Potential markers that complement expression of CA125 in epithelial ovarian cancer

Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer

BACKGROUND

Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer.

METHODS

Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone.

RESULTS

Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis.

CONCLUSION

A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The High Sensitivity of the Multi-Cancer Detection Test ONCOVERYX-F Offers a Promising Platform for Ovarian Cancer Screening

We evaluated the potential relevance of our multi-cancer detection test, OncoVeryx-F, for ovarian cancer screening. For this, we compared its accuracy with that of CA125-based screening. We demonstrate here that, in contrast to CA125-based detection, OncoVeryx-F detected ovarian cancer with very high sensitivity and specificity. Importantly here, Stage I cancers too could be detected with an accuracy of >98%. Furthermore, again unlike CA 125, the detection accuracy of OncoVeryx-F remained comparable in both Caucasian and South Asian/Indian women. Thus, the robustness and accuracy of OncoVeryx-F, particularly for early-stage detection, underscores its potential utility for ovarian cancer screening.

Prediction model of adnexal masses with complex ultrasound morphology

Background

Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.

Methods

In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).

Results

Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.

Conclusion

The risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.

The performance of Carbohydrate Antigen 125-Thomsen-nouveau and anti-Müllerian hormone combined with CA125, Human epididymis protein 4 and Risk of Malignancy Algorithm in diagnosis for patients with Epithelial ovarian cancer

OBJECTIVES

We examined the blood concentrations of Carbohydrate Antigen 125-Thomsen-nouveau (CA125-Tn) and anti-Müllerian hormone (AMH) in epithelial ovarian cancer (EOC) patients to evaluate their potential diagnostic utility together with CA125, human epididymis protein 4 (HE4) and Risk of Malignancy Algorithm (ROMA).

DESIGN & METHODS

50 healthy subjects, 45 EOC patients, 22 patients with borderline ovarian tumors (BOT), 21 patients with benign ovarian tumor (BET) and 45 patients with chocolate cyst of ovary (CCO) were studied. Blood levels of CA125, HE4, CA125-Tn and AMH were measured, and the ROMA value was calculated. We compared the differences in the levels of these biomarkers among groups. Additionally, a total of 10 testing strategies were established for comparison to maximize the diagnostic value.

RESULTS

The levels of CA125, HE4, CA125-Tn and ROMA value were significantly higher in EOC group compared with either the disease control (DC) group (BOT group, BET group and CCO group) or healthy control (HC) group (p < 0.001). In addition, they had better discriminatory performance with an area under the receiver operator characteristic curve (AUC) 0.93; 0.93; 0.93; 0.85, respectively (p < 0.001) compared with the AUC value of AMH 0.67 (p < 0.001). Among all 10 testing strategies, both single-positive of ROMA and double-positive of any 2 markers showed better Youden index (0.82, 0.79, respectively) and kappa value (κ) (0.82, 0.81, respectively).

CONCLUSIONS

CA125-Tn and AMH can be treated as useful biomarkers of EOC when combined with CA125, HE4 and ROMA, because when any two biomarkers of them are positive, the value of EOC diagnosis is maximized.

Crosstalk of Immune Cells and Platelets in an Ovarian Cancer Microenvironment and Their Prognostic Significance

Ovarian cancer (OC) is one of the deadliest gynecological cancers, largely due to the fast development of metastasis and drug resistance. The immune system is a critical component of the OC tumor microenvironment (TME) and immune cells such as T cells, NK cells, and dendritic cells (DC) play a key role in anti-tumor immunity. However, OC tumor cells are well known for evading immune surveillance by modulating the immune response through various mechanisms. Recruiting immune-suppressive cells such as regulatory T cells (Treg cells), macrophages, or myeloid-derived suppressor cells (MDSC) inhibit the anti-tumor immune response and promote the development and progression of OC. Platelets are also involved in immune evasion by interaction with tumor cells or through the secretion of a variety of growth factors and cytokines to promote tumor growth and angiogenesis. In this review, we discuss the role and contribution of immune cells and platelets in TME. Furthermore, we discuss their potential prognostic significance to help in the early detection of OC and to predict disease outcome.

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

Background

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

Methods

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

Results

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

Conclusion

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

GD2 and GD3 gangliosides as diagnostic biomarkers for all stages and subtypes of epithelial ovarian cancer

Background

Ovarian cancer (OC) is the deadliest gynecological cancer, often diagnosed at advanced stages. A fast and accurate diagnostic method for early-stage OC is needed. The tumor marker gangliosides, GD2 and GD3, exhibit properties that make them ideal potential diagnostic biomarkers, but they have never before been quantified in OC. We investigated the diagnostic utility of GD2 and GD3 for diagnosis of all subtypes and stages of OC.

Methods

This retrospective study evaluated GD2 and GD3 expression in biobanked tissue and serum samples from patients with invasive epithelial OC, healthy donors, non-malignant gynecological conditions, and other cancers. GD2 and GD3 levels were evaluated in tissue samples by immunohistochemistry (n=299) and in two cohorts of serum samples by quantitative ELISA. A discovery cohort (n=379) showed feasibility of GD2 and GD3 quantitative ELISA for diagnosing OC, and a subsequent model cohort (n=200) was used to train and cross-validate a diagnostic model.

Results

GD2 and GD3 were expressed in tissues of all OC subtypes and FIGO stages but not in surrounding healthy tissue or other controls. In serum, GD2 and GD3 were elevated in patients with OC. A diagnostic model that included serum levels of GD2+GD3+age was superior to the standard of care (CA125, p<0.001) in diagnosing OC and early-stage (I/II) OC.

Conclusion

GD2 and GD3 expression was associated with high rates of selectivity and specificity for OC. A diagnostic model combining GD2 and GD3 quantification in serum had diagnostic power for all subtypes and all stages of OC, including early stage. Further research exploring the utility of GD2 and GD3 for diagnosis of OC is warranted.

A review of recent advances on single use of antibody-drug conjugates or combination with tumor immunology therapy for gynecologic cancer

Immune checkpoint inhibitors have made significant progress in the treatment of various cancers. However, due to the low ICI responsive rate for the gynecologic cancer, ICI two-drug combination therapy tends to be a predominant way for clinical treatment. Antibody-drug conjugates, a promising therapeutic modality for cancer, have been approved by the FDA for breast cancer, lymphoma, multiple myeloma and gastric cancer. On September 2021, the FDA granted accelerated approval to tisotumab vedotin for patients with recurrent or metastatic cervical cancer. Currently, the role of therapy of ADCs on gynecologic tumors was also included in medication regimens. Now more than 30 ADCs targeting for 20 biomarkers are under clinical trials in the field, including monotherapy or combination with others for multiple lines of therapy. Some ADCs have been proved to enhance the antitumor immunity effect on both pre-clinical models and clinical trials. Therefore, combination of ADCs and ICIs are expected in clinical trials. In this review, we discuss current development of ADCs in gynecologic oncology and the combination effects of ICIs and ADCs.

The Potential Role of MUC16 (CA125) Biomarker in Lung Cancer: A Magic Biomarker but with Adversity

Lung cancer is the second most commonly diagnosed cancer in the world. In terms of the diagnosis of lung cancer, combination carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) detection had higher sensitivity, specificity, and diagnostic odds ratios than CEA detection alone. Most individuals with elevated serum CA125 levels had lung cancer that was either in stage 3 or stage 4. Serum CA125 levels were similarly elevated in lung cancer patients who also had pleural effusions or ascites. Furthermore, there is strong evidence that human lung cancer produces CA125 in vitro, which suggests that other clinical illnesses outside of ovarian cancer could also be responsible for the rise of CA125. MUC16 (CA125) is a natural killer cell inhibitor. As a screening test for lung and ovarian cancer diagnosis and prognosis in the early stages, CA125 has been widely used as a marker in three different clinical settings. MUC16 mRNA levels in lung cancer are increased regardless of gender. As well, increased expression of mutated MUC16 enhances lung cancer cells proliferation and growth. Additionally, the CA125 serum level is thought to be a key indicator for lung cancer metastasis to the liver. Further, CA125 could be a useful biomarker in other cancer types diagnoses like ovarian, breast, and pancreatic cancers. One of the important limitations of CA125 as a first step in such a screening technique is that up to 20% of ovarian tumors lack antigen expression. Each of the 10 possible serum markers was expressed in 29-100% of ovarian tumors with minimal or no CA125 expression. Therefore, there is a controversy regarding CA125 in the diagnosis and prognosis of lung cancer and other cancer types. In this state, preclinical and clinical studies are warranted to elucidate the clinical benefit of CA125 in the diagnosis and prognosis of lung cancer.

CT imaging phenotypes linked to CA125 and HE4 biomarkers are highly predictive in discriminating between hereditary and sporadic ovarian cancer patients

BACKGROUND: Hereditary ovarian cancers (HOC) represent about 23% of ovarian cancer (OC) cases: they are most frequently related to germline mutations in the BRCA genes. OBJECTIVE: We aimed to compare CA125/HE4 serum levels and Computed Tomography (CT) features at time of ovarian cancer (OC) diagnosis in two populations: BRCA mutant and BRCA wild-type (WT) OC, and to investigate the relationship between this laboratory and radiological biomarker and BRCA mutation status. METHODS: This retrospective study included 60 newly diagnosed OC patients with FIGO stage IIIC-IV disease, tested for BRCA1/2 germline mutation status of which preoperative CT scan and serum tumor marker assay were available. RESULTS: The median level of CA125 (708 U/mL) was significantly higher (p < 0.002) in BRCA1/2 mutated patients than in WT patients (176 U/mL), whereas the median level of HE4 (492 pmol/L) was significantly higher (p < 0.002) in WT than in BRCA-mutated patients (252 pmol/L). BRCA mutation carriers showed a higher incidence of bilateral ovarian masses (p = 0.0303) characterized by solid structures (p < 0.00001), higher peritoneal tumor load, macronodular implants >2 cm (p = 0.000099), increased frequency of lymphadenopathies (p = 0.019), and metastasis (p = 0.052) compared to patients with BRCA WT. CONCLUSIONS: Tumor markers and CT patterns may help in identifying BRCA mutation status in OC directing patients towards a personalized treatment.

Potential roles of claudin-3 and claudin-4 in ovarian cancer management

BACKGROUND

Ovarian cancer has the highest mortality amongst all gynaecological malignancies, with around two-thirds of patients diagnosed with advanced disease due to late presentation. Furthermore, around 90% of patients develop recurrence and eventually become chemoresistant. Therefore, there is a high demand to identify biomarkers specific to this disease for screening for early detection, as well as new therapeutic targets. Tight junctions (TJs) regulate paracellular permeability and are vital in establishing epithelial cell polarity. One hallmark of tumorigenesis is the loss of TJs, with loss of cell-to-cell adhesion. Claudins are integral TJ membrane proteins, which have been found to play a critical role in maintaining the TJ's barrier function. Furthermore, claudin-3 (CLDN3) and claudin-4 (CLDN4) are overexpressed in ovarian cancer. This article aims to explore the biological role of CLDN3 and CLDN4 and their potential in different aspects of the management of ovarian cancer.

MAIN BODY

CLDN3 and CLDN4 have been shown to be effective markers for the early detection of ovarian cancer. Whilst there is difficulty in screening for both claudins in serum, their assessment by gene expression analysis and immunohistochemical methods shows promising potential as diagnostic and prognostic biomarkers for ovarian cancer. The localisation and overexpression of claudins, such as CLDN3, have been shown to correlate with poorer survival outcomes. The added value of combining claudins with other markers such as CA125 for diagnosis has also been highlighted. Therapeutically, CLDN3 and more so CLDN4 have been shown to be effective targets of Clostridium perfringens enterotoxin (CPE). Interestingly, CPE has also been shown to resensitise chemoresistant tumours to therapy.

CONCLUSIONS

This review presents the diagnostic and prognostic potential of CLDN3 and CLDN4 and their emerging role as therapeutic targets in ovarian cancer. Clinical trials are required to validate the promising results of the in vitro and in vivo studies for CLDN3 and CLDN4, possibly adding onto current ovarian cancer management.

A Clinical Diagnostic Value Analysis of Serum CA125, CA199, and HE4 in Women with Early Ovarian Cancer: Systematic Review and Meta-Analysis

Objective

To evaluate the value of combined detection of serum CA125, CA199, and HE4 in the diagnosis of ovarian cancer.

Methods

Relevant articles retrieved from PubMed, Elsevier Science, Springer, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP databases were screened strictly according to inclusion and exclusion criteria. Included literature published from January 2005 to December 2021. (2) Serum HE4, CA125, CA199, and their combination for ovarian cancer diagnostic tests were studied, and healthy subjects or patients with the benign disease were taken as a control group. (3) Pathological tissue diagnosis as the gold standard. (4) Complete original data can be obtained. (5) The sample size was ≥20. (6) Language is limited to Chinese and English. Data features and QUADAS table were extracted from the included literature, and QUADAS evaluation tool detail table was used for the included study. Conduct quality evaluation. Statistical analysis was carried out using meta-disc software version 1.4. Appropriate effect model was selected to merge the effect size, and the forest maps of merge sensitivity, merge specificity, and merge likelihood ratio were obtained.

Results

The results of meta-analysis showed that there was a statistical difference in diagnostic specificity analysis of CA125 (OR = 1.91, 95% CI (1.58, 2.32), P < 0.00001, I² = 67%, Z = 6.58); diagnostic sensitivity analysis of CA125 (OR = 2.50, 95% CI (1.73, 3.62), P < 0.00001, I² = 0%, Z = 4.90); diagnostic specificity analysis of CA199 (OR = 1.98, 95% CI (1.60, 2.44), P < 0.00001, I² = 89%, Z = 6.35); diagnostic sensitivity analysis of CA199 (OR = 1.92, 95% CI (1.46, 2.52), P < 0.00001, I² = 73%, Z = 4.70); diagnostic specificity analysis of HE4 (OR = 2.08, 95% CI (1.65, 2.63), P < 0.00001, I² = 73%, Z = 6.19); diagnostic sensitivity analysis of HE4 (OR = 2.37, 95% CI (1.87, 3.00), P < 0.00001, I² = 83%, Z = 7.19).

Conclusion

In the clinical assisted diagnosis of ovarian cancer, combined detection of CA125, CA199, and HE4 has the stronger discriminant ability and higher accuracy than single detection of CA125, which can improve the diagnostic efficiency.

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers

Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cases to an unfavourable prognosis. Current predictive algorithms used to estimate the risk of having Ovarian Cancer fail to provide sufficient sensitivity and specificity to be used widely in clinical practice. The use of additional biomarkers or parameters such as age or menopausal status to overcome these issues showed only weak improvements. It is necessary to identify novel molecular signatures and the development of new predictive algorithms able to support the diagnosis of HGSOC, and at the same time, deepen the understanding of this elusive disease, with the final goal of improving patient survival. Here, we apply a Machine Learning-based pipeline to an open-source HGSOC Proteomic dataset to develop a decision support system (DSS) that displayed high discerning ability on a dataset of HGSOC biopsies. The proposed DSS consists of a double-step feature selection and a decision tree, with the resulting output consisting of a combination of three highly discriminating proteins: TOP1, PDIA4, and OGN, that could be of interest for further clinical and experimental validation. Furthermore, we took advantage of the ranked list of proteins generated during the feature selection steps to perform a pathway analysis to provide a snapshot of the main deregulated pathways of HGSOC. The datasets used for this study are available in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data portal (https://cptac-data-portal.georgetown.edu/).

Predicting Diagnostic Potential of Cathepsin in Epithelial Ovarian Cancer: A Design Validated by Computational, Biophysical and Electrochemical Data

Background: Epithelial ovarian cancer remains one of the leading variants of gynecological cancer with a high mortality rate. Feasibility and technical competence for screening and detection of epithelial ovarian cancer remain a major obstacle and the development of point of care diagnostics (POCD) may offer a simple solution for monitoring its progression. Cathepsins have been implicated as biomarkers for cancer progression and metastasis; being a protease, it has an inherent tendency to interact with Cystatin C, a cysteine protease inhibitor. This interaction was assessed for designing a POCD module. Methods: A combinatorial approach encompassing computational, biophysical and electron-transfer kinetics has been used to assess this protease-inhibitor interaction. Results: Calculations predicted two cathepsin candidates, Cathepsin K and Cathepsin L based on their binding energies and structural alignment and both predictions were confirmed experimentally. Differential pulse voltammetry was used to verify the potency of Cathepsin K and Cathepsin L interaction with Cystatin C and assess the selectivity and sensitivity of their electrochemical interactions. Electrochemical measurements indicated selectivity for both the ligands, but with increasing concentrations, there was a marked difference in the sensitivity of the detection. Conclusions: This work validated the utility of dry-lab integration in the wet-lab technique to generate leads for the design of electrochemical diagnostics for epithelial ovarian cancer.

An open-label phase I dose-escalation study of the safety and pharmacokinetics of DMUC4064A in patients with platinum-resistant ovarian cancer

OBJECTIVES

MUC16 is overexpressed in the majority of human epithelial ovarian cancers (OC). DMUC4064A is a humanized anti-MUC16 monoclonal antibody conjugated to the microtubule-disrupting agent monomethyl auristatin E. This trial assessed the safety, tolerability, pharmacokinetics, and preliminary activity of DMUC4064A in patients with platinum-resistant OC.

METHODS

DMUC4064A was administered once every 3 weeks to patients in 1.0-5.6 mg/kg dose escalation cohorts, followed by cohort expansion at the recommended Phase II dose (RP2D).

RESULTS

Sixty-five patients were enrolled and received a median of 5 cycles (range 1-20) of DMUC4064A. The maximum tolerated dose was not reached; 5.2 mg/kg was the RP2D based on the overall tolerability profile. The most common adverse events were fatigue, nausea, abdominal pain, constipation, blurred vision, diarrhea, and anemia. Sixteen patients (25%) experienced related grade ≥ 3 toxicities. Twenty-six patients (40%) experienced ocular toxicities. The exposure of acMMAE was dose proportional, with a half-life of ~6 days. Sixteen patients (25%) experienced confirmed objective partial response (PR or CR) starting at ≥3.2 mg/kg dose levels, while 23 (35%) patients had best responses of PR or CR. Overall, the clinical benefit rate was 42% (27 patients with a best response [confirmed and unconfirmed] of CR, or PR or SD lasting ≥6 months). Among the 54 patients with high MUC16 immunohistochemistry scores, the clinical benefit rate was 46% (25 patients). Median progression-free survival was 3.9 months overall.

CONCLUSIONS

In this Phase I study, DMUC4064A demonstrated a tolerable safety profile along with encouraging efficacy in the indication of platinum-resistant OC.

Biomarker-based early detection of epithelial ovarian cancer based on a five-protein signature in patient's plasma - a prospective trial

BACKGROUND

Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors.

METHODS

In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses.

RESULTS

Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor.

CONCLUSIONS

The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort.

TRIAL REGISTRATION

Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.

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.

Recent progress in plasmonic nanoparticle-based biomarker detection and cytometry for the study of central nervous system disorders

Neurological disorders affect hundreds of millions of people around the world, are often life-threatening, untreatable, and can result in debilitating symptoms. The high prevalence of these disorders, which feature biochemical or structural abnormalities in neuronal systems, has spurned innovations in both rapid and early detection to assist in the selection of appropriate treatment strategies to improve the patients' quality of life. Plasmonic nanoparticles (PNPs), a versatile and promising class of nanomaterials, are widely utilized in numerous imaging techniques, drug delivery systems, and biomarker detection methods. Recently, PNP-based nanoprobes have attracted considerable attention for the early diagnosis of neurological disorders. Gold nanoparticles (AuNPs), with high local surface plasmon resonance (LSPR) signals, have been particularly well exploited as probes for dynamic biomarker detection, with quantification sensitivity demonstrated down to the single-molecule level. In this review, we will discuss the possibilities of PNPs in the methodological development for rapid neurological disease identification. In addition, we will also describe a new digital cytometry method that combines dark-field imaging and machine learning for precise biomarker enumeration on single cells. The aim of this review is to attract researchers working on the future development of new plasmonic nanoprobe-based strategies for the diagnosis of neurological disorders.

Functional Micro-/Nanomaterials for Multiplexed Biodetection

When analyzing biological phenomena and processes, multiplexed biodetection has many advantages over single-factor biodetection and is highly relevant to both human health issues and advancements in the life sciences. However, many key problems with current multiplexed biodetection strategies remain unresolved. Herein, the main issues are analyzed and summarized: 1) generating sufficient signal to label targets, 2) improving the signal-to-noise ratio to ensure total detection sensitivity, and 3) simplifying the detection process to reduce the time and labor costs of multiple target detection. Then, available solutions made possible by designing and controlling the properties of micro- and nanomaterials are introduced. The aim is to emphasize the role that micro-/nanomaterials can play in the improvement of multiplexed biodetection strategies. Through analyzing existing problems, introducing state-of-the-art developments regarding relevant materials, and discussing future directions of the field, it is hopeful to help promote necessary developments in multiplexed biodetection and associated scientific research.

The evolving role of MUC16 (CA125) in the transformation of ovarian cells and the progression of neoplasia

MUC16 (the cancer antigen CA125) is the most commonly used serum biomarker in epithelial ovarian cancer, with increasing levels reflecting disease progression. It is a transmembrane glycoprotein with multiple isoforms, undergoing significant changes through the metastatic process. Aberrant glycosylation and cleavage with overexpression of a small membrane-bound fragment consist MUC16-related mechanisms that enhance malignant potential. Even MUC16 knockdown can induce an aggressive phenotype but can also increase susceptibility to chemotherapy. Variable MUC16 functions help ovarian cancer cells avoid immune cytotoxicity, survive inside ascites and form metastases. This review provides a comprehensive insight into MUC16 transformations and interactions, with description of activated oncogenic signalling pathways, and adds new elements on the role of its differential glycosylation. By following the journey of the molecule from pre-malignant states to advanced stages of disease it demonstrates its behaviour, in relation to the phenotypic shifts and progression of ovarian cancer. Additionally, it presents proposed differences of MUC16 structure in normal/benign conditions and epithelial ovarian malignancy.

A novel decision tree model based on chromosome imbalances in cell-free DNA and CA-125 in the differential diagnosis of ovarian cancer

OBJECTIVE

CA-125 is widely used as biomarker of ovarian cancer. However, CA-125 suffers low accuracy. We developed a hybrid analytical model, the Ovarian Cancer Decision Tree (OCDT), employing a two-layer decision tree, which considers genetic alteration information from cell-free DNA along with CA-125 value to distinguish malignant tumors from benign tumors.

METHODS

We consider major copy number alterations at whole chromosome and chromosome-arm level as the main feature of our detection model. Fifty-eight patients diagnosed with malignant tumors, 66 with borderline tumors, and 10 with benign tumors were enrolled.

RESULTS

Genetic analysis revealed significant arm-level imbalances in most malignant tumors, especially in high-grade serous cancers in which 12 chromosome arms with significant aneuploidy (P<0.01) were identified, including 7 arms with significant gains and 5 with significant losses. The area under receiver operating characteristic curve (AUC) was 0.8985 for copy number variations analysis, compared to 0.8751 of CA125. The OCDT was generated with a cancerous score (CScore) threshold of 5.18 for the first level, and a CA-125 value of 103.1 for the second level. Our most optimized OCDT model achieved an AUC of 0.975.

CONCLUSIONS

The results suggested that genetic variations extracted from cfDNA can be combined with CA-125, and together improved the differential diagnosis of malignant from benign ovarian tumors. The model would aid in the pre-operative assessment of women with adnexal masses. Future clinical trials need to be conducted to further evaluate the value of CScore in clinical settings and search for the optimal threshold for malignancy detection.

The prognostic and diagnostic potential of kallikrein-related peptidases in ovarian cancer

Introduction: Ovarian cancer is one of the deadliest malignancies among women worldwide. The lack of early diagnostic markers fuels an unfavorable prognosis as most patients are at an advanced stage when the disease is diagnosed for the first time. The role of the kallikrein-related peptidase (KLK) family in ovarian cancer progression and prognosis has been thoroughly investigated in various studies. Most of these peptidases are upregulated in ovarian cancer tissue compared to normal ovarian tissue and their expression is linked to overall and progression-free survival (OS/PFS). In this review, we address the clinical relevance of KLKs in ovarian cancer and their diagnostic potential.Areas covered: This review covers the expression and regulation of KLKs in ovarian cancer with focus on the prognostic and diagnostic potential, especially in liquid biopsies.Expert opinion: In ovarian cancer, several kallikrein-related peptidases are markedly expressed in a tissue-specific manner. Tumor-derived protease secretion results in elevated levels in serum and ascites. KLKs may thus serve as potential biomarkers alone or in combination with other serum tumor markers, such as Cancer Antigen 125 (CA125), for early detection and assessment of the prognosis of ovarian cancer patients.

A high-performance microfluidic detection platform to conduct a novel multiple-biomarker panel for ovarian cancer screening

Ovarian cancer is an important leading cause of cancer-related deaths among females, and a single biomarker does not have the sensitivity and specificity required for an effective ovarian cancer screening. Herein, we investigate a high-performance microfluidic detection platform to conduct a novel panel of multiple biomarkers for the early detection of ovarian carcinoma, which include CA125, HE4, OPN, MSLN, Hsp70, CA153, AFP, IL-6, and IL-8 using a microfluidic chip. High-throughput microfluidic chips and graphene oxide-assembled substrate are used to microprint repeatable capture antibody arrays and conduct multiple biomarkers in microscale volume samples. The proposed microfluidic platform achieves an ultralow detection limit of ∼1 pg mL⁻¹ and 0.01 U mL⁻¹ with excellent detection selectivity and a short detection time of 30 min. The analysis of serum biomarkers in 18 ovarian cancer patients and 4 healthy persons indicates a clear subgroup sorting between the high-grade serous ovarian carcinoma, borderline, and benign tumor patients, and healthy persons. The proposed detection platform and the biomarker panel are promising to conduct an early detection of ovarian cancer.

A high-performance microfluidic detection platform is developed to conduct a novel panel of multiple biomarkers for the early detection of ovarian carcinoma, which is promising for the early detection of ovarian cancer.

CA125 and Ovarian Cancer: A Comprehensive Review

Simple Summary

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

Abstract

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

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.

Plasmonic Nanoparticle-Based Digital Cytometry to Quantify MUC16 Binding on the Surface of Leukocytes in Ovarian Cancer

Although levels of the circulating ovarian cancer marker (CA125) can distinguish ovarian masses that are likely to be malignant and correlate with severity of disease, serum CA125 has not proved useful in general population screening. Recently, cell culture studies have indicated that MUC16 may bind to the Siglec-9 receptor on natural killer (NK) cells where it downregulates the cytotoxicity of NK cells, allowing ovarian cancer cells to evade immune surveillance. We present evidence that the presence of MUC16 can be locally visualized and imaged on the surface of peripheral blood mononuclear cells (PBMCs) in ovarian cancer via a novel "digital" cytometry technique that incorporates: (i) OC125 monoclonal antibody-conjugated gold nanoparticles as optical nanoprobes, (ii) a high contrast dark-field microscopy system to detect PBMC-bound gold nanoparticles, and (iii) a computational algorithm for automatic counting of these nanoparticles to estimate the quantity of surface-bound MUC16. The quantitative detection of our technique was successfully demonstrated by discriminating clones of the ovarian cancer cell line, OVCAR3, based on low, intermediate, and high expression levels of MUC16. Additionally, PBMC surface-bound MUC16 was tracked in an ovarian cancer patient over a 17 month period; the results suggest that the binding of MUC16 on the surface of immune cells may play an early indicator for recurrent metastasis 6 months before computational tomography-based clinical diagnosis. We also demonstrate that the levels of surface-bound MUC16 on PBMCs from five ovarian cancer patients were greater than those from five healthy controls.

Concurrence of ovarian cancer and dermatomyositis: a propensity score analysis

OBJECTIVE

To analyze the clinical characteristics, prognosis and parallel clinical course of ovarian cancer (OC) and dermatomyositis (DM).

METHODS

The medical records of 23 consecutive patients who were diagnosed with OC and DM and were treated at Peking Union Medical College Hospital (PUMCH) between 2002 and 2017 were reviewed. Propensity score matching method was used to match control group (OC patients without DM) at a ratio of 1:5. The correlation between OC and DM was measured using the Pearson correlation scatter plot and Pearson's r. Kaplan-Meier survival analysis and Cox proportional hazard regression analysis were performed to evaluate the prognostic factors.

RESULTS

After matching, 23 patients who have the concurrence of OC and DM (DM group) and 115 patients diagnosed with OC alone (No DM group) were included. The 5-year overall survival rates (71.6% vs. 51.8%, p=0.020) and 5-year progression-free survival (30.5% vs. 0%, p=0.018) were poorer in DM group. Correlation between serum cancer antigen 125 (CA 125) and creatine kinase (CK) level was observed in 12 patients. The time between OC and DM diagnosis is significant through univariable analysis (p=0.021) but not in multivariable analysis in patients who have the concurrence of OC and DM.

CONCLUSION

The concurrence of OC and DM as a paraneoplastic syndrome is rare and has a poor prognosis. The risk for patients diagnosed with DM is highest within 3 years before or after OC diagnosis. A correlation and a parallel clinical course exist between these 2 diseases.

Co-Expression of Mesothelin and CA125 Is Associated with the Poor Prognosis of Endometrial Serous Carcinoma and Mixed Carcinomas Including Serous Carcinoma

The aim of this study was to investigate the association between the clinicopathologic factors and either expression or co-expression of mesothelin and cancer antigen (CA) 125 in endometrial serous carcinoma and mixed carcinomas including serous carcinoma. Between 1990 and 2017, patients with endometrial serous carcinoma and mixed carcinoma including serous carcinoma treated by total hysterectomy and bilateral salpingo-oophorectomy at our hospital were identified. The association between either expression or co-expression of mesothelin and CA125 was evaluated by immunochemical analysis and the clinico-pathological features were retrospectively examined. Among the 40 patients included, 19, 31, and 18 patients exhibited single positive mesothelin, single positive CA125, and positive co-expression, respectively. The expression of mesothelin and CA125 was observed to be positively associated (p = 0.021). There was no significant association of age and FIGO stage with individual mesothelin or CA125 expression or their co-expression. Overall survival (OS), but not progression-free survivals (PFS), of only mesothelin-positive patients was worse (p = 0.024). Hence, OS and PFS of patients with positive co-expression were worse (PFS: p = 0.043, OS: p = 0.012). In multivariate analysis, single mesothelin expression and single CA125 expression did not lead to worse prognosis. However, positive co-expression was the worst prognostic factor for OS (hazard ratio: 3.32, p = 0.039). Co-expression of mesothelin and CA125 may accurately predict OS in endometrial serous carcinoma and mixed carcinomas including serous carcinoma. Further studies should examine this relationship.

Clinical significance of CD38 and CD101 expression in PD-1+CD8+ T cells in patients with epithelial ovarian cancer

Previous studies using mouse liver tumor models have indicated that coexpression of CD38 and CD101 in programmed cell death-1 (PD-1)⁺CD8⁺ T cells may reflect fixed dysregulation of CD8⁺ T cells and thus indicate a poor response to anti-PD-1 immunotherapy. However, whether CD38 and CD101 expression in PD-1⁺CD8⁺ T cells can predict the clinical status and efficacy of chemotherapy for various cancer types, including ovarian cancer (OC), remains unclear. In the present study, peripheral blood mononuclear cells (PBMCs) were obtained by Ficoll-Hypaque gradient centrifugation from 96 fresh samples from healthy adult volunteers and patients with epithelial OC, aged 55.21±9.91 years. Additionally, tumor-infiltrating lymphocytes (TILs) were separated using a combination of mechanical, chemical and enzymatic digestion from fresh surgically removed tumor tissues from 15 patients with epithelial OC. The expression of CD38 and CD101 in PD-1⁺CD8⁺ T cells or TILs was detected by flow cytometry or immunofluorescence (IF) staining, respectively. The association between the level of CD38/CD101 expression and clinicopathological parameters or postoperative chemotherapy in patients with OC was statistically analyzed. The levels of CD38/CD101-coexpressing PD-1⁺CD8⁺ T cells were significantly increased in PBMCs and TILs of patients with OC compared with those of healthy volunteers. The frequency of PD-1⁺CD38⁺CD101⁺CD8⁺ T cells among the total PD-1⁺CD8⁺ T cell subpopulation was negatively associated with clinical stage, lymph node metastasis and postoperative chemotherapy prognosis in patients with OC. Furthermore, IF staining confirmed colocalization of CD38 and CD101 on the majority of TILs in OC tissues. Thus, the present study suggests that coexpression of CD38 and CD101 in peripheral PD-1⁺CD8⁺ T cells and TILs may serve as a new indicator for diagnosis and treatment efficacy in patients with epithelial OC.

Integrating Artificial Intelligence and Nanotechnology for Precision Cancer Medicine

Artificial intelligence (AI) and nanotechnology are two fields that are instrumental in realizing the goal of precision medicine-tailoring the best treatment for each cancer patient. Recent conversion between these two fields is enabling better patient data acquisition and improved design of nanomaterials for precision cancer medicine. Diagnostic nanomaterials are used to assemble a patient-specific disease profile, which is then leveraged, through a set of therapeutic nanotechnologies, to improve the treatment outcome. However, high intratumor and interpatient heterogeneities make the rational design of diagnostic and therapeutic platforms, and analysis of their output, extremely difficult. Integration of AI approaches can bridge this gap, using pattern analysis and classification algorithms for improved diagnostic and therapeutic accuracy. Nanomedicine design also benefits from the application of AI, by optimizing material properties according to predicted interactions with the target drug, biological fluids, immune system, vasculature, and cell membranes, all affecting therapeutic efficacy. Here, fundamental concepts in AI are described and the contributions and promise of nanotechnology coupled with AI to the future of precision cancer medicine are reviewed.

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

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

Diagnostic performance of HE4 and ROMA among Chinese women

OBJECTIVE

Human epididymis protein 4 (HE4) has been suggested as a new biomarker for the detection of ovarian cancer. Because there are few reports on HE4 in terms of ovarian cancer diagnosis in the Chinese population, we evaluated the diagnostic performances of HE4 and the ROMA in Chinese women with pelvic masses.

METHODS

The serum concentrations of CA 125 and HE4 in 318 Chinese women with pelvic masses (39 of which were ovarian cancers) were determined.

RESULTS

For the discrimination of benign gynecological diseases from ovarian cancer, the sensitivity and specificity values were 87.2% and 75.8% for the ROMA and 51.3% and 97.3% for HE4. The ROMA also showed higher sensitivity than HE4 in both the early and advanced stages. In the ROC curve analysis, the AUC values for ROMA, HE4 and CA 125 were 0.927, 0.907 and 0.785, respectively.

CONCLUSIONS

As a new tumor marker, HE4 shows high specificity and efficacy in the Chinese population, while the ROMA that combines HE4 and CA 125 shows high sensitivity and a high Youden's index. These markers should be extended to China since they have good diagnostic performances.

Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives

Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.

Osteopontin, Macrophage Migration Inhibitory Factor and Anti-Interleukin-8 Autoantibodies Complement CA125 for Detection of Early Stage Ovarian Cancer

Early detection of ovarian cancer promises to reduce mortality. While serum CA125 can detect more than 60% of patients with early stage (I–II) disease, greater sensitivity might be observed with a panel of biomarkers. Ten protein antigens and 12 autoantibody biomarkers were measured in sera from 76 patients with early stage (I–II), 44 patients with late stage (III–IV) ovarian cancer and 200 healthy participants in the normal risk ovarian cancer screening study. A four-biomarker panel (CA125, osteopontin (OPN), macrophage inhibitory factor (MIF), and anti-IL-8 autoantibodies) detected 82% of early stage cancers compared to 65% with CA125 alone. In early stage subjects the area under the receiver operating characteristic curve (AUC) for the panel (0.985) was significantly greater (p < 0.001) than the AUC for CA125 alone (0.885). Assaying an independent validation set of sera from 71 early stage ovarian cancer patients, 45 late stage patients and 131 healthy women, AUC in early stage disease was improved from 0.947 with CA125 alone to 0.974 with the four-biomarker panel (p = 0.015). Consequently, OPN, MIF and IL-8 autoantibodies can be used in combination with CA125 to distinguish ovarian cancer patients from healthy controls with high sensitivity. Osteopontin appears to be a robust biomarker that deserves further evaluation in combination with CA125.

DNA aptamers from whole-serum SELEX as new diagnostic agents against gastric cancer

Gastric cancer is still among the leading causes of cancer deaths worldwide. Despite the improvements in diagnostic methods, the status of early detection has not been achieved so far. Early diagnosis of gastric cancer may significantly improve the cure rate of patients. Therefore, a new diagnostic method is needed. In this study, subtractive SELEX was performed to screen gastric cancer serum-specific DNA aptamers by using gastric cancer serum and normal serum as the target and negative serum, respectively. Four highly specific aptamers generated for gastric cancer serum, Seq-3, Seq-6, Seq-19 and Seq-54, were developed using whole-serum subtractive SELEX technology with K_d of 128 ± 26.3 nM, 149 ± 23.6 nM, 232 ± 44.2 nM, 202 ± 25.6 nM, respectively. These generated aptamers showed higher specificities toward their target serum by differentiating normal serum but closely related other cancer serums. The selected four high affinity DNA aptamers were further applied to the development based on qPCR method for the early detection of gastric cancer. In addition, we performed MALDI-TOF MS followed by secondary peptide sequencing MS analysis for the identification of the aptamer binding proteins. Among these potential biomarkers, APOA1, APOA4, PARD3, Importin subunit alpha-1 showed a relatively high score probability. Therefore, these four ssDNA aptamers generated in our study could be a promising molecular probe for gastric cancer diagnosis.

Gastric cancer is still among the leading causes of cancer deaths worldwide.

Quantitative assessment of serum heat shock protein 27 for the diagnosis of epithelial ovarian cancer using targeted proteomics coupled with immunoaffinity enrichment

BACKGROUND

Heat shock protein 27 (HSP27) may take part in the epithelial ovarian cancer (EOC) malignant process because it is elevated in the serum of EOC patients, suggesting that HSP27 may serve as an EOC biomarker to complement the standard serum carbohydrate antigen 125 (CA125) test. Thus, accurate quantification of serum HSP27 would assist the diagnosis of EOC.

METHODS

Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted proteomics coupled with an immunoaffinity enrichment assay was developed and validated to monitor HSP27 concentrations in serum.

RESULTS

Tryptic peptide 80QLSSGVSEIR89 was selected as a surrogate analyte for quantification, and an immuno-depleted serum extract was used as a surrogate matrix. Immunoaffinity enrichment was effective for protein enrichment and sensitivity enhancement, and the resulting LOQ was 500 pg/ml (>10-fold increase). Then, serum HSP27 concentrations in EOC patients, benign ovarian tumors patients and healthy volunteers were accurately determined to be 4.95 ± 0.37 ng/ml, 2.98 ± 0.16 ng/ml and 2.82 ± 0.15 ng/ml, respectively, suggesting that the EOC samples had significantly higher concentrations of HSP27 than a sample from benign ovarian tumor patients. The experimental values for the samples were compared with those obtained from enzyme-linked immune sorbent assays (ELISAs). The ROC curve analysis showed that the combined area under the curve (AUC) for CA125 and HSP27 was 0.88, which is significantly superior to that of CA125 alone.

CONCLUSIONS

Targeted proteomics coupled with immunoaffinity enrichment may provide more accurate quantification of low-abundant proteins.

A multicenter clinical trial validating the performance of HE4, CA125, risk of ovarian malignancy algorithm and risk of malignancy index

OBJECTIVE

To validate, in a multicenter clinical trial, the performance of biomarkers and algorithms for differential diagnosis in a population of women diagnosed with an unknown ovarian cyst or pelvic tumor.

METHODS

Six hospitals in Western Sweden consecutively enrolled 638 women from September 2013 to February 2016. Serum, transvaginal ultrasound data, and basic patient characteristics were collected preoperatively. Biomarker levels, risk of malignancy algorithm (ROMA), and risk of malignancy index (RMI) were calculated and compared with the final pathology report.

RESULTS

Our sample of 638 patients had 445 benign, 31 borderline, and 162 malignant tumors recorded, and the overall incidence of epithelial ovarian cancer was 21%. In postmenopausal women, RMI (>200), ROMA (≥29.9), CA125 (>35 U/mL), and HE4 (>140 pmol/L) showed sensitivity at 89%, 91%, 92%, and 72%, respectively, and specificity at 80%, 77%, 80%, and 92%. In premenopausal women, sensitivity of RMI, ROMA (≥11.6), CA125, and HE4 (>70 pmol/L) was 87%, 87%, 96%, and 83%, respectively, and specificity was 90%, 81%, 60%, 91%. Diagnostic accuracy (ROC AUC) of RMI and ROMA in postmenopausal women was 0.85 and 0.84, and in premenopausal women, 0.90 and 0.81.

CONCLUSION

Our results suggest that CA125 is superior to HE4 as a biomarker to identify women with ovarian cancer. HE4 more correctly identifies benign lesions, which may help in differential diagnoses to guide the level of care and decrease overtreatment. This study confirms prior results from single-center studies and suggests the implementation of HE4 measurement in daily practice.

Diagnostic performance of CA 125, HE4, and risk of Ovarian Malignancy Algorithm for ovarian cancer

OBJECTIVE

We evaluated the diagnostic performance of CA 125, HE4, and ROMA for ovarian cancer in Koreans and set optimal cutoffs.

METHOD

Serum levels of HE4 and CA 125 and the ROMA score were determined in 762 patients with benign gynecological disease and 70 with ovarian cancer. Receiver operating characteristic curves were constructed to calculate the areas under the curve (AUC). CA 125, HE4, and ROMA exhibiting maximum Youden index were determined, respectively, as the optimal cutoffs, and sensitivity and specificity were evaluated by applying those cutoffs.

RESULTS

In benign diseases, CA 125 significantly increased in patients with uterine myoma, adenomyosis, endometrial pathology, or endometriosis, but HE4 only increased in patients with adenomyosis. For the diagnosis of ovarian cancer, the combination of CA 125, HE4, and age showed the highest AUC value of 0.892 in the premenopausal group, and ROMA demonstrated the best diagnostic performance, with an AUC of 0.935 in postmenopausal patients. When the optimal cutoff values for CA 125 and HE4 were applied, the sensitivities of CA 125, HE4, and ROMA in premenopausal women were all the same at 0.714, while the specificities were 0.841, 0.974, and 0.972, respectively. In the postmenopausal group, the sensitivities of these markers were 0.857, 0.804, and 0.929, and the specificities were 0.836, 0.887, and 0.800, respectively.

CONCLUSION

Although all markers demonstrated good diagnostic performance, they varied depending on the pathologic types of benign diseases and ovarian cancer. For accurate diagnosis of ovarian cancer, CA 125, HE4, and ROMA should be used complementarily.

Influence of CA125, platelet count and neutrophil to lymphocyte ratio on the immune system of ovarian cancer patients

OBJECTIVE

The effect of CA125, neutrophil to lymphocyte ratio (NLR) and thrombocytosis on survival has been studied in ovarian cancer. This study explores the link between these variables and serum markers of ovarian cancer patients, such as signaling proteins and cytokines.

METHODS

Serum samples of 39 patients with high-grade serous ovarian cancer (HGSOC) were collected at diagnosis and were retrospectively analysed for clinical characteristics, clinical parameters (NLR, CA125, platelet count) and immune profile [IL-4 (interleukin), IL-10, IL-13, IL-17, transforming growth factor-β, Arginase-1, Interferon gamma), vascular endothelial growth factor (VEGF), galectin-1 and chemokine (C-C) motif ligand 2.

RESULTS

CA125 correlates negatively with VEGF (p = 0.02) and if CA125 rises above 500 kU/L, IL-10 is significantly increased (p = 0.01). NLR > 6 (p < 0.01) was significantly correlated with decreased overall survival. Thrombocytosis was significantly correlated with IL-10 (p < 0.01) and a platelet count > 400 × 10⁹/l led to an improvement in progression free survival (p < 0.01).

CONCLUSIONS

A correlation, at the time of diagnosis, of HGSOC between CA125, NLR and thrombocytes and an immunosuppressive cytokine-profile in serum is shown, and correlates with survival.

Prognostic value of serum and tissue HE4 expression in ovarian cancer: a systematic review with meta-analysis of 90 studies

INTRODUCTION

Ovarian cancer (OC) is one of the leading causes of cancer-related death in women. Accumulating evidence showed an evolving role of HE4 in monitoring the progression and prognosis of OC but without a comprehensive analysis for prognosis and survival data. Areas covered: The present meta-analysis aims to explore the association of HE4 with survival and the clinicopathological features of OC patients. PubMed, Embase, Web of Science and the China National Knowledge Infrastructure (CNKI) were searched for relevant studies regarding the role of both serum and tissue HE4 expression in ovarian cancer. Expert commentary: HE4 has been proposed as the most promising biomarker that may complement the CA125 expression and has been approved by the FDA in monitoring the follow-up and relapse of OC patients. Our results are in accordance with the most recent evidence suggesting its important role in the prognostic surveillance of OC and a better performance in the early prediction of OC recurrence than CA125.

Improving cancer detection through combinations of cancer and immune biomarkers: a modelling approach

Background

Early cancer diagnosis is one of the most important challenges of cancer research, since in many cancers it can lead to cure for patients with early stage diseases. For epithelial ovarian cancer (which is the leading cause of death among gynaecologic malignancies) the classical detection approach is based on measurements of CA-125 biomarker. However, the poor sensitivity and specificity of this biomarker impacts the detection of early-stage cancers.

Methods

Here we use a computational approach to investigate the effect of combining multiple biomarkers for ovarian cancer (e.g., CA-125 and IL-7), to improve early cancer detection.

Results

We show that this combined biomarkers approach could lead indeed to earlier cancer detection. However, the immune response (which influences the level of secreted IL-7 biomarker) plays an important role in improving and/or delaying cancer detection. Moreover, the detection level of IL-7 immune biomarker could be in a range that would not allow to distinguish between a healthy state and a cancerous state. In this case, the construction of solution diagrams in the space generated by the IL-7 and CA-125 biomarkers could allow us predict the long-term evolution of cancer biomarkers, thus allowing us to make predictions on cancer detection times.

Conclusions

Combining cancer and immune biomarkers could improve cancer detection times, and any predictions that could be made (at least through the use of CA-125/IL-7 biomarkers) are patient specific.

Screening for ovarian cancer: imaging challenges and opportunities for improvement

The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) recently reported a reduction in the average overall mortality among ovarian cancer patients screened with an annual sequential, multimodal strategy that tracked biomarker CA125 over time, where increasing serum CA125 levels prompted ultrasound. However, multiple cases were documented wherein serum CA125 levels were rising, but ultrasound screens were normal, thus delaying surgical intervention. A significant factor which could contribute to false negatives is that many aggressive ovarian cancers are believed to arise from epithelial cells on the fimbriae of the fallopian tubes, which are not readily imaged. Moreover, because only a fraction of metastatic tumors may reach a sonographically-detectable size before they metastasize, annual screening with ultrasound may fail to detect a large fraction of early-stage ovarian cancers. The ability to detect ovarian carcinomas before they metastasize is critical and future efforts towards improving screening should focus on identifying unique features specific to aggressive, early-stage tumors, as well as improving imaging sensitivity to allow for detection of tubal lesions. Implementation of a three-stage multimodal screening strategy in which a third modality is employed in cases where the first-line blood-based assay is positive and the second-line ultrasound exam is negative may also prove fruitful in detecting early-stage cases missed by ultrasound.