Development of a multimarker assay for early detection of ovarian cancer

Cooperative amplification of Prussian blue as a signal indicator and functionalized metal-organic framework-based electrochemical biosensor for an ultrasensitive HE4 assay

Human epididymis protein 4 (HE4), a diagnostic biomarker of ovarian cancer, is crucial for monitoring the early stage of the disease. Hence, it is highly important to develop simple, inexpensive, and user-friendly biosensors for sensitive and quantitative HE4 assays. Herein, a new sandwich-type electrochemical immunosensor based on Prussian blue (PB) as a signal indicator and functionalized metal-organic framework nanocompositesas efficient signal amplifiers was fabricated for quantitative analysis of HE4. In principle, ketjen black (KB) and AuNPs modified on TiMOF (TiMOF-KB@AuNPs) could accelerate electron transfer on the electrode surface and act as a matrix for the immobilization of antibodies via cross-linking to improve the determination sensitivity. The PB that covalently binds to labeled antibodies endows the biosensors with intense electrochemical signals. Furthermore, the concentration of HE4 could be indirectly detected by monitoring the electroactivity of PB. Benefiting from the high signal amplification ability of the PB and MOF nanocomposites, this strategy displayed a wide linear range (0.1-80 ng mL-1) and a lower detection limit (0.02 ng mL-1). Hence, this study demonstrated great promise for application in clinical ovarian cancer diagnosis and treatment, and provided a new platform for detecting other cancer biomarkers.

The intratumoral microbiota biomarkers for predicting survival and efficacy of immunotherapy in patients with ovarian serous cystadenocarcinoma

BACKGROUND

Ovarian serous cystadenocarcinoma, accounting for about 90% of ovarian cancers, is frequently diagnosed at advanced stages, leading to suboptimal treatment outcomes. Given the malignant nature of the disease, effective biomarkers for accurate prediction and personalized treatment remain an urgent clinical need.

METHODS

In this study, we analyzed the microbial contents of 453 ovarian serous cystadenocarcinoma and 68 adjacent non-cancerous samples. A univariate Cox regression model was used to identify microorganisms significantly associated with survival and a prognostic risk score model constructed using LASSO Cox regression analysis. Patients were subsequently categorized into high-risk and low-risk groups based on their risk scores.

RESULTS

Survival analysis revealed that patients in the low-risk group had a higher overall survival rate. A nomogram was constructed for easy visualization of the prognostic model. Analysis of immune cell infiltration and immune checkpoint gene expression in both groups showed that both parameters were positively correlated with the risk level, indicating an increased immune response in higher risk groups.

CONCLUSION

Our findings suggest that microbial profiles in ovarian serous cystadenocarcinoma may serve as viable clinical prognostic indicators. This study provides novel insights into the potential impact of intratumoral microbial communities on disease prognosis and opens avenues for future therapeutic interventions targeting these microorganisms.

The incidence risk of gynecological cancer by antipsychotic use: a meta-analysis of 50,402 patients

BACKGROUND

Female gynecological cancers represent a serious public health problem, with 1,398,601 new diagnoses and 671,875 deaths per year worldwide. Antipsychotics are often used in psychiatric disorders, including schizophrenia, bipolar disorder, and major depression. It is estimated that the prescription of these drugs is linked to 1,800 deaths a year in the United States, but their association with cancer remains controversial.

METHODS

We searched PubMed, Scopus, and Web of Science databases for studies reporting the correlation in the incidence risk of gynecological cancer by antipsychotic use. We used DerSimonian and Laird random-effect models to compute logit transformed odds ratio (OR) for the primary binary endpoint with 95% confidence interval (CI). Heterogeneity was assessed through effect size width along with I-squared and Tau-squared statistics. Review Manager 5.4.1. was used for statistical analyses. A p-value of < 0.05 denoted statistically significant.

RESULTS

50,402 patients were included, of whom 778 (1,54%) took antipsychotic medication for at least 1 year. 1,086 (2,15%) with ovarian cancer and 49,316 (97,85%) with endometrial cancer. Antipsychotic use (OR 1.50; 1.06 to 2.13 95% CI; p-value 0.02), hypertension (OR 1.50; 95% CI 1.06 to 2.13; p-value < 0.01), nulliparity (OR 1.98; 95% CI 1.53 to 2.57; p-value < 0.01) and multiparity (OR 0.53; 95% CI 0.41 to 0.69; p-value < 0.01) showed significantly different distributions between groups of cancer and cancer-free patients. The primary endpoint of incidence risk of gynecological cancer by antipsychotic therapy showed a statistically significant difference (OR 1.67; 95% CI 1.02 to 2.73; p-value < 0.05) against the use of antipsychotic drugs.

CONCLUSIONS

Our meta-analysis showed that the use of antipsychotic drugs increases the risk of gynecological cancers, particularly endometrial cancer. This result should be weighed against the potential effects of treatment for a balanced prescribing decision.

Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer

One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Expression of Immune-Related and Inflammatory Markers and Their Prognostic Impact in Colorectal Cancer Patients

The tumor microenvironment of colorectal cancer (CRC) is heterogenous; thus, it is likely that multiple immune-related and inflammatory markers are simultaneously expressed in the tumor. The aim of this study was to identify immune-related and inflammatory markers expressed in freshly frozen CRC tissues and to investigate whether they are related to the clinicopathological features and prognosis of CRC. Seventy patients with CRC who underwent curative surgical resection between December 2014 and January 2017 were included in this study. Tissue samples were obtained from tumor and non-tumor areas in the patients' colons. The concentrations of immune-related markers (APRIL/TNFSF13, BAFF, LAG-3, PD-1, PD-L1, and CTLA-4) and inflammatory markers (CHIT, MMP-3, osteocalcin, pentraxin-3, sTNF-R1, and sTNF-R2) in the samples were measured using the Bio-plex Multiplex Immunoassay system. The concentrations of APRIL/TNFSF13, BAFF, and MMP-3 in the samples were significantly high; thus, we conducted analyses based on the cut-off values for these three markers. The high-APRIL/TNFSH13-expression group showed a significantly higher rate of metastatic lesions than the low-expression group, whereas the high-MMP-3-expression group had higher CEA levels, more lymph node metastases, and more advanced disease stages than the low-expression group. The five-year disease-free survival of the high-MMP-3-expression group was significantly shorter than that of the low-expression group (65.1% vs. 90.2%, p = 0.033). This study provides evidence that the APRIL/TNFSF13, BAFF, and MMP-3 pathway is overexpressed in CRC tissues and is associated with unfavorable clinicopathological features and poor prognosis in CRC patients. These markers could serve as diagnostic or prognostic biomarkers for CRC.

VCAM-1 complements CA-125 in detecting recurrent ovarian cancer

BACKGROUND

Close to three-quarters of ovarian cancer cases are frequently diagnosed at an advanced stage, with more than 70% of them failing to respond to primary therapy and relapsing within 5 years. There is an urgent need to identify strategies for early detection of ovarian cancer recurrence, which may lead to earlier intervention and better outcomes.

METHODS

A customized magnetic bead-based 8-plex immunoassay was evaluated using a Bio-Plex 200 Suspension Array System. Target protein levels were analyzed in sera from 58 patients diagnosed with advanced ovarian cancer (including 34 primary and 24 recurrent tumors) and 46 healthy controls. The clinical performance of these biomarkers was evaluated individually and in combination for their ability to detect recurrent ovarian cancer.

RESULTS

An 8-plex immunoassay was evaluated with high analytical performance suitable for biomarker validation studies. Logistic regression modeling selected a two-marker panel of CA-125 and VCAM-1 that improved the performance of CA-125 alone in detecting recurrent ovarian cancer (AUC: 0.813 versus 0.700). At a fixed specificity of 83%, the two-marker panel significantly improved sensitivity in separating primary from recurrent tumors (70.8% versus 37.5%, P = 0.004), demonstrating that VCAM-1 was significantly complementary to CA-125 in detecting recurrent ovarian cancer.

CONCLUSIONS

A two-marker panel of CA-125 and VCAM-1 showed strong diagnostic performance and improvement over the use of CA-125 alone in detecting recurrent ovarian cancer. The experimental results warrant further clinical validation to determine their role in the early detection of recurrent ovarian cancer.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.

Development of a multiplex-based immunoassay for the characterization of diphtheria, tetanus and acellular pertussis antigens in human combined DTaP vaccines

Routine batch quality testing before vaccine release, notably for potency evaluation, still relies on animal use for several animal and human vaccines. In this context, the VAC2VAC project is a public-private consortium of 22 partners funded by EU whose the main objective is to reduce the number of animal used for batch testing by developing immunoassays that could be implemented for routine potency assessment of vaccines. This paper focused on the development of a Luminex-based multiplex assay to monitor the consistency of antigen quantity and quality throughout the production process of DTaP vaccines from two human vaccine manufacturers. Indepth characterized monoclonal antibody pairs were used for development and optimization of the Luminex assay with non-adsorbed and adsorbed antigens and with complete vaccine formulations from both manufacturers. The multiplex assay demonstrated good specificity, reproducibility and absence of cross-reactivity. Analysis of over and underdosed formulations, heat and H2O2-degraded products as well as batch to batch consistency of vaccines from both manufacturers brought the proof of concept for a future application of the multiplex immunoassay as a useful tool in the frame of DTaP vaccine quality control.

The role of urine and serum biomarkers in the early detection of ovarian epithelial tumours

Ovarian cancer (OC) is one of the leading causes of gynaecological cancer mortality in women worldwide. If detected at an early stage (I, II), OC has a 90% 5-year survival rate; nevertheless, symptoms are often hidden, leading to late-stage (III, IV) diagnosis and a poor prognosis. The current diagnostic procedures, such as a pelvic exam, transvaginal ultrasound, CA-125 blood tests, serum HE4 tests and multivariate index assays (MIA), are insufficient. Sadly, surgery is frequently required to confirm a positive diagnosis. Therefore, there has been an increased interest in different biomarkers using a non-invasive test as a tool for the earlier diagnosis of OC to resolve the need for precise and non-invasive diagnostic methods. This review article aims to investigate how biomarkers influence early OC detection and to emphasise the role of using a combination of serum biomarkers panel rather than a single biomarker. In addition, this review provides insights into the current serum biomarkers, urine biomarkers and other emerging biomarkers in the early detection of OC for better specificity and sensitivity and to improve the overall survival (OS) rate.

Current and emerging biomarkers in ovarian cancer diagnosis; CA125 and beyond

Ovarian cancer (OC) is one of the most common causes of cancer-related death in women worldwide. Its five-year survival rates are worse than the two most common gynecological cancers, cervical and endometrial. This is because it is asymptomatic in the early stages and usually detected in the advanced metastasized stage. Thus, survival is increasingly dependent on timely diagnosis. The delay in detection is contributed partly by the occurrence of non-specific clinical symptoms in the early stages and the lack of effective biomarkers and detection approaches. This underlines the need for biomarker identification and clinical validation, enabling earlier diagnosis, effective prognosis, and response to therapy. Apart from the traditional diagnostic biomarkers for OC, several new biomarkers have been delineated using advanced high-throughput molecular approaches in recent years. They are currently being clinically evaluated for their true diagnostic potential. In this chapter, we document the commonly utilized traditional screening markers and recently identified emerging biomarkers in OC diagnosis, focusing on secretory and protein biomarkers. We also briefly reviewed the recent advances and prospects in OC diagnosis.

Identification of two theranostic biomarker panels for epithelial ovarian cancer

BACKGROUND

Epithelial Ovarian cancer (EOC) is the leading cause of death associated with gynecologic tumors. Because the disease is asymptomatic in early-stage, the majority of patients are not diagnosed until late stages, highlighting the need for the development of novel diagnostic biomarkers. Mediators of tumoral microenvironment may affect EOC progression and resistance to treatment.

AIM OF THE STUDY

Analysis of serum proteins to identify a panel of theranostic biomarkers for EOC.

PATIENTS AND METHODS

Serum levels of 65 analytes were determined in EOC patients, and healthy controls with the ProcartaPlex Human Immune Monitoring 65-Plex Panel.

RESULTS

Twenty-one analytes: 7 cytokines (IFN-γ, IL-12p70, IL-13, IL-18 and TSLP), 7 chemokines (Eotaxin, eotaxin-2, IP-10, BLC, I-TAC, SDF-1α, and fractalkine), 2 growth factors (MMP-1, VEGF-α), and 5 soluble receptors (APRIL, CD40L, TWEAK, CD30 and TNFRII; were significantly differentially expressed between the two groups. ROC curves showed that only seven of them (IL-9, TNF-α, Eotaxin, IP-10, BLC, Fractalkine, and Tweak) had AUC values greater than 0.70 and thus had potential clinical utility. Moreover, five cytokines: IFN-γ, IL-1 β, IL-8, MIP-1β, and TNF-α are positively associated with patients who developed resistance to taxol-platinum-based chemotherapy (CT).

CONCLUSION

This study has revealed a first panel of 7 analytes (IL-9, TNF-α, Eotaxin, IP-10, BLC, Fractalkine and Tweak) that can be used for early detection of EOC and a second panel of five cytokines (IFN-γ, IL-1β, IL-8, MIP-1β, TNF-α) that can help clinicians to identify EOC patients who are at higher risk to develop resistance to CT of EOC.

Serum protein profiling of lung, pancreatic, and colorectal cancers reveals alcohol consumption-mediated disruptions in early-stage cancer detection

While the link between serum proteins and cancer has been studied in an effort to enable early-stage cancer detection, factors that might perturb this link has been poorly understood. To ask this question, we performed serum protein profiling on a prospective cohort of 601 individuals with or without lung, pancreatic, or colorectal cancers and identified ten distinct serum protein signatures with distinct link to the patient metadata. Importantly, we discovered that a positive history of alcohol consumption is a major factor that diminishes the sensitivity of serum protein-mediated liquid biopsy in early-stage malignancies, resulting in a 44% decline in the sensitivity of detecting American Joint Committee on Cancer (AJCC) stage I malignancies. Our data provide evidence that patient lifestyle can affect the sensitivity of liquid biopsy and suggest the potential need for abstinence from alcohol before measurement during serum protein-based cancer screening.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

BACKGROUND

Cervical cancer patients have a high risk of metastasis and a poor prognosis with shorter disease-free survival. Thus, novel biomarkers and feasible therapies urgently need to be discovered. Previous studies have shown that miR-95-3p plays crucial roles in several cancer types. However, the roles of miR-95-3p in cervical cancer remain unknown.

METHODS

The micro ribonucleic acid (miRNA) expression data and clinical characteristics of cervical cancer samples were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic-related miRNAs. The potential target genes of miR-95-3p were predicted by the TargetScan database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the target gene of miR-95-3p. The effects of miR-95-3p inhibition and overexpression on cell proliferation were inspected by cell counting kit-8 (CCK-8) assays and cell colony formation assays. Wound-healing assays and transwell assays were also used to examine cell migration ability in HeLa and SiHa cells.

RESULTS

MiR-95-3p was the only miRNA significantly associated with the poor prognosis of cervical squamous cell carcinoma. A further analysis suggested that vascular cell adhesion molecule 1 (VCAM1) is a target gene of miR-95-3p in cervical cancer, and miR-95-3p promotes the malignant behavior of cervical cancer cells by inhibiting the expression of VCAM1. The CCK-8 and cell colony assays showed that miR-95-3p downregulation significantly suppressed cell proliferation in the HeLa and SiHa cells. The transwell and wound-healing assays showed that miR-95-3p inhibition suppressed cell migration in the HeLa and SiHa cells. Further the Western blot analysis and the quantitative real-time-polymerase chain reaction (qRT-PCR) showed that the knockdown of miR-95-3p in HeLa cells resulted in increased VCAM1 expression. And VCAM1 was highly expressed in the paired adjacent normal cervical epithelium tissue samples, but lowly expressed in the cervical tumor tissue samples.

CONCLUSIONS

Our study was the first to show that miR-95-3p could serve as a prognostic biomarker of cervical cancer. Mechanistically, we discovered that miR-95-3p inhibited the expression of the cell adhesion molecule VCAM1 and thus promoted further tumor progression.

Black phosphorus nanosheets/poly(allylamine hydrochloride) based electrochemical immunosensor for the selective detection of human epididymis protein 4

In this work, an electrochemical immunosensor based on black phosphorus nanosheets (BPNS)/poly(allylamine hydrochloride) (PAH) nanocomposite modified glassy carbon electrode was developed for the detection of ovarian cancer biomarker HE4. PAH has been applied to retain BPNS in its original honeycomb structure and to anchor biomolecules electrostatically on the transducer surface. The as synthesized nanocomposite was characterized by zeta potential analysis, scanning electron microscopy, x-ray photoelectron spectroscopy, transmission electron microscopy, high-resolution transmission electron microscopy. Subsequently, the performance of the electrochemical immunosensor was evaluated through cyclic voltammetry, differential pulse voltammetry and electrochemical impedance spectroscopy. Under the optimal condition, the developed electrochemical immunosensor permitted to detect HE4 with a linear range of 0.1-300 ng ml^-1and a detection limit of 0.01 ng ml^-1. The developed sensor exhibited good selectivity and specificity to HE4 with negligible interference effect from common biomolecules like bovine serum albumin, lysozyme, protamine, glucose, fructose, hemoglobin and fetal bovine serum. Further, practical application of developed electrochemical immunosensor was demonstrated in spiked human serum which showed satisfactory recovery percentages.

Biomarkers in Gynecologic Tumors

Gynecologic malignancies are one of the most frequent cancers amongst women. Biomarkers are crucial for the differential diagnosis of adnexal masses; however, their potential for diagnosis is limited. In the era of difficulty in ovarian cancer screening, novel biomarkers are defined, but CA125 still remains the most valuable one. Circulating tumor DNAs, DNA hypermethylation, metabolites, microRNAs, and kallikreins have recently turned out as ovarian cancer biomarkers and are being applied to clinical practice. For uterine cancer, genomic classification has now been described, it will be used as a prognostic tool. In this chapter, we describe ovarian, endometrial, and cervical cancer biomarkers in detail.

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

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

Circulating ADAMTS13 Levels Are Associated with an Increased Occurrence of Obstructive Sleep Apnea

Background and Aims. Obstructive sleep apnea (OSA) is strongly associated with obesity, metabolic diseases, coronary artery disease (CAD), stroke, hypertension, and other disorders. This study assessed the relationship between circulating a disintegrin and metalloprotease with a thrombospondin type 1 motif, member 13 (ADAMTS13) levels and the presence of OSA. Materials and Methods. This cross-sectional study included a total of 223 patients. We used a powerful high-throughput multiplexed immunobead-based assay to detect circulating levels of ADAMTS13. The associations between circulating ADAMTS13 levels and OSA were evaluated by multivariate logistic regression analysis. Results. Circulating ADAMTS13 levels were significantly elevated in patients with OSA compared with controls (0.8 vs. 2.7 μg/mL, respectively, $P<0.001$ ). After adjusting for confounding factors, circulating ADAMTS13 levels were significantly independently associated with the presence of OSA ( $\text{odds}\text{ratio}=9.96$ , 95% confidence interval (CI) =4.11–24.13, $P<0.001$ ). Furthermore, circulating ADAMTS13 levels showed discriminatory accuracy in assessing the presence of OSA (area under the curve: 0.87, 95% CI 0.81–0.93, $P<0.001$ ). Conclusion. Circulating ADAMTS13 levels were significantly correlated with the presence of OSA. ADAMTS13 may therefore function as a novel biomarker for monitoring the development and progression of OSA.

Stacking Machine Learning Algorithms for Biomarker-Based Preoperative Diagnosis of a Pelvic Mass

Simple Summary

It is critical for women who are diagnosed with a pelvic mass, or an ovarian cyst to be accurately assessed for their risk of having an ovarian malignancy. Accurate risk stratification for these women will allow for appropriate triage and referral to centers best equipped to treat women diagnosed with ovarian cancer. In this study, machine learning (ML) algorithms were used to determine the optimal combination of biomarkers for prediction of malignancy in women presenting with a pelvic mass. Nine unique ML algorithms were employed to evaluate age, menopausal status, race, and levels of 67 biomarkers from serum, urine, and plasma samples prospectively collected in a cohort 140 women with a variety of pelvic mass diagnoses benign and malignant. A complex statistical algorithm using serum levels of CA125, HE4 and transferrin provided greater than 93% sensitivity and specificity for the preoperative prediction of malignancy in women presenting with a pelvic mass.

Abstract

Objective: To identify the most predictive parameters of ovarian malignancy and develop a machine learning (ML) based algorithm to preoperatively distinguish between a benign and malignant pelvic mass. Methods: Retrospective study of 70 predictive parameters collected from 140 women with a pelvic mass. The women were split into a 3:1 “training” to “testing” dataset. Feature selection was performed using Gini impurity through an embedded random forest model and principal component analysis. Nine unique ML classifiers were assessed across a variety of model-specific hyperparameters using 25 bootstrap resamples of the training data. Model predictions were then combined into an ensemble stack by LASSO regression. The final ensemble stack and individual classifiers were then applied to the testing dataset to assess model performance. Results: Feature selection identified HE4, CA125, and transferrin as three predictive parameters of malignancy. Assessment of the ensemble stack on the testing dataset outperformed all individual ML classifiers in predicting malignancy. The ensemble stack demonstrated an accuracy of 97.1%, a receiver operating characteristic (ROC) area under the curve (AUC) of 0.951, and a sensitivity of 93.3% with a specificity of 100%. Conclusions: Combining the measurement of three distinct biomarkers with the stacking of multiple ML classifiers into an ensemble can provide valuable preoperative diagnostic predictions for patients with a pelvic mass.

WFDC Protein: A Promising Diagnosis Biomarker of Ovarian Cancer

An initial diagnosis of cancer is usually based on symptoms, abnormal physical examination and imaging tests. Ovarian cancer is difficult to be diagnosed timely due to the nonspecific symptoms, thus resulting in the high-risk mortality. Despite of the various diagnostic methods, there is still no reliable diagnostic test. Clinically, carbohydrate antigen 125(CA125) is widely recognized as a diagnosis biomarker of ovary cancer. However, CA125 is not sensitive to detect the ovary cancer at the early stage. It is essential to explore other potential biomarkers. Human epididymis protein 4 (HE4) in the whey/four-disulfide core (WFDC) proteins family shows satisfactory sensitivity in the early diagnosis of ovary cancer. In this present review, we summarized the important effects of WFDC family proteins on the proliferation, apoptosis and migration of ovary cancer and intended to provide more evidence to explore the possibility of WFDC protein as a diagnosis biomarker.

An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures

Tumours are abnormal growths of cells that reproduce by redirecting essential nutrients and resources from surrounding tissue. Changes to cell metabolism that trigger the growth of tumours are reflected in subtle differences between the chemical composition of healthy and malignant cells. We used LA-ICP-MS imaging to investigate whether these chemical differences can be used to spatially identify tumours and support detection of primary colorectal tumours in anatomical pathology. First, we generated quantitative LA-ICP-MS images of three colorectal surgical resections with case-matched normal intestinal wall tissue and used this data in a Monte Carlo optimisation experiment to develop an algorithm that can classify pixels as tumour positive or negative. Blinded testing and interrogation of LA-ICP-MS images with micrographs of haematoxylin and eosin stained and Ki67 immunolabelled sections revealed Monte Carlo optimisation accurately identified primary tumour cells, as well as returning false positive pixels in areas of high cell proliferation. We analysed an additional 11 surgical resections of primary colorectal tumours and re-developed our image processing method to include a random forest regression machine learning model to correctly identify heterogenous tumours and exclude false positive pixels in images of non-malignant tissue. Our final model used over 1.6 billion calculations to correctly discern healthy cells from various types and stages of invasive colorectal tumours. The imaging mass spectrometry and data analysis methods described, developed in partnership with clinical cancer researchers, have the potential to further support cancer detection as part of a comprehensive digital pathology approach to cancer care through validation of a new chemical biomarker of tumour cells.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

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.

CA125 and Ovarian Cancer: A Comprehensive Review

Simple Summary

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

Abstract

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

Biomarkers and Strategies for Early Detection of Ovarian Cancer

Early detection of ovarian cancer remains an important unmet medical need. Effective screening could reduce mortality by 10%-30%. Used individually, neither serum CA125 nor transvaginal sonography (TVS) is sufficiently sensitive or specific. Two-stage strategies have proven more effective, where a significant rise above a woman's baseline CA125 prompts TVS and an abnormal sonogram prompts surgery. Two major screening trials have documented that this strategy has adequate specificity, but sensitivity for early-stage (I-II) disease must improve to have a greater impact on mortality. To improve the first stage, different panels of protein biomarkers have detected cases missed by CA125. Autoantibodies against TP53 have detected 20% of early-stage ovarian cancers 8 months before elevation of CA125 and 22 months before clinical diagnosis. Panels of autoantibodies and antigen-autoantibody complexes are being evaluated with the goal of detecting >90% of early-stage ovarian cancers, alone or in combination with CA125, while maintaining 98% specificity in control subjects. Other biomarkers, including micro-RNAs, ctDNA, methylated DNA, and combinations of ctDNA alterations, are being tested to provide an optimal first-stage test. New technologies are also being developed with greater sensitivity than TVS to image small volumes of tumor.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

MicroRNA as Biomarker in Ovarian Cancer Management: Advantages and Challenges

Ovarian cancer is the most prevalent gynecological malignancy affecting women throughout the globe. Ovarian cancer has several subtypes, including epithelial ovarian cancer (EOC) with a whopping incidence rate of 239,000 per year, making it the sixth most common gynecological malignancy worldwide. Despite advancement of detection and therapeutics, death rate accounts for 152,000 per annum. Several protein-based biomarkers such as CA125 and HE4 are currently being used for diagnosis, but their sensitivity and specificity for early detection of ovarian cancer are under question. MicroRNA (a small noncoding RNA molecule that participates in post-transcription regulation of gene expression) and its functional deregulation in most cancers have been discovered in the previous two decades. Studies support that miRNA deregulation has an epigenetic component as well. Aberrant miRNA expression is often correlated with the form of EOC tumor, histological grade, prognosis, and FIGO stage. In this review, we addressed epigenetic regulation of miRNAs, the latest research on miRs as a biomarker in the detection of EOC, and tailored assays to use miRNAs as a biomarker in ovarian cancer diagnosis.

Retrospective Study of the Epidemiology, Pathology, and Therapeutic Management in Patients With Mucinous Ovarian Tumors

Aim:

We sought to determine the epidemiology of mucinous ovarian tumors, the correlation between serum biomarkers and tumor status, and the outcomes of the management in different subtypes of mucinous ovarian tumors in a Chinese surgical cohort.

Methods:

A total of 513 patients were enrolled from January 2009 to May 2017. The number of patients who had benign mucinous ovarian tumor, borderline mucinous ovarian tumor, or malignant mucinous ovarian tumor was pathologically quantified. All patients underwent surgery with or without postoperative adjuvant therapy. Prognosis was analyzed based on clinicopathological characteristics and the type of treatment received. Hyperthermic intraperitoneal chemotherapy efficacy and adverse effects in patients were also explored.

Results:

In all, 383 (75%) patients were diagnosed as having benign mucinous ovarian tumor, 76 (14%) patients with borderline mucinous ovarian tumor, and 54 (5%) patients with malignant mucinous ovarian tumor. Levels of serum biomarkers increased as the tumors became more malignant. Patients with stage IA and IC (unilateral) malignant mucinous ovarian tumor who underwent fertility conserving surgery did not experience poorer prognoses when compared to those who received non-fertility conserving surgery. Hyperthermic intraperitoneal chemotherapy followed by chemotherapy significantly influenced survival rates in patients with a ruptured malignant mucinous ovarian tumor.

Conclusions:

Levels of serum tumor markers, carbohydrate antigen 125, carbohydrate antigen 199, carbohydrate antigen 242, and carcinoembryonic antigen may be useful in monitoring for malignant transformation. Fertility conserving surgery might be a preferable surgical procedure for patients with malignant mucinous ovarian tumor at early stage (IA and IC [unilateral]). Hyperthermic intraperitoneal chemotherapy appears to be a well-tolerated and promising postoperative adjuvant.

EMMPRIN: A potential biomarker for predicting the presence of obstructive sleep apnea

BACKGROUND

Obstructive Sleep Apnea (OSA) is a sleep-related breathing disorder which is strongly associated with the development of cardiovascular diseases. The aim of the study was to investigate the association between circulating extracellular matrix metalloproteinase inducer (EMMPRIN) and OSA risk.

METHODS

This was a cross-sectional study in which a total of 144 patients were recruited. Demographic data, blood biochemical parameters and polysomnography parameters were collected. We used a powerful high-throughput Multiplex Immunobead Assay technique to simultaneously detect circulating levels of EMMPRIN and E-selectin.

RESULTS

Circulating levels of EMMPRIN were significantly increased in patients with OSA compared to controls (7.58[6.21-8.80] vs 1.47[0.80-5.91] ng/ml, P < 0.001). After adjusting for confounding factors, we found that circulating EMMPRIN levels were independently associated with the presence of OSA (odds ratio[OR] = 2.240, 95% confidence interval [CI] = 1.391-3.607, P < 0.001). Furthermore, circulating EMMPRIN showed greater discriminatory accuracy in predicting the presence of OSA (AUC:0.904).

CONCLUSIONS

Circulating EMMPRIN levels were significantly increased in patients with OSA, and may be a novel marker for predicting the risk of OSA.

Novel protein and immune response markers of human serous tubal intraepithelial carcinoma of the ovary

Ovarian cancer is the leading cause of death among gynecologic diseases in the USA and Europe. High-grade serous carcinoma (HGSC) of the ovary, the most aggressive type of ovarian cancer, is typically diagnosed at advanced stages when the 5-year survival is dismal. Since the cure rate for stage I HGSC is high, early detection of localized initial disease may improve patient outcomes. Serous tubal intraepithelial carcinoma (STIC) is considered to be a precursor lesion of HGSC. Discovery of biomarkers associated with STIC could aid in the development of an HGSC screening algorithm. Using immunohistochemical staining, we have demonstrated overexpression of UCHL1, ADAMTS13, and GAPDH in patients' STIC lesions, but not in cancer-free fallopian tubes. We additionally demonstrated a marked increase of T cells in perineoplastic stroma surrounding STIC lesions (largely CD4 + cells), but not in normal fallopian tubes and HGSC. FOXP3 + T regulatory cells are absent in STIC lesions but are present in HGSC. These observations indicate the microenvironment surrounding a STIC lesion may be immune promoting in contrast to the immune suppressive microenvironment of invasive carcinoma. In summary, we have identified UCHL1, ADAMTS13, and GAPDH as novel potentially useful markers associated with early stages of HGSC tumorigenesis and possibly contribute to STIC immunogenicity. The lack of immune suppression in the STIC microenvironment indicates that the immune system can still recognize and keep STIC controlled at this stage of the tumor development.

Simultaneous detection of fungal (1,3)-β-d-glucan and procalcitonin using a dual-label time-resolved fluorescence immunoassay

Neonatal infectious diseases are a serious threat to the health of newborns. The aim was to establish a new detection method for the simultaneous measurement of (1,3)-β-d-glucan and procalcitonin in serum for the early screening and efficacy testing of neonatal infectious diseases. We established a sandwich dual-label time-resolved fluorescence immunoassay (TRFIA): anti-(1,3)-β-d-glucan/procalcitonin antibodies immobilized on 96-well plates captured (1,3)-β-d-glucan/procalcitonin antigens and then banded together with the detection antibodies labeled with europium(III) (Eu³⁺ )/samarium(III) (Sm³⁺ ) chelates. Finally, time-resolved fluorometry was used to measure the fluorescence intensity. The linear correlation coefficient (R² ) of the (1,3)-β-d-glucan standard curve was 0.9913, and the R² of the procalcitonin standard curve was 0.9911. The detection sensitivity for (1,3)-β-d-glucan was 0.4 pg/mL (dynamic range: 0.6-90 pg/mL), and the average recovery was 101.55%. The detection sensitivity for procalcitonin was 0.02 ng/mL (dynamic range: 0.05-95 ng/mL), and the average recovery was 104.61%. There was a high R² between the present TRFIA method and a commercially available assay (R²  = 0.9829 for (1,3)-β-d-glucan and R²  = 0.9704 for procalcitonin). Additionally, the cutoff values for (1,3)-β-d-glucan and procalcitonin were 23.95 pg/mL and 0.055 ng/mL, respectively. The present TRFIA method has high sensitivity, accuracy, and specificity and is an effective method for early screening and efficient testing of neonatal invasive fungal infection.

Performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of ovarian cancer: a systematic review and meta-analysis

BACKGROUND

To evaluate the diagnostic performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for ovarian cancer.

PATIENTS AND METHODS

A thorough research was conducted in PubMed, Web of Science and Embase (until November 2018) to identify studies evaluating the accuracy of MALDI-TOF-MS for ovarian cancer. Using Meta-Disc1.4, Review Manager 5.3 and Stata 15.1 software to analyze the pooled results: sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) show the overall performance of MALDI-TOF-MS.

RESULTS

Eighteen studies were included in the meta-analysis. Methodological quality analysis of the included studies showed that these articles were at low risk of bias and applicability concerns in total. Summary estimates of the diagnostic parameters were as follows: sensitivity, 0.77 (95% CI: 0.73-0.80); specificity, 0.72 (95% CI: 0.70-0.74), PLR, 2.80 (95% CI: 2.41-3.24); NLR, 0.30 (95% CI: 0.22-0.40) and DOR, 10.71 (95% CI: 7.81-14.68). And the AUC was 0.8336. Egger's test showed no significant publication bias in this meta-analysis.

CONCLUSION

In conclusion, MALDI-TOF-MS shows a good ability for diagnosing ovarian cancer. Further evaluation and optimization of standardized procedures are necessary for complete relying on MALDI-TOF-MS to diagnose ovarian cancer.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for cancer.

Multi-biomarker panel signature as the key to diagnosis of ovarian cancer

Early detection of ovarian cancer has been a challenge to manage the high mortality rate caused by this deadly disease. The trends in mortality have been reduced by the scientific contributions from the corners across the globe, however accounting for the fifth leading cause of gynecological mortality. The complexities in the clinical presentation, origin of tumor, and gene expression profiles had added to much difficulty in understanding and diagnosis of the disease. Stage 1 diagnosis of ovarian cancer improves the 5-year survival rate to around 92%. Cancer antigen-125 (CA-125) is the gold standard tumor marker found at abnormally high levels in the blood of many women in ovarian cancer. However, many non-cancerous conditions exhibit high levels of CA-125 and several women have normal CA-125 level in the early stage of ovarian cancer, suggesting CA-125 biomarker is not specific enough for the screening of early stage ovarian cancer. In addition, several other biomarkers, including HE4 have been added in the diagnostic field for higher sensitivity and specificity in the diagnosis and progression of ovarian cancer. HE4 is a prospective single serum biomarker which has been approved by the FDA to monitor the disease progression in epithelial ovarian cancer. However, owing to low sensitivity and specificity, combination of a panel of biomarkers has been proposed in the diagnosis of the disease. Based on extensive biomarkers research findings, here we discuss current trends in diagnostic approaches and updated potential several panels of cancer biomarkers for early detection of ovarian cancer. It has been recently reported that CA125 in combinations with two or more biomarkers have outperformed single biomarker assays for early detection of the disease. Moreover, CA-125 with CA 19–9, EGFR, G-CSF, Eotaxin, IL-2R, cVCAM, MIF improved the sensitivity with 98.2 % and specificity of 98.7% in early stage detection of ovarian cancer. Overall, this review demonstrates a panel of biomarkers signature as the potential tool for prototype development in future and other advanced approaches for early diagnosis of ovarian cancer to avoid false-diagnosis and excessive cost.

Ovarian cancer screening in the general population

Background Ovarian carcinoma is a poor prognosis cancer mainly due to its late diagnosis. Its incidence is relatively low but mortality is high. The symptomatology is only slightly specific, which complicates diagnostic management. It would therefore be interesting to be able to establish a diagnosis as early as possible in order to improve the prognosis of patients suffering from ovarian cancer. Materials and methods Currently, the combination of an ultrasound examination with a cancer antigen (CA)-125 assay is the most effective diagnostic technique, but not already admitted as a screening method. Therefore, we realized an exhaustive analysis of the most important studies in the last 15 years, in order to find new approaches in ovarian cancer screening. Results The age for initiating screening and its frequency are issues that are not fully resolved. The false positives and morbidity that result from screening are currently notable limitations. Conclusions The latest data do not support effective screening in the general population.

An Improved Prediction Model for Ovarian Cancer Using Urinary Biomarkers and a Novel Validation Strategy

This study was designed to analyze urinary proteins associated with ovarian cancer (OC) and investigate the potential urinary biomarker panel to predict malignancy in women with pelvic masses. We analyzed 23 biomarkers in urine samples obtained from 295 patients with pelvic masses scheduled for surgery. The concentration of urinary biomarkers was quantitatively assessed by the xMAP bead-based multiplexed immunoassay. To identify the performance of each biomarker in predicting cancer over benign tumors, we used a repeated leave-group-out cross-validation strategy. The prediction models using multimarkers were evaluated to develop a urinary ovarian cancer panel. After the exclusion of 12 borderline tumors, the urinary concentration of 17 biomarkers exhibited significant differences between 158 OCs and 125 benign tumors. Human epididymis protein 4 (HE4), vascular cell adhesion molecule (VCAM), and transthyretin (TTR) were the top three biomarkers representing a higher concentration in OC. HE4 demonstrated the highest performance in all samples with OC (mean area under the receiver operating characteristic curve (AUC) 0.822, 95% CI: 0.772–0.869), whereas TTR showed the highest efficacy in early-stage OC (AUC 0.789, 95% CI: 0.714–0.856). Overall, HE4 was the most informative biomarker, followed by creatinine, carcinoembryonic antigen (CEA), neural cell adhesion molecule (NCAM), and TTR using the least absolute shrinkage and selection operator (LASSO) regression models. A multimarker panel consisting of HE4, creatinine, CEA, and TTR presented the best performance with 93.7% sensitivity (SN) at 70.6% specificity (SP) to predict OC over the benign tumor. This panel performed well regardless of disease status and demonstrated an improved performance by including menopausal status. In conclusion, the urinary biomarker panel with HE4, creatinine, CEA, and TTR provided promising efficacy in predicting OC over benign tumors in women with pelvic masses. It was also a non-invasive and easily available diagnostic tool.

Multi-institutional Validation Study of Pancreatic Cyst Fluid Protein Analysis for Prediction of High-risk Intraductal Papillary Mucinous Neoplasms of the Pancreas

OBJECTIVE

Preliminary work by our group suggested that proteins within the pancreatic cyst fluid (CF) may discriminate degree of IPMN dysplasia. We sought to externally validate these markers and determine whether their inclusion in a preoperative clinical nomogram could increase diagnostic accuracy.

SUMMARY BACKGROUND DATA

IPMN is the most common radiographically identifiable precursor to pancreatic cancer; however, the timing and frequency of its malignant progression are unknown, and there are currently no reliable preoperative tests that can determine the grade of dysplasia in IPMN.

METHODS

Clinical and radiographic data, as well as CF samples, were obtained from 149 patients who underwent resection for IPMN at 1 of 3 institutions. High-risk disease was defined as the presence of high-grade dysplasia or invasive carcinoma. Multianalyte bead array analysis (Luminex) of CF was performed for 4 protein markers that were previously associated with high-risk disease. Logistic regression models were fit on training data, with and without adjustment for a previously developed clinical nomogram and validated with an external testing set. The models incorporating clinical risk score were presented graphically as nomograms.

RESULTS

Within the group of 149 resected patients, 89 (60%) had low-risk disease, and 60 (40%) had high-risk disease. All 4 CF markers (MMP9, CA72-4, sFASL, and IL-4) were overexpressed in patients with high-risk IPMN (P < 0.05). Two predictive models based on preselected combinations of CF markers had concordance indices of 0.76 (Model-1) and 0.80 (Model-2). Integration of each CF marker model into a previously described clinical nomogram leads to increased discrimination compared with either the CF models or nomogram alone (c-indices of 0.84 and 0.83, respectively).

CONCLUSIONS

This multi-institutional study validated 2 CF protein marker models for preoperative identification of high-risk IPMN. When combined with a clinical nomogram, the ability to predict high-grade dysplasia was even stronger.

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.

Safety and Outcome Measures of First-in-Human Intraperitoneal α Radioimmunotherapy With 212Pb-TCMC-Trastuzumab

PURPOSE

One-year monitoring of patients receiving intraperitoneal (IP) Pb-TCMC-trastuzumab to provide long-term safety and outcome data. A secondary objective was to study 7 tumor markers for correlation with outcome.

METHODS

Eighteen patients with relapsed intra-abdominal human epidermal growth factor receptor-2 expressing peritoneal metastases were treated with a single IP infusion of Pb-TCMC-trastuzumab, delivered <4 h after 4 mg/kg IV trastuzumab. Seven tumor markers were studied for correlation with outcome.

RESULTS

Six dose levels (7.4, 9.6, 12.6, 16.3, 21.1, 27.4 MBq/m) were well tolerated with early possibly agent-related adverse events being mild, transient, and not dose dependent. These included asymptomatic, abnormal laboratory values. No late renal, liver, cardiac, or other toxicity was noted up to 1 year. There were no clinical signs or symptoms of an immune response to Pb-TCMC-trastuzumab, and assays to detect an immune response to this conjugate were negative for all tested. Tumor marker studies in ovarian cancer patients showed a trend of decreasing Cancer antigen 72-4 (CA 72-4) aka tumor-associated glycoprotein 72 (TAG-72) and tumor growth with increasing administered radioactivity. Other tumor markers, including carbohydrate antigen (CA125), human epididymis protein 4 (HE-4), serum amyloid A (SAA), mesothelin, interleukin-6 (IL-6), and carcinoembryonic antigen (CEA) did not correlate with imaging outcome.

CONCLUSIONS

IP Pb-TCMC-trastuzumab up to 27 MBq/m seems safe for patients with peritoneal carcinomatosis who have failed standard therapies. Serum TAG-72 levels better correlated to imaging changes in ovarian cancer patients than the more common tumor marker, CA125.

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

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

Complementary Longitudinal Serum Biomarkers to CA125 for Early Detection of Ovarian Cancer

Early detection of ovarian cancer has the potential to impact mortality. A multimodal screening strategy where rising CA125 values over time, analyzed with the risk of ovarian cancer algorithm (ROCA), triggers transvaginal sonography and possible surgery has high sensitivity and specificity, but still fails to detect the 20% of early-stage cases that do not express CA125. Use of multiple biomarkers could detect cases missed by CA125. We have studied the sensitivity and lead time of a multi-marker panel (CA125, HE4, MMP-7, and CA 72-4) compared with CA125 alone. We used PRoBE design principles to select preclinical longitudinal specimens from 75 women (50 screen-positive, 25 screen-negative) who developed invasive epithelial ovarian cancer (3-5 serial specimens each) and 547 corresponding healthy controls (1-10 serial specimens each) from the ovarian cancer screening trial, UKCTOCS, in a blinded fashion. We measured the multi-marker concentrations in ultra-low serum volumes (16 μL) utilizing multiplexed bead-based immunoassays with low detection limits, high inter- and intra-assay precision, negligible cross-reactivity, and good correlation with standard immunoassays. While, at least one of the complementary biomarkers rose with CA125 in 44% (22/50) of screen-positive cases, there was no advantage in lead time over CA125. Therefore, we developed single-marker longitudinal algorithms (ROCA-like) to determine the presence of a change point to distinguish between the cases and controls. Using these algorithms, at 98% specificity, HE4 and CA72-4 identified 16% (4/25) of screen-negative cases, while MMP-7 identified none. Taken together, HE4 and CA72-4 show promise as complementary biomarkers to CA125 for longitudinal screening.

Human epithelial ovarian cancer cells expressing CD105, CD44 and CD106 surface markers exhibit increased invasive capacity and drug resistance

The high rate of mortality associated with ovarian cancer (OC) is due in part to the development of resistance to chemotherapy, which allows the resistant tumour cells to invade and metastasise. Clarifying the mechanistic basis for drug resistance may reveal novel avenues for treatment. The present study investigated the mechanism of paclitaxel (PTX) resistance in human epithelial OC by evaluating the expression of stem cell-associated cell surface markers endoglin (CD105), CD44 antigen and vascular cell adhesion molecule 1 (CD106), in association with the malignant potential of the human OC OVCAR3 cell line and its PTX-resistant derivative OC3/TAX300. The expression of CD105, CD44 and CD106 was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and flow cytometry, and cell invasion was evaluated using a Transwell invasion assay. CD105, CD44 and CD106 levels were increased in OC3/TAX300 cells compared with the OVCAR3 cells, as determined by flow cytometry (P<0.01) and RT-qPCR (P<0.05). Additionally, the number of invading cells was increased in the OC3/TAX300 group compared with the OVCAR3 group (54.7±6.65 vs. 31.8±6.55; P<0.01). A western blot analysis of cell surface marker expression in 80 clinical epithelial OC tissue samples, differing in terms of sensitivity to drug treatments, disease stage and degree of differentiation, revealed that high CD105, CD44 or CD106 expression was associated with drug resistance, advanced disease stage, poor differentiation and high rate of recurrence. These data indicated that exposure to high doses of PTX enhanced the stem-like properties of OC cells, which are associated with drug resistance and invasion and lead to poor prognosis due to induced chemoresistance and/or metastasis. Therefore, CD105, CD44 and CD106 may serve as potential stem cell-associated cell surface and prognostic markers, and therapeutic targets, in OC.

The contribution and perspectives of proteomics to uncover ovarian cancer tumor markers

Despite all the advances in understanding the mechanisms involved in ovarian cancer (OC) development, many aspects still need to be unraveled and understood. Tumor markers (TMs) are of special interest in this disease. Some aspects of clinical management of OC might be improved by the use of validated TMs, such as differentiating subtypes, defining the most appropriate treatment, monitoring the course of the disease, or predicting clinical outcome. The Food and Drug Administration (FDA) has approved a few TMs for OC: CA125 (cancer antigen 125; monitoring), HE4 (Human epididymis protein; monitoring), ROMA (Risk Of Malignancy Algorithm; HE4+CA125; prediction of malignancy) and OVA1 (Vermillion's first-generation Multivariate Index Assay [MIA]; prediction of malignancy). Proteomics can help advance the research in the field of TMs for OC. A variety of biological materials are being used in proteomic analysis, among them tumor tissues, interstitial fluids, tumor fluids, ascites, plasma, and ovarian cancer cell lines. However, the discovery and validation of new TMs for OC is still very challenging. The enormous heterogeneity of histological types of samples and the individual variability of patients (lifestyle, comorbidities, drug use, and family history) are difficult to overcome in research protocols. In this work, we sought to gather relevant information regarding TMs, OC, biological samples for proteomic analysis, as well as markers and algorithms approved by the FDA for use in clinical routine.