Proteomic-based discovery and characterization of glycosylated eosinophil-derived neurotoxin and COOH-terminal osteopontin fragments for ovarian cancer in urine

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

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.

Glycosylation and its research progress in endometrial cancer

Endometrial cancer (EC) is one of the most common tumors in the female reproductive system, which seriously threatens women's health, particularly in developed countries. 13% of the patients with EC have a poor prognosis due to recurrence and metastasis. Therefore, identifying good predictive biomarkers and therapeutic targets is critical to enable the early detection of metastasis and improve the prognosis. For decades, extensive studies had focused on glycans and glycoproteins in the progression of cancer. The types of glycans that are covalently attached to the polypeptide backbone, usually via nitrogen or oxygen linkages, are known as N‑glycans or O‑glycans, respectively. The degree of protein glycosylation and the aberrant changes in the carbohydrate structures have been implicated in the extent of tumorigenesis and reported to play a critical role in regulating tumor invasion, metabolism, and immunity. This review summarizes the essential biological role of glycosylation in EC, with a focus on the recent advances in glycomics and glycosylation markers, highlighting their implications in the diagnosis and treatment of EC.

OUP accepted manuscript

Currently, the only definitive method for diagnosing ovarian cancer involves histological examination of tissue obtained at time of surgery or by invasive biopsy. Blood has traditionally been the biofluid of choice in ovarian cancer biomarker discovery; however, there has been a growing interest in exploring urinary biomarkers, particularly as it is non-invasive. In this systematic review, we present the diagnostic accuracy of urinary biomarker candidates for the detection of ovarian cancer. A comprehensive literature search was performed using the MEDLINE/PubMed and EMBASE, up to 1 April 2021. All included studies reported the diagnostic accuracy using sensitivity and/or specificity and/or receiver operating characteristics (ROC) curve. Risk of bias and applicability of included studies were assessed using the QUADAS-2 tool. Twenty-seven studies were included in the narrative synthesis. Protein/peptide biomarkers were most commonly described (n = 18), with seven studies reporting composite scores of multiple protein-based targets. The most frequently described urinary protein biomarker was HE4 (n = 5), with three studies reporting a sensitivity and specificity > 80%. Epigenetic (n = 1) and metabolomic/organic compound biomarkers (n = 8) were less commonly described. Overall, six studies achieved a sensitivity and specificity of >90% and/or an AUC > 0.9. Evaluation of urinary biomarkers for the detection of ovarian cancer is a dynamic and growing field. Currently, the most promising biomarkers are those that interrogate metabolomic pathways and organic compounds, or quantify multiple proteins. Such biomarkers require external validation in large, prospective observational studies before they can be implemented into clinical practice.

Quantitative proteomic analysis of glycosylated proteins enriched from urine samples with magnetic ConA nanoparticles identifies potential biomarkers for small cell lung cancer

Lung cancer has high morbidity and mortality and small cell lung cancer (SCLC) is a highly invasive malignant tumor with a very unfavorable survival rate. Early diagnosis and treatment can result in better prognosis for the SCLC patients but current diagnostic methods are either invasive or incapable for large-scale screen. Therefore, discovering biomarkers for early diagnosis of SCLC is of importance. In this work, we covalently coupled Concanavalin A (ConA) to functionalized magnetic nanoparticles to obtain magnetic ConA-nanoparticles (ConA-NPs) for the enrichment of glycosylated proteins. We then purified glycosylated proteins in 36 urine samples from 9 healthy controls, 9 SCLC patients, 9 lung adenocarcinoma (LUAD) patients, and 9 lung squamous cell carcinoma (LUSC) patients. The purified glycosylated proteins were digested and analyzed by LC-MS/MS for identification and quantification. Among the 398 identified proteins, 20, 15, and 1 glycosylated protein(s), respectively, were upregulated in the urine of SCLC, LUAD, and LUSC patients. Immunoblotting experiments further demonstrated that cathepsin C and transferrin were significantly upregulated in the ConA-NP purified urine of SCLC patients. This work suggests that glycosylated cathepsin C and transferrin might be able to serve as potential biomarkers for the noninvasive diagnosis of SCLC patients.

The commutability of enzyme linked immunosorbent assays for the quantification of serum eosinophil-derived neurotoxin (EDN)

Eosinophil-derived neurotoxin (EDN) is a surrogate biomarker of eosinophil activation and has considerable potential as a precision medicine biomarker in diseases where eosinophils may play a causative role. Clinical data for EDN have been generated using different quantitative immunoassays, but comparisons between these individual data sets are challenging as no internationally recognised EDN standards or orthogonal methods exist. In this study we aimed to compare commercial EDN assays from ALPCO, MBL, LSBio and CUSABIO for sample commutability. Firstly, we analytically validated the ALPCO enzyme linked immunosorbent assay (ELISA) and demonstrated appropriate analytical characteristics, including an intra/inter-assay precision coefficient-of-variation of between 1.9 and 6.8%. EDN purified from blood proved to be a good quality control material, whereas recombinant EDN, expressed in E.coli, did not react in the ALPCO immunoassay. Using healthy and asthma patient serum samples we confirmed that the ALPCO assay correlated well with the MBL assay, with a coefficient of determination (R²) of 0.92. However, the results from LSBio and CUSABIO assays were not commutable to the other assays.

Urinary Protein and Peptide Markers in Chronic Kidney Disease

Chronic kidney disease (CKD) is a non-specific type of kidney disease that causes a gradual decline in kidney function (from months to years). CKD is a significant risk factor for death, cardiovascular disease, and end-stage renal disease. CKDs of different origins may have the same clinical and laboratory manifestations but different progression rates, which requires early diagnosis to determine. This review focuses on protein/peptide biomarkers of the leading causes of CKD: diabetic nephropathy, IgA nephropathy, lupus nephritis, focal segmental glomerulosclerosis, and membranous nephropathy. Mass spectrometry (MS) approaches provided the most information about urinary peptide and protein contents in different nephropathies. New analytical approaches allow urinary proteomic-peptide profiles to be used as early non-invasive diagnostic tools for specific morphological forms of kidney disease and may become a safe alternative to renal biopsy. MS studies of the key pathogenetic mechanisms of renal disease progression may also contribute to developing new approaches for targeted therapy.

New Predictive Biomarkers for Ovarian Cancer

Ovarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, with the development of chemoresistance in up to 75% of patients with subsequent poor treatment response and reduced survival. Therefore, there is a critical need to revisit existing, and identify potential biomarkers that could lead to the development of novel and more effective predictors for ovarian cancer diagnosis and prognosis. The capacity of these biomarkers to predict the existence, stages, and associated therapeutic efficacy of ovarian cancer would enable improvements in the early diagnosis and survival of ovarian cancer patients. This review not only highlights current evidence-based ovarian-cancer-specific prognostic and diagnostic biomarkers but also provides an update on various technologies and methods currently used to identify novel biomarkers of ovarian cancer.

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers.

METHODS AND FINDINGS

Clinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I-II and 97 stage III-IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal-Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I-II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843-0.957) and 0.926 (95% CI 0.843-1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903-0.969) and the validation (95% CI 0.888-0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I-II patients from controls, with AUC = 0.992 (95% CI 0.983-1.000), SN = 0.963 (95% CI 0.913-1.000), and SP = 0.967 (95% CI 0.924-1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I-IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy.

CONCLUSIONS

We have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC ('elevated' or 'normal'). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Ovarian Cancer Biomarkers: Moving Forward in Early Detection

Ovarian cancer is a silent cancer which rate survival mainly relays in early stage detection. The discovery of reliable ovarian cancer biomarkers plays a crucial role in the disease management and strongly impact in patient's prognosis and survival. Although having many limitations CA125 is a classical ovarian cancer biomarker, but current research using proteomic or metabolomic methodologies struggles to find alternative biomarkers, using non-invasive our relatively non-invasive sources such as urine, serum, plasma, tissue, ascites or exosomes. Metabolism and metabolites are key players in cancer biology and its importance in biomarkers discovery cannot be neglected. In this chapter we overview the state of art and the challenges facing the use and discovery of biomarkers and focus on ovarian cancer early detection.

Relative Ratios Enhance the Diagnostic Power of Phospholipids in Distinguishing Benign and Cancerous Ovarian Masses

Ovarian cancer remains a highly lethal disease due to its late clinical presentation and lack of reliable early biomarkers. Protein-based diagnostic markers have presented limitations in identifying ovarian cancer. We tested the potential of phospholipids as markers of ovarian cancer by utilizing inter-related regulation of phospholipids, a unique property that allows the use of ratios between phospholipid species for quantitation. High-performance liquid chromatography mass spectrometry was used to measure phospholipid, lysophospholipid, and sphingophospholipid content in plasma from patients with benign ovarian masses, patients with ovarian cancer, and controls. We applied both absolute and relative phospholipid ratios for quantitation. Receiver operating characteristic analysis was performed to test the sensitivity and specificity. We found that utilization of ratios between phospholipid species greatly outperformed absolute quantitation in the identification of ovarian cancer. Of the phospholipids analyzed, species in phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and sphingomyelin (SM) were found to have great biomarker potential. LPC(20:4)/LPC(18:0) carried the greatest capacity to differentiate cancer from control, SM(d18:1/24:1)/SM(d18:1/22:0) to differentiate benign from cancer, and PC(18:0/20:4)/PC(18:0/18:1) to differentiate benign from control. These results demonstrate the potential of plasma phospholipids as a novel marker of ovarian cancer by utilizing the unique characteristics of phospholipids to further enhance the diagnostic power.

Non-invasive Biodiversified Sensors: A Modernized Screening Technology for Cancer

Background:

Biological sensors revolutionize the method of diagnoses of diseases from early to final stages using the biomarkers present in the body. Biosensors are advantageous due to the involvement of minimal sample collection with improved specificity and sensitivity for the detection of biomarkers.

Methods:

Conventional biopsies restrict problems like patient non-compliance, cross-infection and high cost and to overcome these issues biological samples like saliva, sweat, urine, tears and sputum progress into clinical and diagnostic research for the development of non-invasive biosensors. This article covers various non-invasive measurements of biological samples, optical-based, mass-based, wearable and smartphone-based biosensors for the detection of cancer.

Results:

The demand for non-invasive, rapid and economic analysis techniques escalated due to the modernization of the introduction of self-diagnostics and miniature forms of devices. Biosensors have high sensitivity and specificity for whole cells, microorganisms, enzymes, antibodies, and genetic materials.

Conclusion:

Biosensors provide a reliable early diagnosis of cancer, which results in faster therapeutic outcomes with in-depth fundamental understanding of the disease progression.

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.

Urine proteomics study reveals potential biomarkers for the differential diagnosis of cholangiocarcinoma and periductal fibrosis

Cholangiocarcinoma (CCA) is a primary malignant tumor of the epithelial lining of biliary track associated with endemic Opisthorchis viverrini (Ov) infection in northeastern Thailand. Ov-associated periductal fibrosis (PDF) is the precancerous lesion for CCA, and can be detected by ultrasonography (US) to facilitate early detection. However, US cannot be used to distinguish PDF from cancer. Therefore, the objective of this study was to discover and qualify potential urine biomarkers for CCA detection in at-risk population. Biomarker discovery was conducted on pooled urine samples, 42 patients per group, with PDF or normal bile duct confirmed by ultrasound. After depletion of high abundance proteins, 338 urinary proteins were identified from the 3 samples (normal-US, PDF-US, CCA). Based on fold change and literature review, 70 candidate proteins were selected for qualification by multiple reaction monitoring mass spectrometry (MRM-MS) in 90 individual urine samples, 30 per group. An orthogonal signal correction projection to latent structures discriminant analysis (O-PLS-DA) multivariate model constructed from the 70 candidate biomarkers significantly discriminated CCA from normal and PDF groups (P = 0.003). As an independent validation, the expression of 3 candidate proteins was confirmed by immunohistochemistry in CCA tissues: Lysosome associated membrane glycoprotein 1 (LAMP1), lysosome associated membrane glycoprotein 2 (LAMP2) and cadherin-related family member 2 (CDHR2). Further evaluation of these candidate biomarkers in a larger cohort is needed to support their applicability in a clinical setting for screening and monitoring early CCA and for CCA surveillance.

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.

Diagnostic accuracy of urine HE4 in patients with ovarian cancer: a meta-analysis

Urine HE4 has been reported as the potential novel diagnostic biomarker for ovarian cancer in several studies, but their results were inconsistent. Therefore, we conducted a systematic analysis to evaluate the diagnostic value of urine HE4 in detecting ovarian cancer. A comprehensive electronic and manual search was conducted for relevant literatures through several databases up to May 5, 2016. The quality of the studies included in the systematic review was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. All analyses were conducted using Meta-DiSc 1.4 and STATA 12.0 software. A total of seven publications were included in this study, and these studies included 413 ovarian cancer patients and 573 controls. The summary estimates were: sensitivity 0.76 (95% confidence interval [CI]: 0.72–0.80), specificity 0.92 (95% CI: 0.89–0.94), positive likelihood ratio 8.39 (95%CI: 4.81–14.63), negative likelihood ratio 0.23 (95% CI: 0.13–0.39), diagnostic odds ratio 37.90 (95% CI: 18.69–76.83), and area under the curve 0.93. According to our results, urine HE4 has greater diagnostic value in detecting ovarian cancer. In addition, considering the high heterogeneity, further research studies with more well-designed and large sample sizes are needed in the future.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed.

SIGNIFICANCE

Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases.

Detection of the HE4 protein in urine as a biomarker for ovarian neoplasms: Clinical correlates

OBJECTIVES

To measure HE4 levels in urine from normal donors, patients with LMP tumors and ovarian cancer patients and to correlate levels with clinical factors in ovarian cancer patients.

METHODS

Archived samples from controls, patients with LMP tumors and ovarian cancer were tested using commercial assays, including serially collected serum and urine samples from women treated for stage III/IV serous ovarian cancer.

RESULTS

Five of 6 patients with stage I/II and 26 of 36 stage III/IV serous ovarian cancer patients had HE4-positive urines, similar to serum samples (4 of 5 stage I/II and 26 of 34 stage III/IV) when tested at the same level of specificity (95%). Urine HE4 was more sensitive in LMP tumors: 9 of 32 urines (28%) HE4-positive versus 3 of 68 sera (4.4%, p=0.002). Mean levels of serum CA125 and HE4 decreased comparably in patients during initial treatment regardless of their primary platinum response, but mean urine HE4 levels decreased only 7% in primary platinum resistant patients while decreasing 68% in those who were sensitive. By 7months after diagnosis, urine HE4 levels were higher in primary platinum resistant patients compared to those who proved to be sensitive (p=0.051) and persisted 12months after diagnosis (p=0.014). HE4 values in urine also became positive in advance of clinical recurrence in several women while serum HE4 and serum CA-125 remained normal.

CONCLUSIONS

Measuring HE4 in urine complements serum assays for the detection of ovarian cancer and may allow identification of patients at high risk for primary platinum resistance.

Quantitative urinary proteomics using stable isotope labelling by peptide dimethylation in patients with prostate cancer

Prostate cancer (PCa) is the most commonly diagnosed malignancy in men. The current prevalent diagnosis method, prostate-specific antigen (PSA) screening test, has low sensitivity, specificity and is poor at predicting the grade of disease. Thus, new biomarkers are urgently needed to improve the PCa diagnosis and staging for the management of patients. The aim of this study is to investigate the first voided urinary sample after massage for biomarker discovery for PCa. In this work, untargeted metabolomic profiling of the first voided urinary sample after massage from 28 confirmed prostate cancer patients, 20 benign enlarged prostate patients and 6 healthy volunteers was performed using liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS). Single and multiple peptide protein and cross-linking molecules were identified using PEAKS software. Analytical and diagnostic performance was tested using the Student's t test, Benjamini Hochberg correction and the receiver operating characteristic (ROC) curves. Using differential display analysis to compare peptides and cross-linking molecules of urinary samples between patients with benign, enlarged prostate and malignant cancer, we identified multiple peptides derived from osteopontin (SPP1) and prothrombin (F2) that are lower in PCa patients than in benign and enlarged prostate. The diagnosis accuracies of SPP1 and F2 peptides are 0.65-0.77 and 0.68-0.72, respectively. In addition to this, there are significant differences between PCa and benign/enlarged prostate patients in pyridinoline (PYD) and deoxypyridinoline (DPD) (p value = 0.001). Differences also, as shown in the excretion of these molecules for different stages of PCa (p value = 0.04) as the level of DPD and DPD/PYD ratio, were high in patients with locally advanced tumours. The study underscores the importance of proteomics analysis, and our results demonstrate that a urinary-based in depth proteomic approach allows the potential identification of dysregulated pathways and diagnostic biomarkers.

Urinary protein biomarkers in the early detection of lung cancer

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

Protein post-translational modification in host defense: the antimicrobial mechanism of action of human eosinophil cationic protein native forms

Knowledge on the contribution of protein glycosylation in host defense antimicrobial peptides is still scarce. We have studied here how the post-translational modification pattern modulates the antimicrobial activity of one of the best characterized leukocyte granule proteins. The human eosinophil cationic protein (ECP), an eosinophil specific granule protein secreted during inflammation and infection, can target a wide variety of pathogens. Previous work in human eosinophil extracts identified several ECP native forms and glycosylation heterogeneity was found to contribute to the protein biological properties. In this study we analyze for the first time the antimicrobial activity of the distinct native proteins purified from healthy donor blood. Low and heavy molecular weight forms were tested on Escherichia coli cell cultures and compared with the recombinant non-glycosylated protein. Further analysis on model membranes provided an insight towards an understanding of the protein behavior at the cytoplasmic membrane level. The results highlight the significant reduction in protein toxicity and bacteria agglutination activity for heavy glycosylated fractions. Notwithstanding, the lower glycosylated fraction mostly retains the lipopolysaccharide binding affinity together with the cytoplasmic membrane depolarization and membrane leakage activities. From structural analysis we propose that heavy glycosylation interferes with the protein self-aggregation, hindering the cell agglutination and membrane disruption processes. The results suggest the contribution of post-translational modifications to the antimicrobial role of ECP in host defense.

Excretion of urinary orosomucoid 1 protein is elevated in patients with chronic heart failure

Easily screening markers for early detection of chronic heart failure (CHF) are lacking. We identified twenty differently expressed proteins including orosomucoid 1(ORM1) in urine between patients with CHF and normal controls by proteomic methods. Bioinformatics analyses suggested ORM1 could be used for further analysis. After verification by western blotting, the urinary levels of ORM1 were quantified with enzyme-linked immunosorbent assay (ELISA) by correcting for creatinine expression. The ORM1-Cr was significantly elevated in CHF patients than normal controls (6498.83±4300.21 versus 2102.26±1069.24 ng/mg). Furthermore, a Spearman analysis indicated that the urinary ORM1 levels had a high positive correlation with the classification of CHF, and the multivariate analysis suggested that the urinary ORM1 content was associated with the plasma amino-terminal pro- brain natriuretic peptide (NT-proBNP) (OR: 2.106, 95% CI: 1.213–3.524, P = 0.002) and the New York Heart Association (NYHA) classification (OR: 3.019, 95% CI: 1.329–4.721, P<0.001). In addition, receiving operating curve (ROC) analyses suggested that an optimum cut-off value of 2484.98 ng/mg with 90.91% sensitivity and 85.48% specificity, respectively, could be used for the diagnosis of CHF. To sum up, our findings indicate that ORM1 could be a potential novel urinary biomarker for the early detection of CHF.

Urinary signatures of Renal Cell Carcinoma investigated by peptidomic approaches

Renal Cell Carcinoma (RCC) is typically asymptomatic and surgery usually increases patient's lifespan only for early stage tumours. Moreover, solid renal masses cannot be confidently differentiated from RCC. Therefore, markers to distinguish malignant kidney tumours and for their detection are needed. Two different peptide signatures were obtained by a MALDI-TOF profiling approach based on urine pre-purification by C8 magnetic beads. One cluster of 12 signals could differentiate malignant tumours (n = 137) from benign renal masses and controls (n = 153) with sensitivity of 76% and specificity of 87% in the validation set. A second cluster of 12 signals distinguished clear cell RCC (n = 118) from controls (n = 137) with sensitivity and specificity values of 84% and 91%, respectively. Most of the peptide signals used in the two models were observed at higher abundance in patient urines and could be identified as fragments of proteins involved in tumour pathogenesis and progression. Among them: the Meprin 1α with a pro-angiogenic activity, the Probable G-protein coupled receptor 162, belonging to the GPCRs family and known to be associated with several key functions in cancer, the Osteopontin that strongly correlates to tumour stages and invasiveness, the Phosphorylase b kinase regulatory subunit alpha and the SeCreted and TransMembrane protein 1.

Recent technical strategies to identify diagnostic biomarkers for ovarian cancer

Ovarian cancer is the fifth leading cause of cancer deaths among North American women. Regrettably, there is currently no reliable circulating biomarker that can detect ovarian cancer in its early stages. The CA125 biomarker is very useful for treatment response monitoring, but its sensitivity is very low for early detection. Thus, there is an urgent need for the identification of new circulating biomarkers/panel of biomarkers that could be used to diagnose ovarian cancer before it becomes clinically detectable and advanced. Unfortunately, the strategies used in the past years to identify such biomarkers have not led to any outstanding candidate. This review summarizes the different approaches used in the last decade and suggests which strategies should be adopted in the near future in order to lead to the successful identification of new ovarian cancer diagnostic biomarkers.

Potential Urinary Protein Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients

Globally, Prostate cancer (PCa) is the most frequently occurring non-cutaneous cancer, and is the second highest cause of cancer mortality in men. Serum prostate specific antigen (PSA) has been the standard in PCa screening since its approval by the American Food & Drug Administration (FDA) in 1994. Currently, PSA is used as an indicator for PCa - patients with a serum PSA level above 4ng/mL will often undergo prostate biopsy to confirm cancer. Unfortunately fewer than ~30% of these men will biopsy positive for cancer, meaning that the majority of men undergo invasive biopsy with little benefit. Despite PSA's notoriously poor specificity (33%), there is still a significant lack of credible alternatives. Therefore an ideal biomarker that can specifically detect PCa at an early stage is urgently required. The aim of this study was to investigate the potential of using deregulation of urinary proteins in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the protein signatures specific for PCa, protein expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using LC-MS/MS. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This approach revealed that significant the down-regulation of Fibronectin and TP53INP2 was a characteristic event among PCa patients. Fibronectin mRNA down-regulation, was identified as offering improved specificity (50%) over PSA, albeit with a slightly lower although still acceptable sensitivity (75%) for detecting PCa. As for TP53INP2 on the other hand, its down-regulation was moderately sensitive (75%), identifying many patients with PCa, but was entirely non-specific (7%), designating many of the benign samples as malignant and being unable to accurately identify more than one negative.

Biomarkers for early detection of ovarian cancer

Ovarian cancer is the most lethal gynecological malignancy. However, effective screening strategies have not been established and continue to be elusive. A good screening test must adequately address validity, reliability, yield, cost, acceptance and follow-up services. An ideal screening test for ovarian cancer must have a high sensitivity in order to correctly diagnose all women with the disease and a high specificity to avoid false-positive results. The current screening modalities of bimanual examination, CA-125 and transvaginal ultrasonography together allow us to detect only 30-45% of women with early-stage disease. Recent developments in proteomic and genomic research have identified a number of potential biomarkers. Although panels of tumor markers and proteomic-based technologies may improve the positive predictive value, all markers require validation and interfacing with newly developed diagnostic imaging technologies. While a large amount of information on miRNAs has been promising, much remains to be elucidated. This review will examine the current status of biomarkers and technologies of interest in the effort of early detection of ovarian cancer.

Altered expression of sialylated glycoproteins in ovarian cancer sera using lectin-based ELISA assay and quantitative glycoproteomics analysis

Herein, we identify and confirm differentially expressed sialoglycoproteins in the serum of patients with ovarian cancer. On the basis of Sambucus nigra (SNA) lectin enrichment and on an isobaric chemical labeling quantitative strategy, clusterin (CLUS), leucine-rich alpha-2-glycoprotein (LRG1), hemopexin (HEMO), vitamin D-binding protein (VDB), and complement factor H (CFH) were found to be differentially expressed in the serum of patients with ovarian cancer compared to benign diseases. The abnormal sialylation levels of CLUS, CFH, and HEMO in serum of ovarian cancer patients were verified by a lectin-based ELISA assay. ELISA assays were further applied to measure total protein level changes of these glycoproteins. Protein levels of CLUS were found to be down-regulated in the serum of ovarian cancer patients, while protein levels of LRG1 were increased. The combination of CLUS and LRG1 (AUC = 0.837) showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone (AUC = 0.811). In differentiating early stage ovarian cancer from benign diseases or healthy controls, LRG1 showed comparable performance to CA125. An independent sample set was further used to confirm the ability of these candidate markers to detect patients with ovarian cancer. Our study provides a comprehensive strategy for the identification of candidate biomarkers that show the potential for diagnosis of ovarian cancer. Further studies using a large number of samples are necessary to validate the utility of this panel of proteins.

An extensive targeted proteomic analysis of disease-related protein biomarkers in urine from healthy donors

The analysis of protein biomarkers in urine is expected to lead to advances in a variety of clinical settings. Several characteristics of urine including a low-protein matrix, ease of testing and a demonstrated proteomic stability offer distinct advantages over current widely used biofluids, serum and plasma. Improvements in our understanding of the urine proteome and in methods used in its evaluation will facilitate the clinical development of urinary protein biomarkers. Multiplexed bead-based immunoassays were utilized to evaluate 211 proteins in urines from 103 healthy donors. An additional 25 healthy donors provided serial urine samples over the course of two days in order to assess temporal variation in selected biomarkers. Nearly one-third of the evaluated biomarkers were detected in urine at levels greater than 1ng/ml, representing a diverse panel of proteins with respect to structure, function and biological role. The presence of several biomarkers in urine was confirmed by western blot. Several methods of data normalization were employed to assess impact on biomarker variability. A complex pattern of correlations with urine creatinine, albumin and beta-2-microglobulin was observed indicating the presence of highly specific mechanisms of renal filtration. Further investigation of the urinary protein biomarkers identified in this preliminary study along with a consideration of the underlying proteomic trends suggested by these findings should lead to an improved capability to identify candidate biomarkers for clinical development.

Proteomics: methodologies and applications to the study of human diseases

Proteomic approach has allowed large-scale studies of protein expression in different tissues and body fluids in discrete conditions and/or time points. Recent advances of methodologies in this field have opened new opportunities to obtain relevant information on normal and abnormal processes occurring in the human body. In the current report, the main proteomics techniques and their application to human disease study are reviewed.

Cucumber mosaic virus as drug delivery vehicle for doxorubicin

Taking advantage of the unique structure feature of cucumber mosaic virus (CMV), we have anchored folic acid (FA) as targeting moiety on the rigid CMV capsid and loaded significant amount of doxorubicin (Dox) into the interior cavity of CMV through the formation of Dox-RNA conjugate to provide a nanosized control delivery system for cancer therapy. The FA-CMV-Dox assemblies were characterized using transmission electron microscopy and size exclusion chromatography, which disclose that they have comparable size and morphology to the native CMV particles. The Dox-loaded viral particles exhibit sustained in vitro Dox release profile over 5 days at physiological pH but can be liberated from the conjugates with the presence of elevated level of RNase. The in vitro effects of folate receptor (FR)-targeted CMV-Dox nanoconjugates on cellular internalization and cell proliferation were evaluated by live-cell imaging, MTT and TUNEL assay, respectively, in mouse cardiomyocytes and FR over expression OVCAR-3 tumor cells. The in vivo efficacy was also investigated in the OVCAR-3 BALB/c nude mouse xenograft model through histological alterations and TUNEL assessment. The FA-CMV-Dox particles significantly decrease the accumulation of Dox in the nuclei of mouse myocardial cells and improve the uptake of Dox in the ovarian cancer, leading to less cardiotoxicity and enhanced antitumor effect. We believe that CMV offers a new way to fabricate nanosized drug delivery vehicles.

Unrestrictive identification of post-translational modifications in the urine proteome without enrichment

Background

Research on the human urine proteome may lay the foundation for the discovery of relevant disease biomarkers. Post-translational modifications (PTMs) have important effects on the functions of protein biomarkers. Identifying PTMs without enrichment adds no extra steps to conventional identification procedures for urine proteomics. The only difference is that this method requires software that can conduct unrestrictive identifications of PTMs. In this study, routine urine proteomics techniques were used to identify urine proteins. Unspecified PTMs were searched by MODa and PEAKS 6 automated software, followed by a manual search to screen out in vivo PTMs by removing all in vitro PTMs and amino acid substitutions.

Results

There were 75 peptides with 6 in vivo PTMs that were found by both MODa and PEAKS 6. Of these, 34 peptides in 18 proteins have novel in vivo PTMs compared with the annotation information of these proteins on the Universal Protein Resource website. These new in vivo PTMs had undergone methylation, dehydration, oxidation, hydroxylation, phosphorylation, or dihydroxylation.

Conclusions

In this study, we identified PTMs of urine proteins without the need for enrichment. Our investigation may provide a useful reference for biomarker discovery in the future.

Eosinophil associated genes in the inflammatory bowel disease 4 region: Correlation to inflammatory bowel disease revealed

AIM: To study the association between inflammatory bowel disease (IBD) and genetic variations in eosinophil protein X (EPX) and eosinophil cationic protein (ECP).

METHODS: DNA was extracted from ethylene diamine tetraacetic acid blood of 587 patients with Crohn’s disease (CD), 592 with ulcerative colitis (UC) and 300 healthy subjects. The EPX405 (G > C, rs2013109), ECP434 (G > C, rs2073342) and ECP562 (G > C, rs2233860) gene polymorphisms were analysed, by the 5’-nuclease allelic discrimination assay. For determination of intracellular content of EPX and ECP in granulocytes, 39 blood samples was collected and extracted with a buffer containing cetyltrimethylammonium bromide. The intracellular content of EPX was analysed using an enzyme-linked immunosorbent assay. The intracellular content of ECP was analysed with the UniCAP^® system as described by the manufacturer. Statistical tests for calculations of results were χ² test, Fisher’s exact test, ANOVA, Student-Newman-Keuls test, and Kaplan-Meier survival curve with Log-rank test for trend, the probability values of P < 0.05 were considered statistically significant.

RESULTS: The genotype frequency for males with UC and with an age of disease onset of ≥ 45 years (n = 57) was for ECP434 and ECP562, GG = 37%, GC = 60%, CC = 4% and GG = 51%, GC = 49%, CC = 0% respectively. This was significantly different from the healthy subject’s genotype frequencies of ECP434 (GG = 57%, GC = 38%, CC = 5%; P = 0.010) and ECP562 (GG = 68%, GC = 29%,CC = 3%; P = 0.009). The genotype frequencies for females, with an age of disease onset of ≥ 45 years with CD (n = 62), was for the ECP434 and ECP562 genotypes GG = 37%, GC = 52%, CC = 11% and GG = 48%, GC = 47% and CC = 5% respectively. This was also statistically different from healthy controls for both ECP434 (P = 0.010) and ECP562 (P = 0.013). The intracellular protein concentration of EPX and ECP was calculated in μg/10⁶ eosinophils and then correlated to the EPX 405 genotypes. The protein content of EPX was highest in the patients with the CC genotype of EPX405 (GG = 4.65, GC = 5.93, and CC = 6.57) and for ECP in the patients with the GG genotype of EPX405 (GG = 2.70, GC = 2.47 and CC = 1.90). ANOVA test demonstrated a difference in intracellular protein content for EPX (P = 0.009) and ECP (P = 0.022). The age of disease onset was linked to haplotypes of the EPX405, ECP434 and ECP562 genotypes. Kaplan Maier curve showed a difference between haplotype distributions for the females with CD (P = 0.003). The highest age of disease onset was seen in females with the EPX405CC, ECP434GC, ECP562CC haplotype (34 years) and the lowest in females with the EPX405GC, ECP434GC, ECP562GG haplotype (21 years). For males with UC there was also a difference between the highest and lowest age of the disease onset (EPX405CC, ECP434CC, ECP562CC, mean 24 years vs EPX405GC, ECP434GC, ECP562GG, mean 34 years, P = 0.0009). The relative risk for UC patients with ECP434 or ECP562-GC/CC genotypes to develop dysplasia/cancer was 2.5 (95%CI: 1.2-5.4, P = 0.01) and 2.5 (95%CI: 1.1-5.4, P = 0.02) respectively, compared to patients carrying the GG-genotypes.

CONCLUSION: Polymorphisms of EPX and ECP are associated to IBD in an age and gender dependent manner, suggesting an essential role of eosinophils in the pathophysiology of IBD.

Promising Urinary Protein Biomarkers for the Early Detection of Hepatocellular Carcinoma among High-Risk Hepatitis C Virus Egyptian Patients

Hepatocellular Carcinoma is a major healthcare problem, representing the third most common cause of cancer-related mortality worldwide. There are 130 million Hepatitis C virus infected patients worldwide who are at a high-risk for developing Hepatocellular Carcinoma. Due to the fact that reliable parameters and/or tools for the early detection of Hepatocellular Carcinoma among high-risk individuals are severely lacking, Hepatocellular Carcinoma patients are always diagnosed at a late stage where surgical solutions or effective treatment are not possible. Urine was collected from 106 Hepatitis C infected patients patients, 32 of whom had already developed Hepatocellular Carcinoma and 74 patients who were diagnosed as Hepatocellular Carcinoma -free at the time of initial sample collection. In addition to these patients, urine samples were also collected from 12 healthy control individuals. Total urinary proteins were isolated from the urine samples and LC-MS/MS was used to identify potential protein HCC biomarker candidates. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This approach revealed that significant over-expression of three proteins: DJ-1, Chromatin Assembly Factor-1 (CAF-1) and Heat Shock Protein 60 (HSP60), was a characteristic event among Hepatocellular Carcinoma - post Hepatitis C virus infected patients. As a single-based Hepatocellular Carcinoma biomarker, CAF-1 over-expression identified Hepatocellular Carcinoma among Hepatitis C virus infected patients with a specificity of 90%, sensitivity of 66% and with an overall diagnostic accuracy of 78%. Moreover, the CAF-1/HSP60 tandem identified Hepatocellular Carcinoma among Hepatitis C virus infected patients with a specificity of 92%, sensitivity of 61% and with an overall diagnostic accuracy of 77%.

Application of proteomics to cancer early detection

Strategies to achieve personalized medicine and improve public health encompass assessment of an individual's risk for disease, early detection, and molecular classification of disease resulting in an informed choice of the most appropriate treatment instituted at an early stage of disease development. An unmet need in this field for which proteomics is well suited to make a major contribution is the development of blood-based tests for early cancer detection. This is illustrated in proteomic studies of epithelial cancer that encompass analysis of specimens collected both at the time of diagnosis and specimens collected before onset of symptoms that are particularly suited for the identification of early detection markers. This overarching effort benefits from the availability of plasmas from subject cohorts and of engineered mouse models that are sampled at early stages of tumor development. Integration of findings from plasma with tumor tissue and cancer cell proteomic and genomic data allows elucidation of signatures in plasma for altered signaling pathways. The discovery and further development of early detection markers take advantage of the availability of in-depth quantitative proteomics methods and bioinformatics resources for data mining.

A urinary Bcl-2 surface acoustic wave biosensor for early ovarian cancer detection

In this study, the design, fabrication, surface functionalization and experimental characterization of an ultrasonic MEMS biosensor for urinary anti-apoptotic protein B-cell lymphoma 2 (Bcl-2) detection with sub ng/mL sensitivity is presented. It was previously shown that urinary Bcl-2 levels are reliably elevated during early and late stages of ovarian cancer. Our biosensor uses shear horizontal (SH) surface acoustic waves (SAWs) on surface functionalized ST-cut Quartz to quantify the mass loading change by protein adhesion to the delay path. SH-SAWs were generated and received by a pair of micro-fabricated interdigital transducers (IDTs) separated by a judiciously designed delay path. The delay path was surface-functionalized with monoclonal antibodies, ODMS, Protein A/G and Pluronic F127 for optimal Bcl-2 capture with minimal non-specific adsorption. Bcl-2 concentrations were quantified by the resulting resonance frequency shift detected by a custom designed resonator circuit. The target sensitivity for diagnosis and identifying the stage of ovarian cancer was successfully achieved with demonstrated Bcl-2 detection capability of 500 pg/mL. It was also shown that resonance frequency shift increases linearly with increasing Bcl-2 concentration.

Use of electroporation and reverse iontophoresis for extraction of transdermal multibiomarkers

Background

Monitoring of biomarkers, like urea, prostate-specific antigen (PSA), and osteopontin, is very important because they are related to kidney disease, prostate cancer, and ovarian cancer, respectively. It is well known that reverse iontophoresis can enhance transdermal extraction of small molecules, and even large molecules if reverse iontophoresis is used together with electroporation. Electroporation is the use of a high-voltage electrical pulse to create nanochannels within the stratum corneum, temporarily and reversibly. Reverse iontophoresis is the use of a small current to facilitate both charged and uncharged molecule transportation across the skin. The objectives of this in vitro study were to determine whether PSA and osteopontin are extractable transdermally and noninvasively and whether urea, PSA, and osteopontin can be extracted simultaneously by electroporation and reverse iontophoresis.

Methods

All in vitro experiments were conducted using a diffusion cell assembled with the stratum corneum of porcine skin. Three different symmetrical biphasic direct currents (SBdc), five various electroporations, and a combination of the two techniques were applied to the diffusion cell via Ag/AgCl electrodes. The three different SBdc had the same current density of 0.3 mA/cm², but different phase durations of 0 (ie, no current, control group), 30, and 180 seconds. The five different electroporations had the same pulse width of 1 msec and number of pulses per second of 10, but different electric field strengths of 0 (ie, no voltage, control group), 74, 148, 296, and 592 V/cm. Before and after each extraction experiment, skin impedance was measured at 20 Hz.

Results

It was found that urea could be extracted transdermally using reverse iontophoresis alone, and further enhancement of extraction could be achieved by combined use of electroporation and reverse iontophoresis. Conversely, PSA and osteopontin were found to be extracted transdermally only by use of reverse iontophoresis and electroporation with a high electrical field strength (>296 V/cm). After application of reverse iontophoresis, electroporation, or a combination of the two techniques, a reduction in skin impedance was observed.

Conclusion

Simultaneous transdermal extraction of urea, PSA, and osteopontin is possible only for the condition of applying reverse iontophoresis in conjunction with high electroporation.

Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: A systematic review

The focus of this systematic review is to give an overview of the current status of clinical protein profiling studies using MALDI and SELDI MS platforms in the search for ovarian cancer biomarkers. A total of 34 profiling studies were qualified for inclusion in the review. Comparative analysis of published discriminatory peaks to peaks found in an original MALDI MS protein profiling study was made to address the key question of reproducibility across studies. An overlap was found despite substantial heterogeneity between studies relating to study design, biological material, pre-analytical treatment, and data analysis. About 47% of the peaks reported to be associated to ovarian cancer were also represented in our experimental study, and 34% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility an overlap in peaks between clinical studies was demonstrated, which indicate convergence toward a set of common discriminating, reproducible peaks for ovarian cancer. The potential of the discriminating protein peaks for clinical use as ovarian cancer biomarkers will be discussed and evaluated. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Purification and identification of candidate biomarkers discovered using SELDI-TOF MS

Purification and identification of candidate biomarkers is a critical step in the biomarker development process, since it provides insight into the disease biology and facilitates the development of analyte-specific assays. Top-down biomarker discovery workflows like SELDI-TOF MS yield candidate markers that are identified based on native mass. Positive identification of these candidate biomarkers requires further enrichment and/or purification. While purification methods must be optimized for each protein target, there are two general workflows. Native peptides under approximately 4 kDa can be subjected to direct sequence analysis using a tandem mass spectrometer whereas proteins over approximately 4 kDa usually require proteolytic digestion prior to MS/MS analysis. In both cases, partial purification is usually necessary to enrich the candidate biomarker relative to other proteins in a complex biological mixture. This chapter provides detailed protocols for protein purification (including anion exchange, metal affinity, and reverse phase chromatography as well as SDS-PAGE) and identification (including protein processing, digestion, and database searching).