Early detection biomarkers for ovarian cancer

Stretchable Photonic Crystal-Assisted Glycoprotein Identification for Ovarian Cancer Diagnosis

Photonic crystals with specific wavelengths can realize surface-enhanced excitation and emission intensities of fluorophores and enhance the fluorescence signals of fluorescent molecules. Herein, stretchable photonic crystals with good mechanochromic properties provide continuously adjustable forbidden wavelengths by stretching to change the lattice spacing, with reflectance peaks blue-shifted up to 110 nm to match indicators of different wavelengths and produce differentiated optical enhancement effects. Glycoproteins are significantly identified as clinical markers. However, the wide participation of glycoproteins in various life processes poses enormous complexity and critical challenges for rapid, facile, high-throughput, and accurate clinical analysis or health assessment. In this work, we proposed a stretchable photonic crystal-assisted glycoprotein identification approach for early ovarian cancer diagnosis. Stretchable photonic crystals can provide rich optical information to efficiently identify glycoproteins in complex matrices. A double-indicator fluorescence sensor was designed to respond to the protein trunk and oligosaccharide segment of glycoproteins separately for improved recognition accuracy. Seven typical glycoproteins could be discriminated from proteins, saccharides, or mixture interferents. Clinical ovarian cancer samples for early, intermediate, and advanced ovarian cancer and healthy subjects were verified with 100% accuracy. This strategy of stretchable photonic crystal-assisted glycoprotein identification provides an effective method for accurate, rapid ovarian cancer diagnosis and timely clinical treatment.

Comprehensive DNA methylation profiling by MeDIP-NGS identifies potential genes and pathways for epithelial ovarian cancer

Ovarian cancer, among all gynecologic malignancies, exhibits the highest incidence and mortality rate, primarily because it is often presents with non-specific or no symptoms during its early stages. For the advancement of Ovarian Cancer Diagnosis, it is crucial to identify the potential molecular signatures that could significantly differentiate between healthy and ovarian cancerous tissues and can be used further as a diagnostic biomarker for detecting ovarian cancer. In this study, we investigated the genome-wide methylation patterns in ovarian cancer patients using Methylated DNA Immunoprecipitation (MeDIP-Seq) followed by NGS. Identified differentially methylated regions (DMRs) were further validated by targeted bisulfite sequencing for CpG site-specific methylation profiles. Furthermore, expression validation of six genes by Quantitative Reverse Transcriptase-PCR was also performed. Out of total 120 differentially methylated genes (DMGs), 68 genes were hypermethylated, and 52 were hypomethylated in their promoter region. After analysis, we identified the top 6 hub genes, namely POLR3B, PLXND1, GIGYF2, STK4, BMP2 and CRKL. Interestingly we observed Non-CpG site methylation in the case of POLR3B and CRKL which was statistically significant in discriminating ovarian cancer samples from normal controls. The most significant pathways identified were focal adhesion, the MAPK signaling pathway, and the Ras signaling pathway. Expression analysis of hypermethylated genes was correlated with the downregulation of the genes. POLR3B and GIGYF2 turned out to be the novel genes associated with the carcinogenesis of EOC. Our study demonstrated that methylation profiling through MeDIP-sequencing has effectively identified six potential hub genes and pathways that might exacerbate our understanding of underlying molecular mechanisms of ovarian carcinogenesis.

Recent advances in using folate receptor 1 (FOLR1) for cancer diagnosis and treatment, with an emphasis on cancers that affect women

A glycosylphosphatidylinositol (GPI)-anchored glycoprotein called the folate receptor 1 (FOLR1) facilitates the transportation of folate by mediating receptor-mediated endocytosis in response to ligand binding. While FOLR1 expression is typically restricted to the apical surfaces of the epithelium in the lung, kidney, and choroid plexus in healthy people, it is overexpressed in a number of solid tumours, including high-grade osteosarcoma, breast cancer, ovarian cancer, and non-small cell lung cancer. As a result, FOLR1 has become an attractive target for cancer detection and therapy, particularly for cancers that affect women. A number of methods have been developed to target FOLR1 in cancer therapy, including the development of FOLR1-targeted imaging agents for cancer diagnosis and the use of folate conjugates to deliver cytotoxic agents to cancer cells that overexpress FOLR1. Therefore, we focus on the most recent developments in employing FOLR1 for cancer diagnosis and treatment in this review, particularly with regard to cancers that affect women.

Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers

Photoelectrochemical (PEC) sensing is an emerging technological innovation for monitoring small substances/molecules in biological or non-biological systems. In particular, there has been a surge of interest in developing PEC devices for determining molecules of clinical significance. This is especially the case for molecules that are markers for serious and deadly medical conditions. The increased interest in PEC sensors to monitor such biomarkers can be attributed to the many apparent advantages of the PEC system, including an enhanced measurable signal, high potential for miniaturization, rapid testing, and low cost, amongst others. The growing number of published research reports on the subject calls for a comprehensive review of the various findings. This article is a review of studies on electrochemical (EC) and PEC sensors for ovarian cancer biomarkers in the last seven years (2016-2022). EC sensors were included because PEC is an improved EC; and a comparison of both systems has, expectedly, been carried out in many studies. Specific attention was given to the different markers of ovarian cancer and the EC/PEC sensing platforms developed for their detection/quantification. Relevant articles were sourced from the following databases: Scopus, PubMed Central, Web of Science, Science Direct, Academic Search Complete, EBSCO, CORE, Directory of open Access Journals (DOAJ), Public Library of Science (PLOS), BioMed Central (BMC), Semantic Scholar, Research Gate, SciELO, Wiley Online Library, Elsevier and SpringerLink.

Sensitive Detection of the Human Epididymis Protein-4 (HE4) Ovarian Cancer Biomarker through a Sandwich-Type Immunoassay Method with Laser-Induced Breakdown Spectroscopy

Detection of cancer before the appearance of any symptoms is crucial for successful treatment. Early detection is, however, very challenging, particularly for the types of cancer with few or no symptoms at early stages, such as epithelial ovarian cancer (EOC). Developing a user-friendly method that can detect biomarkers with sufficient selectivity, sensitivity, and reproducibility is a promising approach for overcoming the challenges of early detection of EOC. In this study, we report a sandwich-type microparticle immunoassay for sensitive detection of the HE4 biomarker with laser-induced breakdown spectroscopy. Here, we cross-linked elemental particles to a specific functional group of the targeted biomolecules based on a covalent and non-covalent linking chemistry to improve the sensitivity and selectivity of biomarker detection, in which Fe₃O₄ and SiO₂ microparticles were used to conjugate and purify the antibody-antigen in complex media. Simultaneous detection of Fe and Si from a magnetically purified assay significantly improves the HE4 biomarker's detectability, in which HE4 was detected with a limit of detection of 0.0022 pM. We also determined the coupling ratio between HE4 and silica particles using a silicon calibration curve.

Exosomes as crucial emerging tools for intercellular communication with therapeutic potential in ovarian cancer

More than two-thirds of epithelial ovarian cancer (EOC) patients are diagnosed at advanced stages due to the lack of sensitive biomarkers. Currently, exosomes are intensively investigated as non-invasive cancer diagnostic markers. Exosomes are nanovesicles released in the extracellular milieu with the potential to modulate recipient cells' behavior. EOC cells release many altered exosomal cargoes that exhibit clinical relevance to tumor progression. Exosomes represent powerful therapeutic tools (drug carriers or vaccines), posing a promising option in clinical practice for curing EOC in the near future. In this review, we highlight the importance of exosomes in cell–cell communication, epithelial–mesenchymal transition (EMT), and their potential to serve as diagnostic and prognostic factors, particularly in EOC.

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.

Nanobodies for the Early Detection of Ovarian Cancer

Ovarian cancer ranks fifth in cancer-related deaths among women. Since ovarian cancer patients are often asymptomatic, most patients are diagnosed only at an advanced stage of disease. This results in a 5-year survival rate below 50%, which is in strong contrast to a survival rate as high as 94% if detected and treated at an early stage. Monitoring serum biomarkers offers new possibilities to diagnose ovarian cancer at an early stage. In this study, nanobodies targeting the ovarian cancer biomarkers human epididymis protein 4 (HE4), secretory leukocyte protease inhibitor (SLPI), and progranulin (PGRN) were evaluated regarding their expression levels in bacterial systems, epitope binning, and antigen-binding affinity by enzyme-linked immunosorbent assay and surface plasmon resonance. The selected nanobodies possess strong binding affinities for their cognate antigens (K_D~0.1-10 nM) and therefore have a pronounced potential to detect ovarian cancer at an early stage. Moreover, it is of utmost importance that the limits of detection (LOD) for these biomarkers are in the pM range, implying high specificity and sensitivity, as demonstrated by values in human serum of 37 pM for HE4, 163 pM for SLPI, and 195 pM for PGRN. These nanobody candidates could thus pave the way towards multiplexed biosensors.

Effective Combination Immunotherapy with Oncolytic Adenovirus and Anti-PD-1 for Treatment of Human and Murine Ovarian Cancers

Ovarian cancer (OvCa) is one of the most common gynecological cancers and has the highest mortality in this category. Tumors are often detected late, and unfortunately over 70% of OvCa patients experience relapse after first-line treatments. OvCa has shown low response rates to immune checkpoint inhibitor (ICI) treatments, thus leaving room for improvement. We have shown that oncolytic adenoviral therapy with Ad5/3-E2F-d24-hTNFa-IRES-hIL2 (aka. TILT-123) is promising for single-agent treatment of cancer, but also for sensitizing tumors for T-cell dependent immunotherapy approaches, such as ICI treatments. Therefore, this study set out to determine the effect of inhibition of the immune checkpoint inhibitors (ICI), in the context of TILT-123 therapy of OvCa. We show that simultaneous treatment of patient derived samples with TILT-123 and ICIs anti-PD-1 or anti-PD-L1 efficiently reduced overall viability. The combinations induced T cell activation, T cells expressed activation markers more often, and the treatment caused positive microenvironment changes, measured by flow cytometric assays. Furthermore, in an immunocompetent in vivo C57BL/6NHsda mouse model, tumor growth was hindered, when treated with TILT-123, ICI or both. Taken together, this study provides a rationale for using TILT-123 virotherapy in combination with TILT-123 and immune checkpoint inhibitors together in an ovarian cancer OvCa clinical trial.

Genome-Wide Identification and Validation of Gene Expression Biomarkers in the Diagnosis of Ovarian Serous Cystadenocarcinoma

Simple Summary

Despite ovarian serous adenocarcinoma (OSCA) is a high-incidence type of cancer, limited molecular screening methods are available and the diagnosis mostly occurs at a late stage. The aim of this study is screening the potential of gene expression for identifying OSCA-specific molecular biomarkers for improving diagnosis. A genome-wide survey was performed on high-throughput RNA-sequencing experiments on hundreds ovarian cancer samples and healthy ovarian tissues, providing a number of putative OSCA biomarkers, which were then validated on an independent sample set and using a different RNA-quantification technology. Combinations of gene expression biomarkers were identified, which showed high accuracy in discriminating OSCA tissues from the normal counterpart and from other tumor types. The detected biomarkers can improve the molecular diagnosis of OSCA on tissue samples and are, in principle, translatable to the analysis of liquid biopsies.

Abstract

Ovarian cancer is the second most prevalent gynecologic malignancy, and ovarian serous cystadenocarcinoma (OSCA) is the most common and lethal subtype of ovarian cancer. Current screening methods have strong limits on early detection, and the majority of OSCA patients relapse. In this work, we developed and cross-validated a method for detecting gene expression biomarkers able to discriminate OSCA tissues from healthy ovarian tissues and other cancer types with high accuracy. A preliminary ranking-based approach was applied, resulting in a panel of 41 over-expressed genes in OSCA. The RNA quantity gene expression of the 41 selected genes was then cross-validated by using NanoString nCounter technology. Moreover, we showed that the RNA quantity of eight genes (ADGRG1, EPCAM, ESRP1, MAL2, MYH14, PRSS8, ST14 and WFDC2) discriminates each OSCA sample from each healthy sample in our data set with sensitivity of 100% and specificity of 100%. For the other three genes (MUC16, PAX8 and SOX17) in combination, their RNA quantity may distinguish OSCA from other 29 tumor types.

Surface plasmon resonance: A promising approach for label-free early cancer diagnosis

Cancer is the second leading cause of death worldwide after cardiovascular disease. The major cause of high mortality is delayed detection. Therefore, detection at an early stage followed by early treatment can mitigate morbidity as well as mortality. The utilization of biomarker-based detection tools helps in early-stage recognition. Fortunately, biomarkers indicating disease status can be released in to the circulation. These include traditional marker proteins as well as exosomes, micro-RNA (miRNA) and circulating tumor DNA (ct-DNA). Biosensors are biological and chemical reaction devices that generate signals based on analyte concentration. Due to analyte binding, these devices demonstrate high sensitivity and specificity. This review examines the use of surface plasmon resonance (SPR)-based sensors in the diagnosis of various cancer including those of the breast, prostate, lung, ovary, cervix and pancreas. SPR is a label-free, real-time and non-invasive optical biosensing technology representing a novel diagnostic tool in cancer detection.

Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data

Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were down-regulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

Multi-Omics Analysis Identifying Key Biomarkers in Ovarian Cancer

Ovarian cancer is one of the most common malignant tumors. Here, we aimed to study the expression and function of the CREB1 gene in ovarian cancer via the bioinformatic analyses of multiple databases. Previously, the prognosis of ovarian cancer was based on single-factor or single-gene studies. In this study, different bioinformatics tools (such as TCGA, GEPIA, UALCAN, MEXPRESS, and Metascape) have been used to assess the expression and prognostic value of the CREB1 gene. We used the Reactome and cBioPortal databases to identify and analyze CREB1 mutations, copy number changes, expression changes, and protein-protein interactions. By analyzing data on the CREB1 differential expression in ovarian cancer tissues and normal tissues from 12 studies collected from the "Human Protein Atlas" database, we found a significantly higher expression of CREB1 in normal ovarian tissues. Using this database, we collected information on the expression of 25 different CREB-related proteins, including TP53, AKT1, and AKT3. The enrichment of these factors depended on tumor metabolism, invasion, proliferation, and survival. Individualized tumors based on gene therapy related to prognosis have become a new possibility. In summary, we established a new type of prognostic gene profile for ovarian cancer using the tools of bioinformatics.

Influence of Glutaraldehyde's Molecular Transformations on Spectroscopic Investigations of Its Conjugation with Amine-Modified Fe3O4 Microparticles in the Reaction Medium

Glutaraldehyde (GA) is a widely used cross-linking agent in biological research due to its superior characteristics, such as high reactivity toward proteins, high stability, and cost-effectiveness. In this regard, analyzing spectral changes initiated by various molecular forms and transformations of GA in a reaction medium and its reaction with surface functional-modified solid spheres is vital for a successful bioconjugation process targeting the biomolecules of interest. In this work, we present Fourier transform-infrared (FT-IR), Raman, and UV-visible spectroscopic analyses of glutaraldehyde-modified Fe₃O₄ microparticles (magnetic beads) to confirm the conjugation between GA and magnetic beads. We also studied the molecular transformations of glutaraldehyde during the reaction with amine-modified magnetic beads via investigating the reaction medium of the glutaraldehyde solution. Our FT-IR and Raman studies confirmed that glutaraldehyde was successfully coupled on the magnetic beads. Furthermore, FT-IR and UV-vis studies on the glutaraldehyde solution revealed the multiple molecular forms of GA in an aqueous medium, and they also confirmed that glutaraldehyde transforms into other molecular forms while the reaction occurs with the magnetic beads.

Review of biomarker systems as an alternative for early diagnosis of ovarian carcinoma

Early diagnosis of ovarian carcinoma is bound to boost the long-term endurance rate of the patients. Most ovarian tumors happen post menopause when the ovaries have no vital operation and therefore irregular ovarian role causes no signs. According to Muinao T. et al. (Heliyon. 5(12):e02826, 2019), if we consider the frequency of ovarian carcinoma to be moderate, a screening technique must accomplish a base specificity of 99.6% and sensitivity of over 75%. The classification and approval of early diagnostic biomarkers explicit to ovarian carcinoma are essentially required. Prevailing methods for early diagnosis of ovarian carcinoma incorporate TVS, biological marker examination, or a blend of the two or other. In recent years, it has been revealed that a combination of at least two biomarkers has beaten single biomarkers in measures for early diagnosis of the illness. In the present document, we survey the ongoing exploration of innovative characteristic methodologies and possible panels of carcinoma biological markers for the early diagnosis of ovarian carcinoma and discuss biomarkers as the plausible apparatus for model improvement and other progressed approaches as an effective alternative to the prevailing methods for early diagnosis of this dreadful disease to evade bogus analysis and inordinate expense.

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

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

Expression of Circulating MicroRNA-141 in Epithelial Ovarian Cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is a lethal disease due to late diagnosis and lack of effective screening methods. MicroRNA (miR/miRNA) plays an important role in ovarian carcinogenesis and may serve as a non-invasive biomarker for EOC. This study aimed to assess miR-141 expression in the blood plasma of patients with EOC and healthy subjects and determine its association with the clinical stage of EOC.

METHODS

This cross-sectional study used blood plasma from 30 newly diagnosed untreated patients with EOC and 25 healthy subjects. The mean age was 47.73 (SD = 10.29) years for EOC and 44.48 (SD = 16.14) years for healthy subject. The total RNA was isolated from blood plasma and reversed transcribed to obtain cDNA. The expression of miR-141 was measured by real-time quantitative polymerase chain reaction (qRT-PCR), and calculated using 2-ΔΔCt methods. The data were analysed using Mann-Whitney test.

RESULTS

The expression of miR-141 was upregulated 8.41 fold in the blood plasma of EOC patients compared to healthy controls (P < 0.001). Expression of miR-141 in the advanced stage was upregulated 4.2 fold compared to the early stage (P < 0.001).

CONCLUSION

The miR-141 was upregulated in the blood plasma of EOC and associated with an advanced stage of disease, suggesting it has potential as a biomarker for EOC detection.

Clinical usefulness of high levels of C-reactive protein for diagnosing epithelial ovarian cancer

The purpose of the present study was to evaluate the diagnostic role of CRP in ovarian cancer and to assess whether CRP can be combined with tumor markers to enhance the diagnostic efficacy toward ovarian cancer. Area under the curve, sensitivity, and specificity were calculated to access the diagnostic ability of each singly and combined as markers for ovarian cancer. The CRP cut-off value was then calculated to evaluate the diagnostic efficacy of CRP for ovarian cancer. Our results showed that values for all markers were significantly higher in the cancer group than in the control group. Receiver operating characteristic curve results showed that CA125 had the highest diagnostic efficacy for ovarian cancer, while the sensitivity for CRP was higher than for CA125, and the specificity for CRP was equal to that of CA125. The combination of CRP, CA125, and HE4, however, provided the strongest diagnostic capability. Furthermore, the diagnostic cut-off value for CRP with regard to ovarian cancer was 9.8 mg/L, and high levels of CRP were correlated with stage and tumor size of ovarian cancer. Our study indicated that CRP is valuable in the diagnosis of ovarian cancer, and that combining CRP with CA125 and HE4 improved the diagnostic efficacy with respect to ovarian cancer.

Ovarian Cancer: Tumor-Specific Urinary Micro-Peptides Profiling as Potential Biomarkers for Early Diagnosis

Ovarian cancer is the second major lethal gynecologic malignancy in developing countries. This study aimed to characterize urinary micro-peptides as potential diagnostic biomarkers for ovarian cancer. In a prospective, longitudinal and case-controlled study and following informed consent, urine and plasma samples were collected from 112 women with histologically-proven ovarian cancer and 200 apparently healthy age-matched volunteers. Urinary micro-peptides were detected and sequenced using SDS-PAGE and Edman degradation technique. Serum CA125 was detected in less than a quarter (23.2%, 26/112) of patients. One or more urinary micro-peptides were detected in about two thirds of the patients (62.5%, 70/112). A total of 40 patients had three bands (57.1%, 40/70), while two bands (15 and 35 kDa) were detected in 28.6% (20/70) of the patients. Isolated 45 kDa band was seen in 14.3% (10/70). No urinary micro-peptide was detected in the volunteers. The 15 and 35 kDa bands disappeared after 6 months of regular chemotherapy, while the 45 kDa band persisted in 2.9% (2/70) of the patients after treatment. The micro-peptides were identified as: Catalase (45 kDa), α-1 Acid Glycoprotein (35 kDa) and Peroxiredoxin-2 (15 kDa). Urinary catalase, α-1 Acid Glycoprotein and Peroxiredoxin-2 can be useful biomarkers for early detection and treatment response of ovarian cancer.

Identification of molecular biomarkers for ovarian cancer using computational approaches

Ovarian cancer is one of the major causes of mortality among women. This is partly because of highly asymptomatic nature, lack of reliable screening techniques and non-availability of effective biomarkers of ovarian cancer. The recent availability of high-throughput data and consequently the development of network medicine approach may play a key role in deciphering the underlying global mechanism involved in a complex disease. This novel approach in medicine will pave the way in translating the new molecular insights into an effective drug therapy applying better diagnostic, prognostic and predictive tests for a complex disease. In this study, we performed reconstruction of gene co-expression networks with a query-based method in healthy and different stages of ovarian cancer to identify new potential biomarkers from the reported biomarker genes. We proposed 17 genes as new potential biomarkers for ovarian cancer that can effectively classify a disease sample from a healthy sample. Most of the predicted genes are found to be differentially expressed between healthy and diseased states. Moreover, the survival analysis showed that these genes have a significantly higher effect on the overall survival rate of the patient than the established biomarkers. The comparative analyses of the co-expression networks across healthy and different stages of ovarian cancer have provided valuable insights into the dynamic nature of ovarian cancer.

Clinical Interest of Combining Transcriptomic and Genomic Signatures in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer is one of the deadliest gynecological malignancies and remains a clinical challenge. There is a critical need to effectively define patient stratification in a clinical setting. In this study, we address this question and determine the optimal number of molecular subgroups for ovarian cancer patients. By studying several independent patient cohorts, we observed that classifying high-grade serous ovarian tumors into four molecular subgroups using a transcriptomic-based approach did not reproducibly predict patient survival. In contrast, classifying these tumors into only two molecular subgroups, fibrosis and non-fibrosis, could reliably inform on patient survival. In addition, we found complementarity between transcriptomic data and the genomic signature for homologous recombination deficiency (HRD) that helped in defining prognosis of ovarian cancer patients. We also established that the transcriptomic and genomic signatures underlined independent biological processes and defined four different risk populations. Thus, combining genomic and transcriptomic information appears as the most appropriate stratification method to reliably subgroup high-grade serous ovarian cancer patients. This method can easily be transferred into the clinical setting.

Improved early detection of ovarian cancer using longitudinal multimarker models

BACKGROUND

Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer.

METHODS

This case-control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer.

RESULTS

The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time.

CONCLUSIONS

We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.

MicroRNAs in ovarian cancer and recent advances in the development of microRNA-based biosensors

Ovarian cancer is the most aggressive of all gynaecological malignancies and is the leading cause of cancer-associated mortality worldwide.

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.

Nanotechnology and Immunotherapy in Ovarian Cancer: Tracing New Landscapes

Ovarian cancer (OC) is the seventh most common cancer in women worldwide. Standard therapeutic treatments involve debulking surgery combined with platinum-based chemotherapies. Of the patients with advanced-stage cancer who initially respond to current treatments, 50%-75% relapse. Immunotherapy-based approaches aimed at boosting antitumor immunity have recently emerged as promising tools to challenge tumor progression. Treatments with inhibitors of immune checkpoint molecules have shown impressive results in other types of tumors. However, only 15% of checkpoint inhibitors evaluated have proven successful in OC due to the immunosuppressive environment of the tumor and the transport barriers. This limits the efficacy of the existing immunotherapies. Nanotechnology-based delivery systems hold the potential to overcome such limitations. Various nanoformulations including polymeric, liposomes, and lipid-polymer hybrid nanoparticles have already been proposed to improve the biodistribution and targeting capabilities of drugs against tumor-associated immune cells, including dendritic cells and macrophages. In this review, we examine the impact of immunotherapeutic approaches that are currently under consideration for the treatment of OC. In this review, we also provide a comprehensive analysis of the existing nanoparticle-based synthetic strategies and their limitations and advantages over standard treatments. Furthermore, we discuss how the strength of the combination of nanotechnology with immunotherapy may help to overcome the current therapeutic limitations associated with their individual application and unravel a new paradigm in the treatment of this malignancy.

Discovery and Validation of Novel Biomarkers for Detection of Epithelial Ovarian Cancer

Detection of epithelial ovarian cancer (EOC) poses a critical medical challenge. However, novel biomarkers for diagnosis remain to be discovered. Therefore, innovative approaches are of the utmost importance for patient outcome. Here, we present a concept for blood-based biomarker discovery, investigating both epithelial and specifically stromal compartments, which have been neglected in search for novel candidates. We queried gene expression profiles of EOC including microdissected epithelium and adjacent stroma from benign and malignant tumours. Genes significantly differentially expressed within either the epithelial or the stromal compartments were retrieved. The expression of genes whose products are secreted yet absent in the blood of healthy donors were validated in tissue and blood from patients with pelvic mass by NanoString analysis. Results were confirmed by the comprehensive gene expression database, CSIOVDB (Ovarian cancer database of Cancer Science Institute Singapore). The top 25% of candidate genes were explored for their biomarker potential, and twelve were able to discriminate between benign and malignant tumours on transcript levels (p < 0.05). Among them T-cell differentiation protein myelin and lymphocyte (MAL), aurora kinase A (AURKA), stroma-derived candidates versican (VCAN), and syndecan-3 (SDC), which performed significantly better than the recently reported biomarker fibroblast growth factor 18 (FGF18) to discern malignant from benign conditions. Furthermore, elevated MAL and AURKA expression levels correlated significantly with a poor prognosis. We identified promising novel candidates and found the stroma of EOC to be a suitable compartment for biomarker discovery.

Urine Biomarkers for the Early Detection of Ovarian Cancer - Are We There Yet?

Ovarian cancer affects around 7500 women in the United Kingdom every year. Despite this, there is no effective screening strategy or standard treatment for ovarian cancer. If diagnosed during stage I, ovarian cancer has a 90% 5-year survival rate; however, there is usually a masking of symptoms which leads to an often late-stage diagnosis and correspondingly poor survival rate. Current diagnostic methods are invasive and consist of a pelvic examination, transvaginal ultrasonography, and blood tests to detect cancer antigen 125 (CA125). Unfortunately, surgery is often still required to make a positive diagnosis. To address the need for accurate, specific, and non-invasive diagnostic methods, there has been an increased interest in biomarkers identified through non-invasive tests as tools for the earlier diagnosis of ovarian cancer. Although most studies have focused on the identification of biomarkers in blood, the ease of availability of urine and the high patient compliance rates suggest that it could provide a promising resource for the screening of patients for ovarian cancer.

Detection of cancer antigens (CA-125) using gold nano particles on interdigitated electrode-based microfluidic biosensor

Integrating microfluidics with biosensors is of great research interest with the increasing trend of lab-on-the chip and point-of-care devices. Though there have been numerous studies performed relating microfluidics to the biosensing mechanisms, the study of the sensitivity variation due to microfluidic flow is very much limited. In this paper, the sensitivity of interdigitated electrodes was evaluated at the static drop condition and the microfluidic flow condition. In addition, this study demonstrates the use of gold nanoparticles to enhance the sensor signal response and provides experimental results of the capacitance difference during cancer antigen-125 (CA-125) antigen-antibody conjugation at multiple concentrations of CA-125 antigens. The experimental results also provide evidence of disease-specific detection of CA-125 antigen at multiple concentrations with the increase in capacitive signal response proportional to the concentration of the CA-125 antigens. The capacitive signal response of antigen-antibody conjugation on interdigitate electrodes has been enhanced by approximately 2.8 times (from 260.80 to 736.33 pF at 20 kHz frequency) in static drop condition and approximately 2.5 times (from 205.85 to 518.48 pF at 20 kHz frequency) in microfluidic flow condition with gold nanoparticle-coating. The capacitive signal response is observed to decrease at microfluidic flow condition at both plain interdigitated electrodes (from 260.80 to 205.85 pF at 20 kHz frequency) and gold nano particle coated interdigitated electrodes (from 736.33 to 518.48 pF at 20 kHz frequency), due to the strong shear effect compared to static drop condition. However, the microfluidic channel in the biosensor has the potential to increase the signal to noise ratio due to plasma separation from the whole blood and lead to the increase concentration of the biomarkers in the blood volume for sensing.

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.

Anabolic Androgenic Steroids: Searching New Molecular Biomarkers

Even if anabolic androgenic steroid (AAS) abuse is clearly associated with a wide spectrum of collateral effects, adolescents and athletes frequently use a large group of synthetic derivatives of testosterone, both for aesthetic uses and for improving performance. Over the last few years, the development of MicroRNA (miRNA) technologies has become an essential part of research projects and their role as potential molecular biomarkers is being investigated by the scientific community. The circulating miRNAs detection as a diagnostic or prognostic tool for the diagnosis and treatment of several diseases is very useful, because with a minimal quantity of sample (peripheral blood), miRNAs are very sensitive. Even more, miRNAs remain stable both at room temperature and during freeze-thaw cycles. These characteristics highlight the important role of miRNAs in the near future as new tools for anti-doping. The article provides a systematic review and meta-analysis on the role of miRNAs as new potential molecular biomarkers of AAS use/abuse. Particularly, this paper analyzed the “miRNA signature” use as biomarkers for health disorders, focusing on the organ damages which are related to ASS use/abuse. Moreover, this review aims to provide a future prospect for less invasive or non-invasive procedures for the detection of circulating miRNA biomarkers as doping assumption signaling.

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

Aim

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

Material and Methods

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

Results

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

Conclusions

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

STAT3/PIAS3 Levels Serve as "Early Signature" Genes in the Development of High-Grade Serous Carcinoma from the Fallopian Tube

The initial molecular events that lead to malignant transformation of the fimbria of the fallopian tube (FT) through high-grade serous ovarian carcinoma (HGSC) remain poorly understood. In this study, we report that increased expression of signal transducer and activator of transcription 3 (pSTAT3 Tyr705) and suppression or loss of protein inhibitor of activated STAT3 (PIAS3) in FT likely drive HGSC. We evaluated human tissues-benign normal FT, tubal-peritoneal junction (TPJ), p53 signature FT tissue, tubal intraepithelial lesion in transition (TILT), serous tubal intraepithelial carcinoma (STIC) without ovarian cancer, and HGSC for expression of STAT3/PIAS3 (compared with their known TP53 signature) and their target proliferation genes. We observed constitutive activation of STAT3 and low levels or loss of PIAS3 in the TPJ, p53 signature, TILT, and STIC through advanced stage IV (HGSC) tissues. Elevated expression of pSTAT3 Tyr705 and decreased levels of PIAS3 appeared as early as TPJ and the trend continued until very advanced stage HGSC (compared with high PIAS3 and low pSTAT3 expression in normal benign FT). Exogenous expression of STAT3 in FT cells mediated translocation of pSTAT3 and c-Myc into the nucleus. In vivo experiments demonstrated that overexpression of STAT3 in FT secretory epithelial cells promoted tumor progression and metastasis, mimicking the clinical disease observed in patients with HGSC. Thus, we conclude that the STAT3 pathway plays a role in the development and progression of HGSC from its earliest premalignant states.Significance: Concomitant gain of pSTAT3 Tyr705 and loss of PIAS3 appear critical for initiation and development of high-grade serous carcinoma. Cancer Res; 78(7); 1739-50. ©2018 AACR.

Tumor suppressor PRSS8 targets Sphk1/S1P/Stat3/Akt signaling in colorectal cancer

PRSS8 is a membrane-anchored serine protease prostasin and has been shown an association with carcinogenesis. Herein we found that PRSS8 expression was significantly reduced in colorectal adenomas and adenocarcinomas. The decreased PRSS8 was well correlated with clinical stages, poor differentiation and shorter survival time of colorectal cancer. Furthermore, increase of PRSS8 led to the inhibition of colorectal cancer cell proliferation, knockdown of PRSS8 accelerated cell proliferation in vitro, and overexpressing PRSS8 retarded cancer cell growth in nude mice. Mechanistic studies revealed that PRSS8 inhibited Sphk1/S1P/Stat3/Akt signaling pathway, in terms of inverse association between PRSS8 and Sphk1 in human colorectal cancers and in Sphk1-/- mice. In conclusion, PRSS8 acts as a tumor suppressor by inhibiting Sphk1/S1P/Stat3/Akt signaling pathway, and could be used as a biomarker to monitor colorectal carcinogenesis and predict outcomes.

Extracellular vesicles in ovarian cancer: applications to tumor biology, immunotherapy and biomarker discovery

In recent years there has been tremendous interest in both the basic biology and applications of extracellular vesicles (EVs) in translational cancer research. This includes a better understanding of their biogenesis and mechanisms of selective cargo packaging, their precise roles in horizontal communication, and their application as non-invasive biomarkers. The rapid advances in next-generation omics technologies are the driving forces for these discoveries. In this review, the authors focus on recent results of EV research in ovarian cancer. A deeper understanding of ovarian cancer-derived EVs, the types of cargo molecules and their biological roles in cancer growth, metastases and drug resistance, could have significant impact on the discovery of novel biomarkers and innovative therapeutics. Insights into the role of EVs in immune regulation could lead to novel approaches built on EV-based immunotherapy.

Overexpression of Protease Serine 8 Inhibits Glioma Cell Proliferation, Migration, and Invasion via Suppressing the Akt/mTOR Signaling Pathway

Protease serine 8 (PRSS8), a serine peptidase, has a widespread expression in normal epidermal cells. Recently, many researchers demonstrated downregulation of PRSS8 in cancer tissues as well as its tumor suppressor role in cancer development. However, the biological functions of PRSS8 in glioma remain unclear. In the current study, we demonstrated a decreased expression of PRSS8 in glioma tissues and cell lines. PRSS8 upregulation inhibited glioma cell proliferation, migration, and invasion. In addition, xenograft experiments showed that PRSS8 overexpression suppressed glioma cell growth in vivo. We also found that upregulated PRSS8 reduced the protein expression levels of p-Akt and p-mTOR in glioma cells. Taken together, our study demonstrated that overexpression of PRSS8 inhibited glioma cell proliferation, migration, and invasion via suppressing the Akt/mTOR signaling pathway. Therefore, PRSS8 may act as a novel therapeutic target for glioma.

Molecular Subtyping of Serous Ovarian Cancer Based on Multi-omics Data

Classification of ovarian cancer by morphologic features has a limited effect on serous ovarian cancer (SOC) treatment and prognosis. Here, we proposed a new system for SOC subtyping based on the molecular categories from the Cancer Genome Atlas project. We analyzed the DNA methylation, protein, microRNA, and gene expression of 1203 samples from 599 serous ovarian cancer patients. These samples were divided into nine subtypes based on RNA-seq data, and each subtype was found to be associated with the activation and/or suppression of the following four biological processes: immunoactivity, hormone metabolic, mesenchymal development and the MAPK signaling pathway. We also identified four DNA methylation, two protein expression, six microRNA sequencing and four pathway subtypes. By integrating the subtyping results across different omics platforms, we found that most RNA-seq subtypes overlapped with one or two subtypes from other omics data. Our study sheds light on the molecular mechanisms of SOC and provides a new perspective for the more accurate stratification of its subtypes.

The serine protease prostasin (PRSS8) is a potential biomarker for early detection of ovarian cancer

Background

Ovarian cancer (OVC) is the deadliest of all gynecologic cancers, primarily as a consequence of asymptomatic progression. The complex nature of OVC creates challenges for early detection, and there is a lack of specific and sensitive biomarkers suitable for screening and detecting early stage OVC.

Methods

Potential OVC biomarkers were identified by bioinformatic analysis. Candidates were further screened for differential expression in a library of OVC cell lines. OVC-specific overexpression of a candidate gene, PRSS8, which encodes prostasin, was confirmed against 18 major human cancer types from 390 cancer samples by qRT-PCR. PRSS8 expression profiles stratified by OVC tumor stage-, grade- and subtype were generated using cDNA samples from 159 OVC samples. Cell-specific expression and localization of prostasin was determined by immunohistological tissue array analysis of more than 500 normal, benign, and cancerous ovarian tissues. The presence of prostasin in normal, benign, and OVC serum samples was also determined.

Results

Gene expression analysis indicated that PRSS8 was expressed in OVC at levels more than 100 fold greater than found in normal or benign ovarian lesions. This overexpression signature was found in early stages of OVC and was maintained in higher stages and grades of OVC. The PRSS8 overexpression signature was specific for OVC and urinary bladder cancer among 18 human cancer types. The majority of ovarian cell lines overexpressed PRSS8. In situ hybridization and histopathology studies of OVC tissues indicated that overexpression of prostasin was largely localized to tumor epithelium and was absent in neighboring stroma. Significantly higher levels of prostasin were found in early stage OVC serum samples compared to benign ovarian and normal donor samples.

Conclusions

The abundant amounts of secreted prostasin found in sera of early stage OVC can potentially be used as a minimally invasive screening biomarker for early stage OVC. Overexpression of PRSS8 mRNA and high levels of prostasin in multiple subtypes of early stage ovarian tumors may provide clinical biomarkers for early detection of OVC, which can potentially be used with CA125 and HE4.

Electronic supplementary material

The online version of this article (doi:10.1186/s13048-016-0228-9) contains supplementary material, which is available to authorized users.

Accumulated Metabolites of Hydroxybutyric Acid Serve as Diagnostic and Prognostic Biomarkers of Ovarian High-Grade Serous Carcinomas

Ovarian cancer is a heterogeneous disease of low prevalence, but poor survival. Early diagnosis is critical for survival, but it is often challenging because the symptoms of ovarian cancer are subtle and become apparent only during advanced stages of the disease. Therefore, the identification of robust biomarkers of early disease is a clinical priority. Metabolomic profiling is an emerging diagnostic tool enabling the detection of biomarkers reflecting alterations in tumor metabolism, a hallmark of cancer. In this study, we performed metabolomic profiling of serum and tumor tissue from 158 patients with high-grade serous ovarian cancer (HGSOC) and 100 control patients with benign or non-neoplastic lesions. We report metabolites of hydroxybutyric acid (HBA) as novel diagnostic and prognostic biomarkers associated with tumor burden and patient survival. The accumulation of HBA metabolites caused by HGSOC was also associated with reduced expression of succinic semialdehyde dehydrogenase (encoded by ALDH5A1), and with the presence of an epithelial-to-mesenchymal transition gene signature, implying a role for these metabolic alterations in cancer cell migration and invasion. In conclusion, our findings represent the first comprehensive metabolomics analysis in HGSOC and propose a new set of metabolites as biomarkers of disease with diagnostic and prognostic capabilities.

Involvement of Kallikrein-Related Peptidases in Normal and Pathologic Processes

Human kallikrein-related peptidases (KLKs) are a subgroup of serine proteases that participate in proteolytic pathways and control protein levels in normal physiology as well as in several pathological conditions. Their complex network of stimulatory and inhibitory interactions may induce inflammatory and immune responses and contribute to the neoplastic phenotype through the regulation of several cellular processes, such as proliferation, survival, migration, and invasion. This family of proteases, which includes one of the most useful cancer biomarkers, kallikrein-related peptidase 3 or PSA, also has a protective effect against cancer promoting apoptosis or counteracting angiogenesis and cell proliferation. Therefore, they represent attractive therapeutic targets and may have important applications in clinical oncology. Despite being intensively studied, many gaps in our knowledge on several molecular aspects of KLK functions still exist. This review aims to summarize recent data on their involvement in different processes related to health and disease, in particular those directly or indirectly linked to the neoplastic process.

Relative Quantification and Higher-Order Modeling of the Plasma Glycan Cancer Burden Ratio in Ovarian Cancer Case-Control Samples

An early-stage, population-wide biomarker for ovarian cancer (OVC) is essential to reverse its high mortality rate. Aberrant glycosylation by OVC has been reported, but studies have yet to identify an N-glycan with sufficiently high specificity. We curated a human biorepository of 82 case-control plasma samples, with 27%, 12%, 46%, and 15% falling across stages I-IV, respectively. For relative quantitation, glycans were analyzed by the individuality normalization when labeling with glycan hydrazide tags (INLIGHT) strategy for enhanced electrospray ionization, MS/MS analysis. Sixty-three glycan cancer burden ratios (GBRs), defined as the log10 ratio of the case-control extracted ion chromatogram abundances, were calculated above the limit of detection. The final GBR models, built using stepwise forward regression, included three significant terms: OVC stage, normalized mean GBR, and tag chemical purity; glycan class, fucosylation, or sialylation were not significant variables. After Bonferroni correction, seven N-glycans were identified as significant (p < 0.05), and after false discovery rate correction, an additional four glycans were determined to be significant (p < 0.05), with one borderline (p = 0.05). For all N-glycans, the vectors of the effects from stages II-IV were sequentially reversed, suggesting potential biological changes in OVC morphology or in host response.

Development of Follicle-Stimulating Hormone Receptor Binding Probes to Image Ovarian Xenografts

The Follicle-Stimulating Hormone Receptor (FSHR) is used as an imaging biomarker for the detection of ovarian cancer (OC). FSHR is highly expressed on ovarian tumors and involved with cancer development and metastatic signaling pathways. A decapeptide specific to the FSHR extracellular domain is synthesized and conjugated to fluorescent dyes to image OC cells in vitro and tumors xenograft model in vivo. The in vitro binding curve and the average number of FSHR per cell are obtained for OVCAR-3 cells by a high resolution flow cytometer. For the decapeptide, the measured EC50 was 160 μM and the average number of receptors per cell was 1.7 × 10⁷. The decapeptide molecular imaging probe reached a maximum tumor to muscle ratio five hours after intravenous injection and a dose-dependent plateau after 24-48 hours. These results indicate the potential application of a small molecular weight imaging probe specific to ovarian cancer through binding to FSHR. Based on these results, multimeric constructs are being developed to optimize binding to ovarian cells and tumors.

An ultra-sensitive impedimetric immunosensor for detection of the serum oncomarker CA-125 in ovarian cancer patients

Effective treatment of ovarian cancer depends upon the early detection of the malignancy. Here, we report on the development of a new nanostructured immunosensor for early detection of cancer antigen 125 (CA-125). A gold electrode was modified with mercaptopropionic acid (MPA), and then consecutively conjugated with silica coated gold nanoparticles (AuNP@SiO2), CdSe quantum dots (QDs) and anti-CA-125 monoclonal antibody (mAb). The engineered MPA|AuNP@SiO2|QD|mAb immunosensor was characterised using transmission electron microscopy (TEM), atomic force microscopy (AFM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Successive conjugation of AuNP@SiO2, CdSe QD and anti-CA-125 mAb onto the gold electrode resulted in sensitive detection of CA-125 with a limit of detection (LOD) of 0.0016 U mL(-1) and a linear detection range (LDR) of 0-0.1 U mL(-1). Based on the high sensitivity and specificity of the immunosensor, we propose this highly stable and reproducible biosensor for the early detection of CA-125.