination that will help optimize the multidisciplinary care and management of oncologic patients.

Serum Biomarker Based Algorithms in Diagnosis of Ovarian Cancer: A Review

Epithelial ovarian cancer accounts for more than 90% of ovarian tumours and continues as a leading cause of death from gynaecological malignancies. It is often difficult to differentiate a benign ovarian mass from malignant ones. Invasive histopathological biopsy is used as the gold standard diagnostic tool to diagnose cancer in patients with ovarian mass. A wide spectrum of Biomarkers were tried in various studies to develop a non invasive diagnostic tool, out of which HE4 and CA 125 remain the only clinically useful biomarker. Consequently various Biomarker based algorithms i.e. Risk of Malignancy Index, risk of ovarian cancer algorithm, OVA1, risk of malignancy algorithm were generated that have been developed to assess the risk of a mass being malignant. These algorithms help in timely triage of patients. Recently in 2016 FDA cleared Ova1 test (OVERA) with CA 125-II, HE4, apolipoprotein A-1, FSH, and transferring (Sensitivity 91% and Specificity 69%) as a referral or Triage test in patients presenting with ovarian mass. Combination of protein and circulating Micro RNA analysis in blood, could provide a comprehensive screening and diagnostic panel, in management of patients presenting with ovarian mass in one clinical setting.

Ovarian cancer screening-ultrasound; impact on ovarian cancer mortality

Although ovarian cancer (OC) is the most lethal of all female malignancies, debate still exists concerning the benefits and harms of the screening programs and their impact on long-term survival and mortality from the disease. The most widely tested screening strategies have focused on transvaginal ultrasound (TVU) and on algorithms that measure serum levels or interval changes of cancer antigen-125 (CA-125) either individually or in combination. Transvaginal ultrasound can identify size and morphology changes of the ovary that may signal a developing malignancy; yet, it is still accused of having a low specificity. There is preliminary evidence that screening can improve survival, but the impact of screening on mortality from OC is still unclear and warrants further validation. In spite of having many published prospective studies, up to-date, none have been able to demonstrate conclusively a reduction in mortality from OC both in the screened general or high-risk population. Data from the US Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial has not shown survival or mortality benefits in the general population. Most prospective trials have reported a decrease in stage at detection (with the exception of the PLCO trial), thereby allowing treatment to be initiated when the disease is most curable. Research is in progress to develop new diagnostic tests and novel biomarkers, which when used in combination can increase the accuracy and outcomes of screening. In this review article, we will discuss the debate provoked on OC screening programs and the impact of using ultrasound on the reduction of OC-related mortality.

Does the Risk of Ovarian Malignancy Algorithm Provide Better Diagnostic Performance Than HE4 and CA125 in the Presurgical Differentiation of Adnexal Tumors in Polish Women?

Aim

This study compared the diagnostic performance of the Risk of Ovarian Malignancy Algorithm (ROMA) and HE4 and CA125 for the presurgical differentiation of adnexal tumors.

Material and Methods

This prospective study included 302 patients admitted for surgical treatment due to adnexal tumors. The ROMA was calculated depending on CA125, HE4, and menopausal status.

Results

Fifty patients were diagnosed with malignant disease. In the differentiation of malignant from nonmalignant adnexal tumors, the area under curve (AUC) was higher for ROMA and HE4 than that for CA125 in both the premenopausal and postmenopausal subgroups. In the differentiation of stage I FIGO malignancies and epithelial ovarian cancer from nonmalignant pathologies, the AUC of HE4 and ROMA was higher than that of CA125. The ROMA performed significantly better than CA125 in the differentiation of all malignancies and differentiation of stage I FIGO malignancies from nonmalignant pathologies (p = 0.043 and p = 0.025, resp.). There were no significant differences between the ROMA and the tumor markers for any other variants.

Conclusions

The ROMA is more useful than CA125 for the differentiation of malignant (including stage I FIGO) from nonmalignant adnexal tumors. It is also as useful as HE4 and CA125 for the differentiation of epithelial ovarian cancer from nonmalignant adnexal tumors.

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users.

Development of a tool for prediction of ovarian cancer in patients with adnexal masses: Value of plasma fibrinogen

Objective

To develop a tool for individualized risk estimation of presence of cancer in women with adnexal masses, and to assess the added value of plasma fibrinogen.

Study design

We performed a retrospective analysis of a prospectively maintained database of 906 patients with adnexal masses who underwent cystectomy or oophorectomy. Uni- and multivariate logistic regression analyses including pre-operative plasma fibrinogen levels and established predictors were performed. A nomogram was generated to predict the probability of ovarian cancer. Internal validation with split-sample analysis was performed. Decision curve analysis (DCA) was then used to evaluate the clinical net benefit of the prediction model.

Results

Ovarian cancer including borderline tumours was found in 241 (26.6%) patients. In multivariate analysis, elevated plasma fibrinogen, elevated CA-125, suspicion for malignancy on ultrasound, and postmenopausal status were associated with ovarian cancer and formed the basis for the nomogram. The overall predictive accuracy of the model, as measured by AUC, was 0.91 (95% CI 0.87–0.94). DCA revealed a net benefit for using this model for predicting ovarian cancer presence compared to a strategy of treat all or treat none.

Conclusion

We confirmed the value of plasma fibrinogen as a strong predictor for ovarian cancer in a large cohort of patients with adnexal masses. We developed a highly accurate multivariable model to help in the clinical decision-making regarding the presence of ovarian cancer. This model provided net benefit for a wide range of threshold probabilities. External validation is needed before a recommendation for its use in routine practice can be given.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

First International Consensus Report on Adnexal Masses: Management Recommendations

The First International Consensus Conference on Adnexal Masses was convened to thoroughly examine the state of the science and to formulate recommendations for clinical assessment and management. The panel included representatives of societies in the fields of gynecology, gynecologic oncology, radiology, and pathology and clinicians from Europe, Canada, and the United States. In the United States, there are approximately 9.1 surgeries per malignancy compared to the European International Ovarian Tumor Analysis center trials, with only 2.3 (oncology centers) and 5.9 (other centers) reported surgeries per malignancy, suggesting that there is room to improve our preoperative assessments. The American College of Obstetricians and Gynecologists Practice Bulletin on "Management of Adnexal Masses," reaffirmed in 2015 (Obstet Gynecol 2007; 110:201-214), still states, "With the exception of simple cysts on a transvaginal ultrasound finding, most pelvic masses in postmenopausal women will require surgical intervention." The panel concluded that patients would benefit not only from a more conservative approach to many benign adnexal masses but also from optimization of physician referral patterns to a gynecologic oncologist in cases of suspected ovarian malignancies. A number of next-step options were offered to aid in management of cases with sonographically indeterminate adnexal masses. This process would provide an opportunity to improve risk stratification for indeterminate masses via the provision of alternatives, including but not limited to evidence-based risk-assessment algorithms and referral to an "expert sonologist" or to a gynecologic oncologist. The panel believed that these efforts to improve clinical management and preoperative triage patterns would ultimately improve patient care.

The differential diagnosis of benign and malignant ovarian neoplasms (history)

The history of the differential diagnosis of ovarian neoplasms at the preoperative stage is presented in the review article. This is still a problem due to the high incidence of tumors and tumor-like formations of ovaries, the continuing upward trend in the index of ovarian cancer, along with a slight decrease in mortality and 5-year survival. Considerable success of surgical treatment and chemotherapy in the early stages of ovarian cancer suggests the earliest possible detection and accuracy of differential diagnosis of ovarian neoplasms. It highlights the role of the different research methods, including radiation imaging techniques, tumor markers and their potential advantages and disadvantages.

Validation of a Novel Biomarker Panel for the Detection of Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological malignancy. Our integrated -omics approach to ovarian cancer biomarker discovery has identified kallikrein 6 (KLK6) and folate-receptor 1 (FOLR1) as promising candidates but these markers require further validation.

METHODS

KLK6, FOLR1, CA125, and HE4 were investigated in three independent serum cohorts with a total of 20 healthy controls, 150 benign controls, and 216 ovarian cancer patients. The serum biomarker levels were determined by ELISA or automated immunoassay.

RESULTS

All biomarkers demonstrated elevations in the sera of ovarian cancer patients compared with controls (P < 0.01). Overall, CA125 and HE4 displayed the strongest ability (AUC 0.80 and 0.82, respectively) to identify ovarian cancer patients and the addition of HE4 to CA125 improved the sensitivity from 36% to 67% at a set specificity of 95%. In addition, the combination of HE4 and FOLR1 was a strong predictor of ovarian cancer diagnosis, displaying comparable sensitivity (65%) to the best-performing CA125-based models (67%) at a set specificity of 95%.

CONCLUSIONS

The markers identified through our integrated -omics approach performed similarly to the clinically approved markers CA125 and HE4. Furthermore, HE4 represents a powerful diagnostic marker for ovarian cancer and should be used more routinely in a clinical setting.

IMPACT

The implications of our study are 2-fold: (i) we have demonstrated the strengths of HE4 alone and in combination with CA125, lending credence to increasing its usage in the clinic; and (ii) we have demonstrated the clinical utility of our integrated -omics approach to identifying novel serum markers with comparable performance to clinical markers. Cancer Epidemiol Biomarkers Prev; 25(9); 1333-40. ©2016 AACR.

Diagnostic performance and establishment of reference limits of HE4 in Korean healthy women

OBJECTIVE

We aimed to establish distribution and reference limits of HE4 and risk of ovarian malignancy algorithm (ROMA) in healthy Korean women and investigated the factors influencing HE4 levels. We also investigated the diagnostic performances of HE4 and ROMA score, compared with CA125.

METHODS

We collected specimens from 1809 healthy Korean women, 140 specimens from patients with ovarian cancers (OCs) and 123 specimens from patients with benign ovarian tumor. Serum HE4 and CA125 concentrations were measured using an electrochemiluminescence immunoassay. The receiver operator characteristic (ROC) curve analysis was done for ROMA, HE4, CA125 and combining of HE4 and CA125.

RESULTS

HE4 level was influenced by age, not by menopausal status. The 97.5th percentile upper reference limit of HE4 of subjects <50years and ≥50year-old was 63.87pmol/L and 88.28pmol/L, respectively. The 97.5th percentile upper reference limits of ROMA score were 13.66 in premenopausal and 19.30 in postmenopausal women. The serum HE4 level was even lower in the patients with benign tumor compared to those in healthy controls. HE4 had significantly higher concentrations in OCs than benign ovarian tumor (P<0.001). ROMA and HE4 combined with CA125 or not performed better diagnostically than CA125 alone for distinguishing OCs, with AUCs of 0.844 for ROMA, 0.827 for combining of HE4 and CA125, 0.825 for HE4, and 0.795 for CA125.

CONCLUSIONS

The reference limit of HE4 was different from those reported by other studies, suggesting racial or regional difference. HE4 and ROMA were better than CA125 for differentiation normal and benign ovarian tumor from OCs. (Word count: 253).

Biological markers of prognosis, response to therapy and outcome in ovarian carcinoma

INTRODUCTION

Ovarian cancer (OvCa) is among the most common types of cancer and is the leading cause of death from gynecological malignancies in western countries. Cancer biomarkers have a potential for improving the management of OvCa patients at every point from screening and detection, diagnosis, prognosis, follow up, response to therapy and outcome.

AREAS COVERED

The literature search has indicated a number of candidate biomarkers have recently emerged that could facilitate the molecular definition of OvCa, providing information about prognosis and predicting response to therapy. These potentially promising biomarkers include immune cells and their products, tumor-derived exosomes, nucleic acids and epigenetic biomarkers. Expert commentary: Although most of the biomarkers available today require prospective validation, the development of noninvasive liquid biopsy-based monitoring promises to improve their utility for evaluations of prognosis, response to therapy and outcome in OvCa.

Pathobiological role of MUC16 mucin (CA125) in ovarian cancer: Much more than a tumor biomarker

MUC16 (CA125) has remained the mainstay for ovarian cancer assessment and management since the early 1980’s. With the exception of HE4, it is the only reliable serum biomarker for ovarian cancer. MUC16 belongs to a family of high-molecular weight glycoproteins known as mucins. The mucin family is comprised of large secreted transmembrane proteins that includes MUC1, MUC4 and MUC16. These mucins are often overexpressed in a variety of malignancies. MUC1 and MUC4 have been shown to contribute to breast and pancreatic tumorigenesis. Recent studies have uncovered unique biological functions for MUC16 that go beyond its role as a biomarker for ovarian cancer. Here, we provide an overview of the literature to highlight the importance of MUC16 in ovarian cancer tumorigenesis. We focus on the growing literature describing the role of MUC16 in proliferation, migration, metastasis, tumorigenesis and drug resistance. Accumulating experimental evidence suggest that the C-terminal domain of MUC16 is critical to mediate theses effects. The importance of MUC16 in the pathogenesis of ovarian cancer emphasizes the need to fully understand the signaling capabilities of MUC16 C-terminal domain to develop more efficient strategies for the successful treatment of ovarian cancer.

Current clinical application of serum biomarkers to detect ovarian cancer

For the last decades, hundreds of potential serum biomarkers have been assessed in diagnosing of ovarian cancer including the wide spectrum of cytokines, growth factors, adhesion molecules, proteases, hormones, coagulation factors, acute phase reactants, and apoptosis factors but except CA125 none of them have been applied to everyday clinical practice. Nowadays, the growing number of evidence suggests that the classic marker CA125 should be accompanied by HE4 and in fact, Risk of Ovarian Malignancy Algorithm (ROMA) is becoming more and more widespread in clinical practice for the evaluation of adnexal masses. Early ovarian cancer is often asymptomatic, so the challenge still exists to develop serum markers suitable for early diagnosis and screening. Current knowledge strongly points to different mechanisms of pathogenesis, genetic disturbances and clinical course of major histological subtypes of ovarian cancer. Thus, future biomarker/multimarker panels should take into consideration the implications of different molecular patterns and biological behavior of various subtypes of ovarian cancer. Very promising are studies on miRNAs – small non-protein coding gene-regulatory RNA molecules functionally involved in the pathogenesis of cancers acting as oncogenes (oncomirs) or tumor suppressors. The studies devoted to ovarian cancer tissue miRNA profiling have shown that miRNAs could be useful in diagnosing and predicting the OC outcome. They also confirmed that OC is a highly heterogeneous disease, gathering four distinct histological tumor subtypes characterized not only by distinct origin, behavior and response to chemotherapy but also by different patterns of miRNA expression.

Lavage of the Uterine Cavity for Molecular Detection of Müllerian Duct Carcinomas: A Proof-of-Concept Study

Purpose

Type II ovarian cancer (OC) and endometrial cancer (EC) are generally diagnosed at an advanced stage, translating into a poor survival rate. There is increasing evidence that Müllerian duct cancers may exfoliate cells. We have established an approach for lavage of the uterine cavity to detect shed cancer cells.

Patients and Methods

Lavage of the uterine cavity was used to obtain samples from 65 patients, including 30 with OC, five with EC, three with other malignancies, and 27 with benign lesions involving gynecologic organs. These samples, as well as corresponding tumor tissue, were examined for the presence of somatic mutations using massively parallel sequencing (next-generation sequencing) and, in a subset, singleplex analysis.

Results

The lavage technique could be applied successfully, and sufficient amounts of DNA were obtained in all patients. Mutations, mainly in TP53, were identified in 18 (60%) of 30 lavage samples of patients with OC using next-generation sequencing. Singleplex analysis of mutations previously determined in corresponding tumor tissue led to further identification of six patients. Taken together, in 24 (80%) of 30 patients with OC, specific mutations could be identified. This also included one patient with occult OC. All five analyzed lavage specimens from patients with EC harbored mutations. Eight (29.6%) of 27 patients with benign lesions tested positive for mutations, six (75%) as a result of mutations in the KRAS gene.

Conclusion

This study proved that tumor cells from ovarian neoplasms are shed and can be collected via lavage of the uterine cavity. Detection of OC and EC and even clinically occult OC was achieved, making it a potential tool of significant promise for early diagnosis.

Prognostic value and characterization of the ovarian cancer-specific antigen CA166-9

COC166-9 is an ovarian cancer-specific monoclonal antibody, and COC166-9-based immunotherapy has been shown to possess killing effects against ovarian cancer cells in vitro and in vivo. However the antigen recognized by COC166-9 (COC166-9-Ag, CA166-9) has not been identified and the clinical significance of CA166-9 expression remains unknown. We found that CA166-9 was positive in 53.1% of ovarian cancer tissues. Expression of CA166-9 was strongly correlated with the cancer recurrence (P<0.001). Patients with positive CA166-9 had substantially shorter overall survival (P=0.026) and disease-free survival (P=0.002). CA166-9 was also shown to be an independent predictive factor for overall survival (HR=2.454, P=0.016) and disease-free survival (HR=2.331, P=0.021). We identified CA166-9 as human immunoglobulin γ-1 heavy chain constant region (IGHG1). Purified IGHG1 promoted proliferation, migration, and invasion of CA166-9-negative ovarian cancer HOC1A cells, whereas it had minimal effects on the phenotypes of CA166-9-positive ovarian cancer CAOV-3 cells. In addition, overexpression of IGHG1 enhanced migration of ovarian cancer cells. On the contrary, COC166-9 inhibited proliferation, migration, and invasion of CAOV-3 cells, but had no effects on HOC1A cells. Therefore, IGHG1 similarly to CA166-9, could play an important role in ovarian cancer development and may serve as a potential prognostic marker and a therapeutical target for ovarian cancer.

ARHI (DIRAS3)-mediated autophagy-associated cell death enhances chemosensitivity to cisplatin in ovarian cancer cell lines and xenografts

Autophagy can sustain or kill tumor cells depending upon the context. The mechanism of autophagy-associated cell death has not been well elucidated and autophagy has enhanced or inhibited sensitivity of cancer cells to cytotoxic chemotherapy in different models. ARHI (DIRAS3), an imprinted tumor suppressor gene, is downregulated in 60% of ovarian cancers. In cell culture, re-expression of ARHI induces autophagy and ovarian cancer cell death within 72 h. In xenografts, re-expression of ARHI arrests cell growth and induces autophagy, but does not kill engrafted cancer cells. When ARHI levels are reduced after 6 weeks, dormancy is broken and xenografts grow promptly. In this study, ARHI-induced ovarian cancer cell death in culture has been found to depend upon autophagy and has been linked to G1 cell-cycle arrest, enhanced reactive oxygen species (ROS) activity, RIP1/RIP3 activation and necrosis. Re-expression of ARHI enhanced the cytotoxic effect of cisplatin in cell culture, increasing caspase-3 activation and PARP cleavage by inhibiting ERK and HER2 activity and downregulating XIAP and Bcl-2. In xenografts, treatment with cisplatin significantly slowed the outgrowth of dormant autophagic cells after reduction of ARHI, but the addition of chloroquine did not further inhibit xenograft outgrowth. Taken together, we have found that autophagy-associated cancer cell death and autophagy-enhanced sensitivity to cisplatin depend upon different mechanisms and that dormant, autophagic cancer cells are still vulnerable to cisplatin-based chemotherapy.

Diagnostic value of preoperative SUVmax on FDG-PET/CT for the detection of ovarian cancer

OBJECTIVE

The objective of this study was to investigate the preoperative diagnostic value of F-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography and computed tomography (PET/CT) in patients with ovarian cancer.

METHODS

One hundred sixty patients suspected of having malignant ovarian tumors were included in this study. All patients underwent FDG-PET/CT scans before operation, and the maximum standardized uptake value (SUVmax) of the primary tumor was measured. We evaluated the diagnostic accuracy of SUVmax for detecting malignancy and its relationship with histological findings.

RESULTS

Postoperative pathological diagnoses showed that 67 were malignant, 14 were borderline malignant, and 79 were benign tumors. With the use of a cutoff SUVmax of 2.9 obtained from the receiver operating characteristic curve analysis, the sensitivity, specificity, positive predictive value, and negative predictive value for detecting malignancy were 80.6%, 94.6%, 91.5%, and 87.1%, respectively. Positive FDG accumulation (SUVmax ≥ 2.9) was shown in 89.5% of serous adenocarcinoma and in 92.3% of endometrioid adenocarcinoma. In contrast, lower frequencies of positive FDG accumulation were shown in clear cell adenocarcinoma (54.5%), mucinous adenocarcinoma (66.7%), and metastatic carcinoma (66.7%), and the median SUVmax of these 3 histological types were significantly lower than those of serous and endometrioid types. In addition, a positive FDG accumulation was shown in all patients with malignant transformation of mature cystic teratoma. Finally, of the 14 borderline malignant tumors, only 2 (14.3%) showed positive FDG accumulation.

CONCLUSIONS

The SUVmax on FDG-PET/CT is useful for differentiating ovarian cancer from borderline or benign tumor with a high specificity and positive predictive value. However, our data also demonstrated a lower FDG uptake value in clear cell or mucinous histological finding, suggesting that SUVmax may vary depending on the tumor histological subtype.

A multiplexable, microfluidic platform for the rapid quantitation of a biomarker panel for early ovarian cancer detection at the point-of-care

Point-of-care (POC) diagnostic platforms have the potential to enable low-cost, large-scale screening. As no single biomarker is shed by all ovarian cancers, multiplexed biomarker panels promise improved sensitivity and specificity to address the unmet need for early detection of ovarian cancer. We have configured the programmable bio-nano-chip (p-BNC)-a multiplexable, microfluidic, modular platform-to quantify a novel multi-marker panel comprising CA125, HE4, MMP-7, and CA72-4. The p-BNC is a bead-based immunoanalyzer system with a credit-card-sized footprint that integrates automated sample metering, bubble and debris removal, reagent storage and waste disposal, permitting POC analysis. Multiplexed p-BNC immunoassays demonstrated high specificity, low cross-reactivity, low limits of detection suitable for early detection, and a short analysis time of 43 minutes. Day-to-day variability, a critical factor for longitudinally monitoring biomarkers, ranged between 5.4% and 10.5%, well below the biologic variation for all four markers. Biomarker concentrations for 31 late-stage sera correlated well (R(2) = 0.71 to 0.93 for various biomarkers) with values obtained on the Luminex platform. In a 31 patient cohort encompassing early- and late-stage ovarian cancers along with benign and healthy controls, the multiplexed p-BNC panel was able to distinguish cases from controls with 68.7% sensitivity at 80% specificity. Utility for longitudinal biomarker monitoring was demonstrated with prediagnostic plasma from 2 cases and 4 controls. Taken together, the p-BNC shows strong promise as a diagnostic tool for large-scale screening that takes advantage of faster results and lower costs while leveraging possible improvement in sensitivity and specificity from biomarker panels.

MUC16 (CA125): tumor biomarker to cancer therapy, a work in progress

Over three decades have passed since the first report on the expression of CA125 by ovarian tumors. Since that time our understanding of ovarian cancer biology has changed significantly to the point that these tumors are now classified based on molecular phenotype and not purely on histological attributes. However, CA125 continues to be, with the recent exception of HE4, the only clinically reliable diagnostic marker for ovarian cancer. Many large-scale clinical trials have been conducted or are underway to determine potential use of serum CA125 levels as a screening modality or to distinguish between benign and malignant pelvic masses. CA125 is a peptide epitope of a 3-5 million Da mucin, MUC16. Here we provide an in-depth review of the literature to highlight the importance of CA125 as a prognostic and diagnostic marker for ovarian cancer. We focus on the increasing body of literature describing the biological role of MUC16 in the progression and metastasis of ovarian tumors. Finally, we consider previous and on-going efforts to develop therapeutic approaches to eradicate ovarian tumors by targeting MUC16. Even though CA125 is a crucial marker for ovarian cancer, the exact structural definition of this antigen continues to be elusive. The importance of MUC16/CA125 in the diagnosis, progression and therapy of ovarian cancer warrants the need for in-depth research on the biochemistry and biology of this mucin. A renewed focus on MUC16 is likely to culminate in novel and more efficient strategies for the detection and treatment of ovarian cancer.

Preparation and characterization of luteinising-hormone releasing hormone nanoliposomal microbubbles specifically targeting ovarian cancer cells in vitro

The aim of the present study was to prepare luteinizing-hormone releasing hormone (LHRH) nanoliposomal microbubbles specifically targeting ovarian cancer cells. The lyophilization/sonication method was used to prepare non-targeting nanoliposomal microbubbles (N-N-Mbs). Using the biotin-avidin bridge method, conjugated LHRH antibodies to N-N-Mbs generated LHRH nanoliposomal microbubbles (LHRH-N-Mbs) specifically targeting ovarian cancer cells. The morphology and physicochemical properties of the microbubbles was detected using an optical microscope and zeta detector. The binding affinity between the secondary antibody and LHRH-N-Mbs or N-N-Mbs was determined by flow cytometry. The binding of LHRH-N-Mb to human ovarian cancer cells (OVCAR-3) was detected by light microscopy. The rounded and uniformly distributed N-N-Mbs and LHRH-N-Mbs were successfully generated. The particle size ranged from 295-468 nm with a mean of 360 nm for N-N-Mbs or 369-618 nm with a mean of 508 nm for LHRH-N-Mbs. There was a significant difference in size between the two groups (P<0.05), although the surface potential of the two microbubbles remained the same (-14.6 mV). Following being kept at room temperature for 14 days, no significant difference in the physicochemical properties of the LHRH-N-Mbs was detected compared with that of freshly prepared microbubbles. The secondary antibody binding rate of LHRH-N-Mbs and N-N-Mbs was 75.6 and 0.83%, respectively. Furthermore, the formation of a rosette-like structure surrounding OVCAR-3 cells was observed after the cells were incubated with LHRH-N-Mbs, whereas pre-incubation with LHRH antibody blocked this rosette formation. In conclusion, LHRH-N-Mbs specifically targeting ovarian cancer cells were successfully prepared through biotin-avidin mediation and the lyophilization/sonication method. The key feature of LHRH-N-Mbs is their small size, stability and high efficiency in targeting human OVCAR-3 cells in vitro.

Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis

BACKGROUND Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. METHODS An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95% confidence intervals or plot summary ROC curves for all models considered. RESULTS Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27%) malignant and 19 239 (73%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-off of 10% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95% CI 0.88-0.95] and 0.83 [95% CI 0.77-0.88] for LR2 and 0.93 [95% CI 0.89-0.95] and 0.81 [95% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-off of 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95% CI 0.75-0.91] and 0.91 [95% CI 0.83-0.96] compared with 0.93 [95% CI 0.84-0.97] and 0.83 [95% CI 0.73-0.90] for SR and 0.44 [95% CI 0.28-0.62] and 0.95 [95% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95% CI 0.89-0.97] and 0.70 [95% CI 0.62-0.77], 0.93 [95% CI 0.88-0.96] and 0.76 [95% CI 0.69-0.82], and 0.79 [95% CI 0.72-0.85] and 0.90 [95% CI 0.84-0.94], respectively. CONCLUSIONS An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age.

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies

Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

The emerging role of HE4 in the evaluation of epithelial ovarian and endometrial carcinomas

HE4 (human epididymis protein 4) is overexpressed in both ovarian and endometrial cancers. Levels of the shed HE4 protein are elevated in sera from ovarian and endometrial cancer patients. HE4 is less frequently elevated than cancer antigen 125 (CA 125) in benign gynecologic conditions and is found in a fraction of endometrial and ovarian cancers that lack CA 125 expression. Consequently, HE4 has emerged as an important biomarker that complements CA 125 in discriminating between benign and malignant pelvic masses, monitoring response to treatment, and detecting recurrences of both ovarian and endometrial cancer. The "risk of ovarian malignancy algorithm" (ROMA) incorporates CA 125, HE4, and menopausal status to distinguish benign from malignant adnexal masses, and has been approved by the US Food and Drug Administration to aid in referring patients who are likely to have ovarian cancer to specially trained gynecologic oncologists for surgery. HE4 also promises to augment the sensitivity of CA 125 for detecting early-stage ovarian cancer. In this review, we discuss the discovery and biologic significance of HE4 and evaluate available evidence regarding the utility of HE4 as a biomarker for ovarian and endometrial cancer.

Diagnostic value of ultrasound indicators of neoplastic risk in preoperative differentiation of adnexal masses

AIM

To assess the diagnostic value of the risk of malignancy indices and simple ultrasound- based rules in preoperative differentiation of adnexal masses.

MATERIAL AND METHODS

Retrospective examination of 87 patients admitted to hospital due to adnexal tumors. The lesions were evaluated on the basis of international ultrasound classification of ovarian tumors and four risk of malignancy indices were calculated based on ultrasound examination, concentration of CA 125 and menopausal status.

RESULTS

The patients were aged between 17 and 79, the mean age was 44.5 (standard deviation SD=16.6). Most of the patients (60.91%) were before their menopause. The sensitivity of the simple ultrasound-based rules in the diagnosis of malignancies equaled 64.71% and the specificity constituted 90.00%. A significant statistical difference in the presence of the malignant process was demonstrated in relation to age, menopausal status, CA 125 concentration and analyzed ultrasound score. All indices were characterized by similar sensitivity and specificity. The highest specificity and predictive value of malignant lesions out of the assessed ones was demonstrated by the risk of malignancy index proposed by Yamamoto. The risk of malignancy index according to Jacobs, however, showed the highest predictive value in the case of non-malignant lesions.

CONCLUSIONS

The multiparametric ultrasound examination may facilitate the selection of patients with adnexal tumors to provide them with an appropriate treatment - observation, laparotomy and laparoscopy. These parameters constitute a simple ambulatory method of determining the character of adnexal masses before recommending appropriate treatment.