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

Applications of Pyrrole and Pyridine-based Heterocycles in Cancer Diagnosis and Treatment

BACKGROUND

The escalation of cancer worldwide is one of the major causes of economy burden and loss of human resources. According to the American Cancer Society, there will be 1,958,310 new cancer cases and 609,820 projected cancer deaths in 2023 in the United States. It is projected that by 2040, the burden of global cancer is expected to rise to 29.5 million per year, causing a death toll of 16.4 million. The hemostasis regulation by cellular protein synthesis and their targeted degradation is required for normal cell growth. The imbalance in hemostasis causes unbridled growth in cells and results in cancer. The DNA of cells needs to be targeted by chemotherapeutic agents for cancer treatment, but at the same time, their efficacy and toxicity also need to be considered for successful treatment.

OBJECTIVE

The objective of this study is to review the published work on pyrrole and pyridine, which have been prominent in the diagnosis and possess anticancer activity, to obtain some novel lead molecules of improved cancer therapeutic.

METHODS

A literature search was carried out using different search engines, like Sci-finder, Elsevier, ScienceDirect, RSC etc., for small molecules based on pyrrole and pyridine helpful in diagnosis and inducing apoptosis in cancer cells. The research findings on the application of these compounds from 2018-2023 were reviewed on a variety of cell lines, such as breast cancer, liver cancer, epithelial cancer, etc. Results: In this review, the published small molecules, pyrrole and pyridine and their derivatives, which have roles in the diagnosis and treatment of cancers, were discussed to provide some insight into the structural features responsible for diagnosis and treatment. The analogues with the chromeno-furo-pyridine skeleton showed the highest anticancer activity against breast cancer. The compound 5-amino-N-(1-(pyridin-4- yl)ethylidene)-1H-pyrazole-4-carbohydrazides was highly potent against HEPG2 cancer cell. Redaporfin is used for the treatment of cholangiocarcinoma, biliary tract cancer, cisplatin-resistant head and neck squamous cell carcinoma, and pigmentation melanoma, and it is in clinical trials for phase II. These structural features present a high potential for designing novel anticancer agents for diagnosis and drug development.

CONCLUSION

Therefore, the N- and C-substituted pyrrole and pyridine-based novel privileged small Nheterocyclic scaffolds are potential molecules used in the diagnosis and treatment of cancer. This review discusses the reports on the synthesis of such molecules during 2018-2023. The review mainly discusses various diagnostic techniques for cancer, which employ pyrrole and pyridine heterocyclic scaffolds. Furthermore, the anticancer activity of N- and C-substituted pyrrole and pyridine-based scaffolds has been described, which works against different cancer cell lines, such as MCF-7, A549, A2780, HepG2, MDA-MB-231, K562, HT- 29, Caco-2 cells, Hela, Huh-7, WSU-DLCL2, HCT-116, HBL-100, H23, HCC827, SKOV3, etc. This review will help the researchers to obtain a critical insight into the structural aspects of pyrrole and pyridine-based scaffolds useful in cancer diagnosis as well as treatment and design pathways to develop novel drugs in the future.

Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes

OBJECTIVES

Ovarian cancer is the most lethal gynecological malignancy in developed countries. One of the key associations with the high mortality rate is diagnosis at late stages. This clinical limitation is primarily due to a lack of distinct symptoms and detection at the early stages. The ovarian cancer biomarker, CA125, is mainly effective for identifying serous ovarian carcinomas, leaving a gap in non-serous ovarian cancer detection. Mucin 13 (MUC13) is a transmembrane, glycosylated protein with aberrant expression in malignancies, including ovarian cancer. We explored the potential of MUC13 to complement CA125 as an ovarian cancer biomarker, by evaluating its ability to discriminate serous and non-serous subtypes of ovarian cancer at FIGO stages I-IV from benign conditions.

METHODS

We used our newly developed, high sensitivity ELISA to measure MUC13 protein in a large, well-defined cohort of 389 serum samples from patients with ovarian cancer and benign conditions.

RESULTS

MUC13 and CA125 serum levels were elevated in malignant compared to benign cases (p<0.0001). Receiver-operating characteristic (ROC) curve analysis showed similar area under the curve (AUC) of 0.74 (MUC13) and 0.76 (CA125). MUC13 concentrations were significantly higher in mucinous adenocarcinomas compared to benign controls (p=0.0005), with AUC of 0.80. MUC13 and CA125 showed significant elevation in early-stage cases (stage I-II) in relation to benign controls (p=0.0012 and p=0.014, respectively).

CONCLUSIONS

We report the novel role of MUC13 as a serum ovarian cancer biomarker, where it could complement CA125 for detecting some subtypes of non-serous ovarian carcinoma and early-stage disease.

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.

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).

Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer

BACKGROUND

CA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer.

METHODS

In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer.

RESULTS

Nine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9-18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone.

CONCLUSION

Using pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0-9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.

Validation of Serum Biomarkers That Complement CA19-9 in Detecting Early Pancreatic Cancer Using Electrochemiluminescent-Based Multiplex Immunoassays

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy; its early detection is critical for improving prognosis. Electrochemiluminescent-based multiplex immunoassays were developed with high analytical performance. All proteins were analyzed in sera of patients diagnosed with PDAC (n = 138), benign pancreatic conditions (111), and healthy controls (70). The clinical performance of these markers was evaluated individually or in combination for their complementarity to CA19-9 in detecting early PDAC. Logistic regression modeling including sex and age as cofactors identified a two-marker panel of CA19-9 and CA-125 that significantly improved the performance of CA19-9 alone in discriminating PDAC (AUC: 0.857 vs. 0.766), as well as early stage PDAC (0.805 vs. 0.702) from intraductal papillary mucinous neoplasm (IPMN). At a fixed specificity of 80%, the panel significantly improved sensitivities (78% vs. 41% or 72% vs. 59%). A two-marker panel of HE4 and CEA significantly outperformed CA19-9 in separating IPMN from chronic pancreatitis (0.841 vs. 0.501). The biomarker panels evaluated by assays demonstrated potential complementarity to CA19-9 in detecting early PDAC, warranting additional clinical validation to determine their role in the early detection of pancreatic cancer.

SPME-LC/MS-based serum metabolomic phenotyping for distinguishing ovarian cancer histologic subtypes: a pilot study

Epithelial ovarian cancer (EOC) is the most common cause of death from gynecological cancer. The outcomes of EOC are complicated, as it is often diagnosed late and comprises several heterogenous subtypes. As such, upfront treatment can be highly challenging. Although many significant advances in EOC management have been made over the past several decades, further work must be done to develop early detection tools capable of distinguishing between the various EOC subtypes. In this paper, we present a sophisticated analytical pipeline based on solid-phase microextraction (SPME) and three orthogonal LC/MS acquisition modes that facilitates the comprehensive mapping of a wide range of analytes in serum samples from patients with EOC. PLS-DA multivariate analysis of the metabolomic data was able to provide clear discrimination between all four main EOC subtypes: serous, endometrioid, clear cell, and mucinous carcinomas. The prognostic performance of discriminative metabolites and lipids was confirmed via multivariate receiver operating characteristic (ROC) analysis (AUC value > 88% with 20 features). Further pathway analysis using the top 57 dysregulated metabolic features showed distinct differences in amino acid, lipid, and steroids metabolism among the four EOC subtypes. Thus, metabolomic profiling can serve as a powerful tool for complementing histology in classifying EOC subtypes.

Prognostic value of E-Cadherin and its tumor suppressor role in Saudi women with advanced epithelial ovarian cancer

The extracellular matrix (ECM) disruption and cytoskeleton reorganization are crucial events in tumor proliferation and invasion. E-Cadherin (E-CAD) is a member of cell adhesion molecules involved in cell-cell junctions and ECM stability. The loss of E-CAD expression is associated with cancer progression and metastasis. This retrospective study aimed to assess E-CAD protein expression in ovarian cancer (OC) tissues and to evaluate its prognostic value. Patients and Methods: 143 formalin-fixed and paraffin-embedded (FFPE) blocks of primary advanced stages OC were retrieved and used to construct Tissue microarrays. Automated immunohistochemistry technique was performed to evaluate E-CAD protein expression patterns in OC. Results: E-CAD protein expression was significantly correlated with OC histological subtype (p < 0.0001), while borderline significant correlations were observed with both tumor grade (p = 0.06) and stage (p = 0.07). Interestingly, Kaplan-Meier survival analysis showed that OC patients with membranous E-CAD expression survived longer than those with no E-CAD expression mainly those at advanced stages (p < 0.009). Further in silico analysis confirms the key roles of E-CAD in OC molecular functions. Conclusion: we reported a prognosis value of membranous E-CAD in advanced stage OC patients. Further validation using larger cohorts is recommended to extract clinically relevant outcomes towards better OC management and individualized oncology.

Comparison of two multiplexed technologies for profiling >1,000 serum proteins that may associate with tumor burden

Background: In this pilot study, we perform a preliminary comparison of two targeted multiplex proteomics technologies for discerning serum protein concentration changes that may correlate to tumor burden in ovarian cancer (OC) patients. Methods: Using the proximity extension assay (PEA) and Quantibody® Kiloplex Array (QKA), we measured >1,000 proteins in the pre-surgical and post-surgical serum from nine OC patients (N=18 samples). We expect that proteins that have decreased significantly in the post-surgical serum concentration may correlate to tumor burden in each patient. Duplicate sera from two healthy individuals were used as controls (N=4 samples). We employed in-house ELISAs to measure five proteins with large serum concentration changes in pre- and post-surgical sera, from four of the original nine patients and the two original controls. Results: Both platforms showed a weak correlation with clinical cancer antigen 125 (CA125) data. The two multiplexed platforms showed a significant correlation with each other for >400 overlapping proteins. PEA uncovered 15 proteins, while QKA revealed 11 proteins, with more than a two-fold post-surgical decrease in at least six of the nine patients. Validation using single enzyme-linked immunosorbent assays (ELISAs) showed at least a two-fold post-surgical decrease in serum concentration of the same patients, as indicated by the two multiplex assays. Conclusion: Both methods identified proteins that had significantly decreased in post-surgical serum concentration, as well as recognizing proteins that had been implicated in OC patients. Our findings from a limited sample size suggest that novel targeted proteomics platforms are promising tools for identifying candidate serological tumor-related proteins.  However further studies are essential for the improvement of accuracy and avoidance of false results.

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.

The Repertoire of Glycan Alterations and Glycoproteins in Human Cancers

Cancer as the leading cause of death worldwide has many issues that still need to be addressed. Since the alterations on the glycan compositions or/and structures (i.e., glycosylation, sialylation, and fucosylation) are common features of tumorigenesis, glycomics becomes an emerging field examining the structure and function of glycans. In the past, cancer studies heavily relied on genomics and transcriptomics with relatively little exploration of the glycan alterations and glycoprotein biomarkers among individuals and populations. Since glycosylation of proteins increases their structural complexity by several orders of magnitude, glycome studies resulted in highly dynamic biomarkers that can be evaluated for cancer diagnosis, prognosis, and therapy. Glycome not only integrates our genetic background with past and present environmental factors but also offers a promise of more efficient patient stratification compared with genetic variations. Therefore, studying glycans holds great potential for better diagnostic markers as well as developing more efficient treatment strategies in human cancers. While recent developments in glycomics and associated technologies now offer new possibilities to achieve a high-throughput profiling of glycan diversity, we aim to give an overview of the current status of glycan research and the potential applications of the glycans in the scope of the personalized medicine strategies for cancer.

Field-effect transistor bioassay for ultrasensitive detection of folate receptor 1 by ligand-protein interaction

A miniaturized and integrated bioassay was developed based on molybdenum disulfide (MoS₂) field-effect transistor (FET) functionalized with bovine serum albumin-folic acid (BSA-FA) for monitoring FOLR1. We performed the electrical test of FOLR1 within the range 100 fg/mL to 10 ng/mL, and the limit of detection was 0.057 pg/mL. The ultrahigh sensitivity of the bioassay was realized by ligand-protein interaction between FA and FOLR1, with a ligand-protein binding ratio of 3:1. The formation of FA-FOLR1 was confirmed with ELISA. The binding affinity dissociation constant K_D was 12 ± 6 pg/mL. This device can work well for FOLR1 detection in human serum, which presents its promising application in point-of-care diagnosis. This study supports the future applications of such ligand-protein-based bioassays in the clinical practices. Graphical abstract MoS₂-based FET device for detecting folate receptor 1 (FOLR1) was fabricated. The molecular folic acid as a probe can specifically bound to FOLR1 with a high affinity.

A systematic review and meta-analysis of higher expression of folate receptor alpha (FOLR1) predicts poor cancer prognosis

Folate receptor alpha (FOLR1), a glycosylphosphatidylinositol-linked protein, is a well characterized folate transporter. However, the prognostic power of FOLR1 in cancer remains controversial. We conducted a meta-analysis to assess the prognostic roles of FOLR1 on different cancers. Twelve studies involving 4471 patients were included in this meta-analysis. The pooled analysis indicated that high FOLR1 significantly predicted poor overall survival (OS) (pooled hazard ratio (HR) = 0.78, 95% confidence interval (CI) = 0.64-0.94, p = 0.009) and the disease-free survival (DFS) (HR = 1.25, 95% CI = 1.07-1.47, p = 0.005). Subgroup analyses based on tumour type found that high FOLR1 level was associated with poor OS in breast cancer (HR = 2.66, 95% CI = 1.54-4.59, p = 0.0005) and endometrial carcinoma (HR = 1.30, 95% CI = 1.05-1.61, p = 0.02). However, FOLR1 has relatively weakly correlation with gender, tumour size and chemotherapy. Additionally, overexpression of FOLR1 was correlated with grade, FIGO stage, vital status and nodule status. The present meta-analysis indicated that the high expression of FOLR1 is associated with the poor survival of cancer patients, which is helpful for the clinical decision-making process.

Preclinical evaluation of local prolonged release of paclitaxel from gelatin microspheres for the prevention of recurrence of peritoneal carcinomatosis in advanced ovarian cancer

Patients with advanced ovarian cancer develop recurrence despite initial treatment response to standard treatment of surgery and intravenous/intraperitoneal (IP) chemotherapy, partly due to a limited peritoneal exposure time of chemotherapeutics. Paclitaxel-loaded genipin-crosslinked gelatin microspheres (PTX-GP-MS) are evaluated for the treatment of microscopic peritoneal carcinomatosis and prevention of recurrent disease. The highest drug load (39.2 µg PTX/mg MS) was obtained by immersion of GP-MS in aqueous PTX nanosuspension (PTXnano-GP-MS) instead of ethanolic PTX solution (PTXEtOH-GP-MS). PTX release from PTX-GP-MS was prolonged. PTXnano-GP-MS displayed a more controlled release compared to a biphasic release from PTXEtOH-GP-MS. Anticancer efficacy of IP PTX-GP-MS (PTXEtOH-GP-MS, D = 7.5 mg PTX/kg; PTXnano-GP-MS D = 7.5 and 35 mg PTX/kg), IP nanoparticular albumin-bound PTX (D = 35 mg PTX/kg) and controls (0.9% NaCl, blank GP-MS) was evaluated in a microscopic peritoneal carcinomatosis xenograft mouse model. PTXnano-GP-MS showed superior anticancer efficacy with significant increased survival time, decreased peritoneal carcinomatosis index score and ascites incidence. However, prolonged PTX release over 14 days from PTXnano-GP-MS caused drug-related toxicity in 27% of high-dosed PTXnano-GP-MS-treated mice. Dose simulations for PTXnano-GP-MS demonstrated an optimal survival without drug-induced toxicity in a range of 7.5-15 mg PTX/kg. Low-dosed PTXnano-GP-MS can be a promising IP drug delivery system to prevent recurrent ovarian cancer.

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.

Molecularly imprinted polymer SPE sensor for analysis of CA-125 on serum

Considering the high incidence level and mortality rate of ovarian cancer, particularly among the European female population, the carbohydrate antigen 125 (CA-125) was selected as the protein target for this study for the development of a MIP-based biosensor. This work presents the development of molecular imprinting polymers (MIPs) on gold electrode surface for CA-125 biomarker recognition. The preparation of the CA-125 imprinting was obtained by electropolymerization of pyrrole (Py) monomer in a gold electrode using cyclic voltammetry (CV) in order to obtain highly selective materials with great molecular recognition capability. The quantification of CA-125 biomarker was made through the comparison of two methods: electrochemical (square wave voltammetry -SWV) and optical transduction (surface plasmon resonance -SPR). SWV has been widely used in biological molecules analysis since it is a fast and sensitive technique. In turn, SPR is a non-destructive optical technique that provides high-quality analytical data of CA-125 biomarker interactions with MIP. Several analytical parameters, such as sensitivity, linear response interval, and detection limit were determined to proceed to the performance evaluation of the electrochemical and optical transduction used in the development of the CA-125 biosensor. The biosensor based in the electrochemical transduction was the one that presented the best analytical parameters, yielding a good selectivity and a detection limit (LOD) of 0.01 U/mL, providing a linear concentration range between 0.01 and 500 U/mL. This electrochemical biosensor was selected for the study and it was successfully applied in the CA-125 analysis in artificial serum samples with recovery rates ranging from 91 to 105% with an average relative error of 5.8%.

High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer

Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.

High-throughput assessment of the antibody profile in ovarian cancer ascitic fluids

The identification of effective biomarkers for early diagnosis, prognosis, and response to treatments remains a challenge in ovarian cancer (OC) research. Here, we present an unbiased high-throughput approach to profile ascitic fluid autoantibodies in order to obtain a tumor-specific antigen signature in OC. We first reported the reactivity of immunoglobulins (Igs) purified from OC patient ascites towards two different OC cell lines. Using a discovery set of Igs, we selected tumor-specific antigens from a phage display cDNA library. After biopanning, 700 proteins were expressed as fusion protein and used in protein array to enable large-scale immunoscreening with independent sets of cancer and noncancerous control. Finally, the selected antigens were validated by ELISA. The initial screening identified eight antigenic clones: CREB3, MRPL46, EXOSC10, BCOR, HMGN2, HIP1R, OLFM4, and KIAA1755. These antigens were all validated by ELISA in a study involving ascitic Igs from 153 patients (69 with OC, 34 with other cancers and 50 without cancer), with CREB3 showing the highest sensitivity (86.95%) and specificity (98%). Notably, we were able to identify an association between the tumor-associated (TA) antibody response and the response to a first-line tumor treatment (platinum-based chemotherapy). A stronger association was found by combining three antigens (BCOR, CREB3, and MRLP46) as a single antibody signature. Measurement of an ascitic fluid antibody response to multiple TA antigens may aid in the identification of new prognostic signatures in OC patients and shift attention to new potentially relevant targets.

Multiple biomarker algorithms to predict epithelial ovarian cancer in women with a pelvic mass: Can additional makers improve performance?

INTRODUCTION

Management of a woman with a pelvic mass is complicated by difficulty in discriminating malignant from benign disease. Many serum biomarkers have been examined to determine their sensitivity for detecting malignancy. This study was designed to evaluate if the addition of biomarkers to HE4 and CA125, as used in the Risk of Malignancy Algorithm (ROMA), can improve the detection of EOC.

METHODS

This was an IRB approved, prospective clinical trial examining serum obtained from women diagnosed with a pelvic mass who subsequently underwent surgery. Serum biomarker levels for CA125, HE4, YKL-40, transthyretin, ApoA1, Beta-2-microglobulin, transferrin, and LPA were measured. Logistic regression analysis was performed for various marker combinations, ROC curves were generated, and the area under the curves (AUCs) were determined.

RESULTS

A total of 184 patients met inclusion criteria with a median age of 56 years (Range 20-91). Final pathology revealed there were 103 (56.0%) benign tumors, 4 (2.2%) LMP tumors, 61 EOC (33.1%), 2 (1.1%) non-EOC ovarian cancers, 6 (3.3%) gynecologic cancers with metastasis to the ovary and 8 (4.3%) non-gynecologic cancers with metastasis to the ovary. The combination of HE4 and CA125 (i.e. ROMA) achieved an AUC of 91.2% (95% CI: 86.0-96.4) for the detection of EOC vs benign disease. The combination of CA125, HE4, YKL-40, transthyretin, ApoA1, Beta 2 microglobulin, transferrin, LPA and menopausal status achieved the highest AUC of 94.6% (95% CI: 90.1-99.2) but this combination was not significantly better than the HE4 and CA125 combination alone (p = 0.078).

CONCLUSIONS

The addition of select further serum biomarkers to HE4 and CA125 does not add to the performance of the dual marker combination for the detection of ovarian cancer.

Aberrant Expression of Folate Metabolism Enzymes and Its Diagnosis and Survival Prediction in Ovarian Carcinoma

This study was to validate changes in the levels of folate receptor-α (FOLR1), dihydrofolate reductase (DHFR), and methionine synthase reductase (MTRR) in the tissue of OC patients. The expression of FOLR1, DHFR, and MTRR was evaluated in 80 cases of primary OC, 50 cases of benign ovarian tumors, and 30 normal ovarian tissues. Associations between protein expression and clinicopathological characters were assessed, and diagnostic and prognostic evaluation of FOLR1, DHFR, and MTRR was performed. Results showed that upregulated FOLR1 and MTRR and downregulated DHFR were detected in OC. Patients with abnormality of FOLR1, DHFR, and MTRR tend to have a higher percentage of platinum resistance. Moreover, the areas under receiver operating characteristic curves (AUCs-ROC) for FOLR1, DHFR, and MTRR were 0.723, 0.717, and 0.714, respectively. The combination of FOLR1, DHFR, and MTRR could produce an area of 0.864 under the receiver-operating characteristic curve in distinguishing platinum-resistant patients from platinum-sensitive patients (P < 0.0001). Correlations were present between the expression of FOLR1, DHFR, and MTRR. Furthermore, Kaplan-Meier curves indicated that the patients with overexpressed MTRR had a poorer overall survival time compared to those with low expression (P < 0.05). Thus, folate metabolic enzymes could provide a potential promising biomarker for diagnosis platinum-resistant in OC.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA‐125 and sFR.

Exosomal miR-1290 is a potential biomarker of high-grade serous ovarian carcinoma and can discriminate patients from those with malignancies of other histological types

Background

microRNAs (miRNAs) stably exist in circulating blood encapsulated in extracellular vesicles such as exosomes; therefore, serum miRNAs have the potential to serve as novel cancer biomarkers. New diagnostic markers to detect high grade serous ovarian cancer (HGSOC) are urgently needed. The aim of this study was to identify miRNAs specific to HGSOC and analyze whether serum miRNA can discriminate HGSOC patients from healthy controls or patients with ovarian malignancies of other histological types.

Methods

Exosomes from ovarian cancer cell lines were collected and exosomal miRNAs extracted. miRNA microarray analysis revealed several elevated miRNAs specific to HGSOC. Among these, we focused on miR-1290. Sera from 70 ovarian cancer patients and 13 healthy controls were gathered and its expression levels detected by quantitative real-time polymerase chain reaction.

Results

In HGSOC patients, serum miR-1290 was significantly overexpressed compared to in healthy controls (3.52 fold; P = 0.03), unlike in patients with ovarian cancers of other histological types. The relative expression of miR-1290 was higher in advanced stages of HGSOC than in early stages (4.23 vs. 1.58; P = 0.23). Its expression significantly decreased after operation (5.87 to 1.17; P < 0.01), indicating that this miRNA reflects tumor burden. A receiver operating characteristic curve analysis showed that at the cut-off of 1.20, the sensitivity and specificity were 63% and 85% respectively for discriminating patients with HGSOC (area under the curve [AUC] = 0.71) from healthy controls, and at the cut-off of 1.55, the sensitivity and specificity were 47% and 85% respectively for discriminating patients with HGSOC (AUC = 0.76) from those with malignancies of other histological types.

Conclusions

Serum miR-1290 is significantly elevated in patients with HGSOC and can be used to discriminate these patients from those with malignancies of other histological types; it is a new potential diagnostic biomarker for HGSOC.

Algorithms Used in Ovarian Cancer Detection: A Minireview on Current and Future Applications

BACKGROUND

Ovarian cancer is the 5th most common cause of cancer death among women in the US. Currently, there is no screening algorithm for asymptomatic women that has been shown to lower mortality rates. Screening is currently not recommended and has been shown to increase harm. Epithelial ovarian cancer (EOC) detection is reviewed, with a focus on high-grade serous, clear-cell, and endometrioid histotypes.

CONTENT

A review of current literature surrounding tools used in detection of ovarian cancer will be presented. CA 125, HE4, risk of ovarian cancer algorithm (ROCA), risk of malignancy algorithm (ROMA), risk of malignancy (RMI), OVA1, and future potential biomarkers are reviewed.

SUMMARY

Screening and early identification of EOC is currently managed as a single disease entity. However, recent evidence has shown ovarian cancer varies with relation to cellular origin, pathogenesis, molecular alterations, and prognosis, depending on histotype. There is a clear need for future studies identifying histotype-specific preclinical tumor markers to aid in detection and improvement of survival rates.

Unraveling endometriosis-associated ovarian carcinomas using integrative proteomics

Background: To elucidate potential markers of endometriosis and endometriosis-associated endometrioid and clear cell ovarian carcinomas using mass spectrometry-based proteomics.

Methods: A total of 21 fresh, frozen tissues from patients diagnosed with clear cell carcinoma, endometrioid carcinoma, endometriosis and benign endometrium were subjected to an in-depth liquid chromatography-tandem mass spectrometry analysis on the Q-Exactive Plus. Protein identification and quantification were performed using MaxQuant, while downstream analyses were performed using Perseus and various bioinformatics databases.

Results: Approximately 9000 proteins were identified in total, representing the first in-depth proteomic investigation of endometriosis and its associated cancers. This proteomic data was shown to be biologically sound, with minimal variation within patient cohorts and recapitulation of known markers. While moderate concordance with genomic data was observed, it was shown that such data are limited in their abilities to represent tumours on the protein level and to distinguish tumours from their benign precursors.

Conclusions: The proteomic data suggests that distinct markers may differentiate endometrioid and clear cell carcinoma from endometriosis. These markers may be indicators of pathobiology but will need to be further investigated. Ultimately, this dataset may serve as a basis to unravel the underlying biology of the endometrioid and clear cell cancers with respect to their endometriotic origins.

Diagnostic markers for the detection of ovarian cancer in BRCA1 mutation carriers

Background

Screening for ovarian cancer (OC) in women at high risk consists of a combination of carbohydrate antigen 125 (CA125) and transvaginal ultrasound, despite their low sensitivity and specificity. This could be improved by the combination of several biomarkers, which has been shown in average risk patients but has not been investigated until now in female BRCA mutation carriers.

Methods

Using a multiplex, bead-based, immunoassay system, we analyzed the concentrations of leptin, prolactin, osteopontin, insulin-like growth factor II, macrophage inhibitory factor, CA125 and human epididymis antigen 4 in 26 healthy wild type women, 26 healthy BRCA1 mutation carriers, 28 wildtype OC patients and 26 OC patients with BRCA1 mutation.

Results

Using the ROC analysis, we found a high overall sensitivity of 94.3% in differentiating healthy controls from OC patients with comparable results in the wildtype subgroup (sensitivity 92.8%, AUC = 0.988; p = 5.2e-14) as well as in BRCA1 mutation carriers (sensitivity 95.2%, AUC = 0.978; p = 1.7e-15) at an overall specificity of 92.3%.

The used algorithm also allowed to identify healthy BRCA1 mutation carriers when compared to healthy wildtype women (sensitivity 88.4%, specificity 80.7%, AUC = 0.895; p = 6e-08), while this was less pronounced in patients with OC (sensitivity 66.7%, specificity 67.8%, AUC = 0.724; p = 0.00065).

Conclusion

We have developed an algorithm, which can differentiate between healthy women and OC patients and have for the first time shown, that such an algorithm can also be used in BRCA mutation carriers. To clarify a suggested benefit to the existing early detection program, large prospective trials with mainly early stage OC cases are warranted.

Study of kallikrein-related peptidase 6 (KLK6) and its complex with α1-antitrypsin in biological fluids

BACKGROUND

Human kallikrein-related peptidase 6 (KLK6) is a member of the kallikrein family of serine proteases. KLK6 is synthesized as a preproenzyme, mainly in tissues of the central nervous system (CNS), and secreted as an inactive precursor. Serum KLK6 is a biomarker of unfavorable prognosis for ovarian cancer, but its sensitivity for early detection is relatively low. Differential glycosylation of KLK6 has been identified in ascites fluid obtained from ovarian cancer patients, suggesting the presence of unique KLK6 isoforms in biological samples.

METHODS

In the present study, we applied a two-step enrichment approach for KLK6 in ovarian cancer ascites, followed by mice immunization and production of monoclonal antibodies. Immunoaffinity techniques coupled to mass spectrometric methods were employed for hybridoma screening and target antigen identification.

RESULTS

We found that the main target of the newly-generated monoclonal antibodies target was the serine protease inhibitor α1-antitrypsin (A1AT). Additional experiments confirmed that A1AT is the main inhibitor of KLK6 in biological fluids. One new antibody (24ED138) was chosen to build a hybrid assay for the accurate quantification of the A1AT-KLK6 complex in biological samples. The aforementioned assay was evaluated with serum samples collected from patients with ovarian cancer (n=24) and normal donors (n=16) and showed slight improvement in sensitivity (~12%) compared to the standard in-house KLK6 assay.

CONCLUSIONS

We conclude that KLK6 is present in biological fluids either as free form, or bound to A1AT, and the bound form performs better than total KLK6 as a biomarker of ovarian carcinoma.

Performance of seven criteria to assess CA125 increments among ovarian cancer patients monitored during first-line chemotherapy and the post-therapy follow-up period

Aim:

To investigate seven CA125 criteria to monitor progressive ovarian cancer among patients with stage IC–IV disease.

Materials & methods:

Four criteria were used to asses CA125 increments starting from concentrations ≥35 U/ml and three criteria to asses increments starting from concentrations <35 U/ml.

Results:

A total of 231 patients were allocated to CA125 monitoring. The performances of the CA125 criteria were similar with sensitivities of 30–55%, negative predictive values of 28–46%, positive predictive values of 90–100% and median lead times of 26–87 days.

Conclusion:

The criteria showed low sensitivity and inability to exclude progressive ovarian cancer. The study suggests that CA125 information cannot stand alone but should be considered used in conjunction with other investigative procedures.

Few have validated the CA125 progression criteria proposed by Rustin et al. in 1996 and in 2001. These two criteria were officially recommended by the Gynecological Cancer Intergroup to be incorporated into clinical trials in 2010. Among other criteria, we validated the Gynecological Cancer Intergroup CA125 progression criteria in an ovarian cancer population regarding sensitivity, specificity, positive predictive value and negative predictive value. We found that the criteria had low sensitivity and ability to exclude tumor growth. We believe that the clinical utility of CA125 may be questioned, and there is a need for supplementary markers and alternative assessment criteria.

Towards personalized tumor markers

The cancer biomarker discovery pipeline is progressing slowly. The difficulties of finding novel and effective biomarkers for diagnosis and management of cancer patients are well-known. We speculate that it is unlikely to discover new serological biomarkers characterized by high sensitivity and specificity. This projection is supported by recent findings that cancers are genetically highly heterogeneous. Here, we propose a new way of improving the landscape of cancer biomarker research. There are currently hundreds, if not thousands, of described biomarkers which perform at high specificity (> 90%), but at relatively low sensitivity (< 30%). We call these “rare tumor markers.” Borrowing from the principles of precision medicine, we advocate that among these low sensitivity markers, some may be useful to specific patients. We suggest screening new patients for hundreds to thousands of cancer biomarkers to identify a few that are informative, and then use them clinically. This is similar to what we currently do with genomics to identify personalized therapies. We further suggest that this approach may explain as to why some biomarkers are elevated in only a small group of patients. It is likely that these differences in expression are linked to specific genomic alterations, which could then be found with genomic sequencing.