Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer

The Role of CA 125 as Tumor Marker: Biochemical and Clinical Aspects

CA 125 also known as mucin 16 or MUC16 is a large membrane glycoprotein belonging to the wide mucin family, encoded by the homonymous MUC16 gene. Following its discovery in the blood of some patients with specific types of cancers or other benign conditions, CA125 has found application as a tumor marker of ovarian cancer. Thirty years after its discovery, use of CA 125 is still FDA-recommended to monitor response to therapy in patients with epithelial ovarian cancer and to detect residual or recurrent disease in patients who have undergone first-line therapy and would be considered for second-look procedures. However, due to its limited specificity and sensitivity, CA 125 alone cannot still be an ideal biomarker. Increased clinical performance, in terms of better sensitivity and specificity in identifying epithelial ovarian cancer relapse, has been obtained by combined use of CA 125 with HE4, another ovarian cancer marker recently introduced in clinical use. Significant advancements have been achieved more recently, due to the introduction of FDA-approved ROMA and OVA1 algorithms to evaluate the risk of ovarian cancer for patients with a pelvic mass.

Metabonomic analysis of ovarian tumour cyst fluid by proton nuclear magnetic resonance spectroscopy

The majority of ovarian tumours are of the epithelial type, which can be sub classified as benign, borderline or malignant. Epithelial tumours usually have cystic spaces filled with cyst fluid, the metabolic profile of which reflects the metabolic activity of the tumour cells, due to their close proximity. The approach of metabonomics using 1H-NMR spectroscopy was employed to characterize the metabolic profiles of ovarian cyst fluid samples (n = 23) from benign, borderline and malignant ovarian tumours in order to shed more light into ovarian tumour and cancer development. The analysis revealed that citrate was elevated in benign versus malignant tumours, while the amino acid lysine was elevated in malignant versus non-malignant tumours, both at a 5% significance level. Choline and lactate also had progressively increasing levels from benign to borderline to malignant samples. Finally, hypoxanthine was detected exclusively in a sub-cohort of the malignant tumours. This metabonomic study demonstrates that ovarian cyst fluid samples have potential to be used to distinguish between the different types of ovarian epithelial tumours. Furthermore, the respective metabolic profiles contain mechanistic information which could help identify biomarkers and therapeutic targets for ovarian tumours.

Discovery and verification of urinary peptides in type 2 diabetes mellitus with kidney injury

Varying degrees of renal injury could lead to different changes in urinary protein composition. We want to find urinary candidate peptide biomarkers in type 2 diabetic patients with different extents of kidney injury. Two sets of patients were recruited. Discovery set: weak cationic-exchange magnetic beads coupled with matrix-assisted laser desorption ionization time-of-flight mass spectrometry were used to profile the low-molecular weight peptidome in urine samples from type 2 diabetes patients with normoalbuminura and microalbuminuria. The differently expressed urinary peptides were screened by ClinProTools2.1 bioinformatics software and identified through nano-liquid chromatography-tandem mass spectrometry. Verification set: the above screened urinary peptides were validated by use matrix-assisted laser desorption ionization time-of-flight mass spectrometry on another group of type 2 diabetes patients with different extents use of kidney injury. In the screening and identification stages, seven urinary peptides were selected as the most promising biomarker candidates, and they were identified as fragments of vitronectin precursor, isoform 1 of fibrinogen alpha chain precursor, prothrombin precursor and inter-alpha-trypsin inhibitor heavy chain H4. The diagnostic efficacy of these urinary peptides was evaluated by area under the receiver operating characteristic curve, and they were 0.767, 0.768, 0.868, 0.910, 0.860, 0.843, and 0.865, respectively. In the verification stage, m/z 1743.9, 2154, 2175.5, and 2184.9 were decreased as albumin-to-creatinine (Alb/Cre) increased and m/z 2231.1, 2430.8, and 2756.1 were elevated as Alb/Cre rose. These small molecule peptides are related to type 2 diabetes kidney damage, and they may play an important role in monitoring type 2 diabetes.

Advances in mass spectrometry-based clinical biomarker discovery

The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery.

Experimental and theoretical investigation of the precise transduction mechanism in giant magnetoresistive biosensors

Giant magnetoresistive (GMR) biosensors consisting of many rectangular stripes are being developed for high sensitivity medical diagnostics of diseases at early stages, but many aspects of the sensing mechanism remain to be clarified. Using e-beam patterned masks on the sensors, we showed that the magnetic nanoparticles with a diameter of 50 nm located between the stripes predominantly determine the sensor signals over those located on the sensor stripes. Based on computational analysis, it was confirmed that the particles in the trench, particularly those near the edges of the stripes, mainly affect the sensor signals due to additional field from the stripe under an applied field. We also demonstrated that the direction of the average magnetic field from the particles that contributes to the signal is indeed the same as that of the applied field, indicating that the particles in the trench are pivotal to produce sensor signal. Importantly, the same detection principle was validated with a duplex protein assay. Also, 8 different types of sensor stripes were fabricated and design parameters were explored. According to the detection principle uncovered, GMR biosensors can be further optimized to improve their sensitivity, which is highly desirable for early diagnosis of diseases.

Proteomics of ovarian cancer: functional insights and clinical applications

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics' contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. We propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.

Highly dispersed magnetic molecularly imprinted nanoparticles with well-defined thin film for the selective extraction of glycoprotein

Highly dispersed magnetic molecularly imprinted nanoparticles (MMINs) with a well-defined thin film for the selective extraction of glycoprotein HRP were developed in this work.

Identification of cysteinylated transthyretin, a predictive biomarker of treatment response to partially hydrolyzed guar gum in type 2 diabetes rats, by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Recent evidence has indicated that total fiber intake is inversely related to type 2 diabetes risk. The present study aimed to investigate the effects of chronic administration of partially hydrolyzed guar gum (PHGG), a water-soluble dietary fiber, on the occurrence of diabetes and its complications, fatty liver and nephropathy. We also identified predictive serum biomarkers of treatment response to PHGG by mass spectroscopy-based proteomic analysis using Otsuka Long-Evans Tokushima Fatty (OLETF) rats, a good model of human non-insulin-dependent diabetes mellitus. In this study, at 5 weeks of age, OLETF rats and control strain Long-Evans Tokushima Otsuka (LETO) rats were fed a control diet or a high-fiber diet (5% PHGG) for 57 weeks. Body weight, food intake, oral glucose tolerance test, plasma insulin levels, and urine glucose and protein levels were regularly measured. Oral glucose tolerance tests (OGTT) and storage of serum in a deep freezer were conducted at the beginning of the experiment and every 4 weeks after overnight fasting during the experiments. PHGG treatment affected neither meal patterns nor the body weight of OLETF and LETO rats. Repeated measure analysis of variance revealed significant differences in fasting plasma glucose and plasma glucose at 2 h after OGTT between control OLETF (OLETF-C) rats and OLETF rats treated with PHGG (OLETF-F). The glucose response determined by the area under the curve of OGTT was significantly greater in OLETF-C rats than that in OLETF-F rats at 25 weeks of age. HOMA-IR, an index of insulin resistance, increased at 25 weeks of age in OLETF-C rats, while this increase was significantly inhibited in OLETF-F rats. At 62 weeks of age, PHGG treatment significantly improved hepatic steatosis as well as renal mesangial matrix accumulation in OLETF rats. To identify the risk marker for diabetes mellitus by SELDI-TOF MS, we collected sera from 21-week-old individuals. Among the 12 specific peaks that were risk marker candidates for diabetes mellitus, the m/z 13,720 peak was identified as that of cysteinylated transthyretin by sequencing of four tryptic peptides using tandem mass spectrometry and peak distribution around the m/z 13,720 peak in the SELDI-TOF spectra. In conclusion, we found that chronic treatment with PHGG improved insulin resistance, delayed the onset of diabetes, and inhibited the development of diabetic complications, as well as identified cysteinylated transthyretin as a predictive biomarker of treatment response to PHGG in OLETF rats.

Apolipoprotein A-I and Cancer

High-density lipoprotein (HDL) and apolipoprotein A-I (apoA-I), the predominant protein in plasma HDL, have long been the focus of intense studies in the field of atherosclerosis and cardiovascular disease. ApoA-I, in large part, is responsible for HDL assembly and its main atheroprotective function, that of shuttling excess cholesterol from peripheral tissues to the liver for excretion (reverse cholesterol transport). Recently, a protective role for HDL in cancer was suggested from several large clinical studies where an inverse relationship between plasma HDL-cholesterol (HDL-C) levels and risk of developing cancer was noted. This notion has now been tested and found to be supported in mouse tumor studies, where increasing levels of apoA-I/HDL were discovered to protect against tumor development and provision of human apoA-I was therapeutic against established tumors. This mini-review discusses the emerging role of apoA-I in tumor biology and its potential as cancer therapeutic.

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

INTRODUCTION

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

METHOD

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

RESULTS

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

CONCLUSIONS

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.

Proteomic analysis for finding serum pathogenic factors and potential biomarkers in multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a malignant tumor, which takes the second place in malignant blood disease. The clinical symptoms are complicated that make more difficult to diagnose and therapy. Lots of researches focus on the proteins about MM in order to solve those problems. We used proteomic methods to find potential biomarkers in MM patients.

METHODS

We applied the peptide ligand library beads (PLLBs) to deplete high abundance proteins in serum for finding potential pathogenic factors and biomarkers of MM. Using 1D-Gel-liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified 789 and 849 unique serum proteins in MM patients and in healthy controls, respectively.

RESULTS

Twenty-two proteins were found differentially expressed between the two groups including serum amyloid A protein, vitamin D-binding protein isoform-1 precursor, plasma kallikrein, and apolipoprotein A-I. Changes of integrin alpha-11 and isoform-1 of multimerin-1 were validated with Western blotting. The linkage of the differentially expressed proteins and the pathogenesis pathways of MM were discussed.

CONCLUSIONS

PLLB combined with 1D-gel-LC-MS/MS analysis is an efficient method to identify differentially expressed proteins in serum from patients with MM.

Proteomic changes in the cortex membrane fraction of genetic absence epilepsy rats from Strasbourg

Epilepsy is a serious neurodegenerative disorder with a high incidence and a variety of presentations and causes. Studies on brain from various animal models including chronic models: Genetic Absence Epilepsy Rats from Strasbourg (GAERS) are very useful for understanding the fundamental mechanisms associated with human epilepsy. Individual regions of the brain have different protein composition in different conditions. Therefore, proteomic analyses of the brain compartments are preferred for the development of new therapeutic targets in different pathophysiological conditions like neurodegenerative disorders. In this study, we describe a proteomic profiling of membrane fraction of cortex tissue from epileptic GAERS and non-epileptic Wistar rat brain by two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption/ionization mass spectroscopy. Comparing the optical density of spots between groups, we found that one protein expression was significantly down-regulated (guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1) and one protein expression was significantly up-regulated (14-3-3 protein epsilon isoform) in GAERS group. Our results indicate that these proteins might have played a significant role in epilepsy and may be considered as valuable therapeutic targets in the absence of epilepsy.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.

High sensitivity automated multiplexed immunoassays using photonic crystal enhanced fluorescence microfluidic system

We demonstrate a platform that integrates photonic crystal enhanced fluorescence (PCEF) detection of a surface-based microspot fluorescent assay with a microfluidic cartridge to achieve simultaneous goals of high analytic sensitivity (single digit pg/mL), high selectivity, low sample volume, and assay automation. The PC surface, designed to provide optical resonances for the excitation wavelength and emission wavelength of Cyanines 5 (Cy5), was used to amplify the fluorescence signal intensity measured from a multiplexed biomarker microarray. The assay system is comprised of a plastic microfluidic cartridge for holding the PC and an assay automation system that provides a leak-free fluid interface during introduction of a sequence of fluids under computer control. Through the use of the assay automation system and the PC embedded within the microfluidic cartridge, we demonstrate pg/mL-level limits of detection by performing representative biomarker assays for interleukin 3 (IL3) and Tumor Necrosis Factor (TNF-α). The results are consistent with limits of detection achieved without the use of the microfluidic device with the exception that coefficients of variability from spot-to-spot are substantially lower than those obtained by performing assays with manual manipulation of assay liquids. The system's capabilities are compatible with the goal of diagnostic instruments for point-of-care settings.

Cerebrospinal fluid protein dynamic driver network: At the crossroads of brain tumorigenesis

To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In our controlled rat model study, matched ENU- and saline-exposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. Future characterization of the critical transition state (P60) during the brain tumor progression may reveal the underlying pathophysiology to device novel therapeutics preventing tumor formation. More detailed method and information are accessible through our website at http://translationalmedicine.stanford.edu.

Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer

PURPOSE

Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers.

EXPERIMENTAL DESIGN

Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples.

RESULTS

We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting.

CONCLUSIONS AND CLINICAL RELEVANCE

We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening.

Segregation of ovarian cancer stage exploiting spectral biomarkers derived from blood plasma or serum analysis: ATR-FTIR spectroscopy coupled with variable selection methods

Ovarian cancer is a solid tumor and a leading cause of mortality. Diagnostic tools for the detection of early stage (stage I) ovarian cancer are urgently needed. For this purpose, attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) coupled with variable selection methods, successive projection algorithm or genetic algorithm (GA) combined with linear discriminant analysis (LDA), were employed to identify spectral biomarkers in blood plasma or serum samples for accurate diagnosis of different stages of ovarian cancer, histological type and segregation based on age. Three spectral datasets (stage I vs. stage II-IV; serous vs. non-serous carcinoma; and, ≤60 years vs. >60 years) were processed: sensitivity and specificity required for real-world diagnosis of ovarian cancer was achieved. Toward segregating stage I vs. stage II-IV, sensitivity and specificity (plasma blood) of 100% was achieved using a GA-LDA model with 33 wavenumbers. For serous vs. non-serous category (plasma blood), the sensitivity and specificity levels, using 29 wavenumbers by GA-LDA, were remarkable (up to 94%). For ≤60 years and >60 years categories (plasma blood), the sensitivity and specificity, using 42 wavenumbers by GA-LDA, gave complete accuracy (100%). For serum samples, sensitivity and specificity results gave relatively high accuracy (up to 91.6% stage I vs. stage II-IV; up to 93.0% serous vs. non-serous; and, up to 96.0% ≤60 years vs. >60 years) using several wavenumbers. These findings justify a prospective population-based assessment of biomarkers signatures using ATR-FTIR spectroscopy as a screening tool for stage of ovarian cancer.

Identification of epithelial ovarian tumor-specific aptamers

Ovarian cancer is often diagnosed in late stages with few treatment options and poor long-term prognosis. New clinical tools for early detection of ovarian malignancies will significantly help reduce mortality and improve current long-term survival rates. The objective of this work was to identify ovarian tumor-specific single-stranded DNA aptamers that bind to malignant ovarian tumor cells and internalize with high affinity and specificity. Aptamers can identify unique tumor biomarkers, can aid in early detection and diagnosis of neoplastic disorders, and can be functionalized by conjugation to small molecules. To identify aptamers from random single-stranded DNA pools (60 bases long), we used whole Cell-SELEX (systematic evolution of ligands by exponential enrichment) to enrich and isolate tumor-specific aptamers that bind to tumor-specific receptors in their native state on the cell surface. Next-Generation sequencing identified seven novel aptamers and detailed analyses of three are described. Aptamers bound to, and were internalized by, target Caov-3 cell populations, but not nontarget nonmalignant ovarian epithelial HOSE 6-3 cells or multiple other epithelial tumor cell lines. Furthermore, aptamers showed unique binding affinities with apparent dissociation constants (Kd) measuring in the submicromolar range supporting their physiological relevance and potential use in clinical applications.

Validation of LRG1 as a potential biomarker for detection of epithelial ovarian cancer by a blinded study

Background

Leucine-rich alpha-2-glycoprotein (LRG1) was found to be differentially expressed in sera from patients with Epithelial Ovarian Cancer (EOC). The aim of this study is to investigate the performance of LRG1 for detection of EOC, including early stage EOC, and to evaluate if LRG1 can complement CA125 in order to improve EOC detection using two independent blinded sample sets.

Methods and Results

Serum LRG1 and CA125 were measured by immunoassays. All assays were performed blinded to clinical data. Using the two independent sample sets (156 participants for sample set 1, and 233 for sample set 2), LRG1 was differentially expressed in EOC cases as compared to healthy, surgical, and benign controls, and its performance was not affected by the conditions of blood collection. The areas under the ROC curve (AUC) for LRG1 in differentiating EOC cases from non-cases were 0.797 and 0.786 for sample set 1 and 2. For differentiating EOC cases from healthy controls, the AUC values for LRG1 were 0.792 and 0.794. At a fixed specificity of 95%, LRG1 detects 52%, and 53.5% of EOC cases from healthy controls for sample set 1 and 2. When combining LRG1 and CA125, the AUC value increased to 0.927, which was improved compared to CA125 (AUC=0.916) (p=0.008) alone in distinguishing EOC cases from non-cases. More importantly, LRG1 also showed potential performance in differentiating early stage EOC from non-cases with an AUC of 0.715 for sample set 1, and 0.690 for sample set 2. The combination of LRG1 and CA125 resulted in an AUC of 0.838, which outperforms CA125 (AUC=0.785) (p=0.018) in detecting early stage EOC cases from non-cases using the larger sample set.

Conclusions

LRG1 could be a useful biomarker alone or in combination with CA125 for the diagnosis of ovarian cancer.

Reorganization of low-molecular-weight fraction of plasma proteins in the annual cycle of cyprinidae

Reorganization of the low-molecular-weight fraction of cyprinid plasma was analyzed using various electrophoretic techniques (disc electrophoresis, electrophoresis in polyacrylamide concentration gradient, in polyacrylamide with urea, and in SDS-polyacrylamide). The study revealed coordinated changes in the low-molecular-weight protein fractions with seasonal dynamics and related reproductive rhythms of fishes. We used cultured species of the Cyprinidae family with sequenced genomes for the detection of these interrelations in fresh-water and anadromous cyprinid species. The common features of organization of fish low-molecular-weight plasma protein fractions made it possible to make reliable identification of their proteins. MALDI mass-spectrometry analysis revealed the presence of the same proteins (hemopexin, apolipoproteins, and serpins) in the low-molecular-weight plasma fraction in wild species and cultured species with sequenced genomes (carp, zebrafish). It is found that the proteins of the first two classes are organized as complexes made of protein oligomers. Stoichiometry of these complexes changes in concordance with the seasonal and reproductive rhythms.

Usefulness of diagnostic indices comprising clinical, sonographic, and biomarker data for discriminating benign from malignant ovarian masses

The objective of this study was to review the accuracy of indices combining several diagnostic variables, in comparison to other models, sonography alone, and biomarker assays, for predicting benign or malignant ovarian lesions. Different single modalities were reviewed. The most useful complex models were International Ovarian Tumor Analysis (IOTA) sonographic logistic regression model 2 (area under the curve, 0.949), risk of malignancy index-cancer antigen 125-human epididymis protein 4 (0.950), risk of malignancy algorithm (0.953), pelvic mass score (0.960), non-IOTA logistic regression model (0.970), and histoscanning score logistic regression model (0.970). None of the indices was superior to an expert subjective sonographic assessment (0.968). For women with adnexal tumors, indices with high accuracy are available that are applicable in clinical practice and comparable to an expert subjective sonographic assessment for discriminating benign from malignant masses.

Evaluation of haemoglobin in blister fluid as an indicator of paediatric burn wound depth

The early and accurate assessment of burns is essential to inform patient treatment regimens; however, this first critical step in clinical practice remains a challenge for specialist burns clinicians worldwide. In this regard, protein biomarkers are a potential adjunct diagnostic tool to assist experienced clinical judgement. Free circulating haemoglobin has previously shown some promise as an indicator of burn depth in a murine animal model. Using blister fluid collected from paediatric burn patients, haemoglobin abundance was measured using semi-quantitative Western blot and immunoassays. Although a trend was observed in which haemoglobin abundance increased with burn wound severity, several patient samples deviated significantly from this trend. Further, it was found that haemoglobin concentration decreased significantly when whole cells, cell debris and fibrinous matrix was removed from the blister fluid by centrifugation; although the relationship to depth was still present. Statistical analyses showed that haemoglobin abundance in the fluid was more strongly related to the time between injury and sample collection and the time taken for spontaneous re-epithelialisation. We hypothesise that prolonged exposure to the blister fluid microenvironment may result in an increased haemoglobin abundance due to erythrocyte lysis, and delayed wound healing.

Important options available--from start to finish--for translating proteomics results to clinical chemistry

In the realm of clinical chemistry, the field of clinical proteomics, that is, the application of proteomic methods for understanding mechanisms and enabling diagnosis, prediction, measurement of activity, and treatment response in disease, is first and foremost a discovery and research tool that feeds assay development downstream. Putative new assay candidates generated by proteomics discovery projects compete with well-established assays with known indications, well-described performance, and of known value in specific clinical settings. Careful attention to the many options available in the design, execution, and interpretation of clinical proteomics studies is thus necessary for translation into clinical practice. We here review and discuss important options associated with clinical proteomics endeavors stretching from the planning phases to the final use in clinical chemistry.

Proteomic cancer biomarkers from discovery to approval: it's worth the effort

The current landscape of cancer biomarkers is changing rapidly, with new and exciting developments. With the advances of proteomic technologies, many potential cancer biomarkers have been discovered. However, the number of new cancer biomarkers cleared or approved by the US FDA is rather limited. Although technological advances are important, clearly defining intended use, good study design and appropriate patient specimens are critical for the success of FDA approval. While obtaining FDA clearance/approval for newly developed and clinically useful cancer biomarkers has been slow, the reward for patient care could be enormous.

Costs, effectiveness, and workload impact of management strategies for women with an adnexal mass

BACKGROUND

We compared the estimated clinical outcomes, costs, and physician workload resulting from available strategies for deciding which women with an adnexal mass should be referred to a gynecologic oncologist.

METHODS

We used a microsimulation model to compare five referral strategies: 1) American Congress of Obstetricians and Gynecologists (ACOG) guidelines, 2) Multivariate Index Assay (MIA) algorithm, 3) Risk of Malignancy Algorithm (ROMA), 4) CA125 alone with lowered cutoff values to prioritize test sensitivity over specificity, 5) referral of all women (Refer All). Test characteristics and relative survival were obtained from the literature and data from a biomarker validation study. Medical costs were estimated using Medicare reimbursements. Travel costs were estimated using discharge data from Surveillance, Epidemiology and End Results-Medicare and State Inpatient Databases. Analyses were performed separately for pre- and postmenopausal women (60 000 "subjects" in each), repeated 10 000 times.

RESULTS

Refer All was cost-effective compared with less expensive strategies in both postmenopausal (incremental cost-effectiveness ratio [ICER] $9423/year of life saved (LYS) compared with CA125) and premenopausal women (ICER $10 644/YLS compared with CA125), but would result in an additional 73 cases/year/subspecialist. MIA was more expensive and less effective than Refer All in pre- and postmenopausal women. If Refer All is not a viable option, CA125 is an optimal strategy in postmenopausal women.

CONCLUSIONS

Referral of all women to a subspecialist is an efficient strategy for managing women with adnexal masses requiring surgery, assuming sufficient capacity for additional surgical volume. If a test-based triage strategy is needed, CA125 with lowered cutoff values is a cost-effective strategy.

Correlation of apolipoprotein A-I kinetics with survival and response to first-line platinum-based chemotherapy in advanced non-small cell lung cancer

The aim of this study was to determine whether apolipoprotein A-I (ApoA-I) kinetics predict the overall survival in patients with advanced-stage non-small cell lung cancer (NSCLC) during platinum-based first-line therapy. A total of 125 NSCLC patients from January 2008 to September 2014 were retrospectively reviewed. Serum ApoA-I level was measured at baseline and thereafter at the start of each palliative chemotherapy cycle for all patients. Patients were divided into four groups according to ApoA-I kinetics. Patients whose ApoA-I ≥ 1.01 g/L and never decreased during treatment, patients whose ApoA-I ≥ 1.01 g/L and decreased (ApoA-I < 1.01 g/L) at least one time during treatment, patients whose ApoA-I < 1.01 g/L and normalized (ApoA-I ≥ 1.01) at least one time during treatment, and patients whose ApoA-I < 1.01 g/L and never normalized during treatment were assigned to non-decreased, decreased, normalized, and non-normalized ApoA-I groups, respectively. Overall survival rates were significantly different between the four groups, with 2-year survival rates of 88.6 and 17.5 % for the non-decreased and the decreased ApoA-I groups, respectively, and none survived 2 years later in the normalized and the non-normalized ApoA-I groups. When compared with the non-decreased group, the hazard ratios of death were 0.05, 0.44, and 1.73 in the normalized, decreased, and non-normalized groups, respectively (P < 0.001). Normalization of ApoA-I was associated with a low risk of progression, whereas patients with a decreased level of ApoA-I showed a progression of disease in most cases. ApoA-I can be a novel, widely available biomarker for patients with NSCLC.

Biomarkers identified from serum proteomic analysis for the differential diagnosis of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves different organs. Its most important feature is the production of specific autoantibodies against nuclear or cytoplasmic antigens. Proteomic analysis of serum, as one of the most readily available body fluids, can be used as a method for clarifying the pathogenesis of SLE. In this study the serum proteome of 13 patients with SLE was evaluated and compared with seven healthy control participants. A specific kit was used to remove high-abundance proteins. After depletion, the protein expression patterns created by two-dimensional gel electrophoresis (2-DE) and MALDI-TOF/TOF-MS were used to identify disease-associated proteins. We found differential expression of 15 protein spots, including seven up-regulated and eight down-regulated proteins in SLE samples, in comparison with healthy participants. These spots were identified by MALDI-TOF/TOF-MS and classified into three groups include keratins, apolipoproteins and albumin, and individual proteins such as transthyretin, haptoglobin and prothrombin. These findings can help to clarify the pathophysiology and mechanism of SLE.

Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

Discovery of serum biomarkers of ovarian cancer using complementary proteomic profiling strategies

Purpose

Ovarian cancer is a devastating disease and biomarkers for its early diagnosis are urgently required. Serum may be a valuable source of biomarkers that may be revealed by proteomic profiling. Herein, complementary serum protein profiling strategies were employed for discovery of biomarkers that could discriminate cases of malignant and benign ovarian cancer.

Experimental design

Identically collected and processed serum samples from 22 cases of invasive epithelial ovarian cancer, 45 benign ovarian neoplasms, and 64 healthy volunteers were subjected to immunodepletion and protein equalization coupled to 2D‐DIGE/MS and multidimensional fractionation coupled to SELDI‐TOF profiling with MS/MS for protein identification. Selected candidates were verified by ELISA in samples from malignant (n = 70) and benign (n = 89) cases and combined marker panels tested against serum CA125.

Results

Both profiling platforms were complementary in identifying biomarker candidates, four of which (A1AT, SLPI, APOA4, VDBP) significantly discriminated malignant from benign cases. However, no combination of markers was as good as CA125 for diagnostic accuracy. SLPI was further tested as an early marker using prediagnosis serum samples. While it rose in cases toward diagnosis, it did not discriminate prediagnosis cases from controls.

Conclusions and clinical relevance

The candidate biomarkers warrant further validation in independent sample sets.

Profiling proteoforms: promising follow-up of proteomics for biomarker discovery

Today, proteomics usually compares clinical samples by use of bottom-up profiling with high resolution mass spectrometry, where all protein products of a single gene are considered as an integral whole. At the same time, proteomics of proteoforms, which considers the variety of protein species, offers the potential to discover valuable biomarkers. Proteoforms are protein species that arise as a consequence of genetic polymorphisms, alternative splicing, post-translational modifications and other less-explored molecular events. The comprehensive observation of proteoforms has been an exclusive privilege of top-down proteomics. Here, we review the possibilities of a bottom-up approach to address the microheterogeneity of the human proteome. Special focus is given to shotgun proteomics and structure-based bioinformatics as a source of hypothetical proteoforms, which can potentially be verified by targeted mass spectrometry to determine the relevance of proteoforms to diseases.

Label-free LC-MSe in tissue and serum reveals protein networks underlying differences between benign and malignant serous ovarian tumors

Purpose

To identify proteins and (molecular/biological) pathways associated with differences between benign and malignant epithelial ovarian tumors.

Experimental Procedures

Serum of six patients with a serous adenocarcinoma of the ovary was collected before treatment, with a control group consisting of six matched patients with a serous cystadenoma. In addition to the serum, homogeneous regions of cells exhibiting uniform histology were isolated from benign and cancerous tissue by laser microdissection. We subsequently employed label-free liquid chromatography tandem mass spectrometry (LC-MS^e) to identify proteins in these serum and tissues samples. Analyses of differential expression between samples were performed using Bioconductor packages and in-house scripts in the statistical software package R. Hierarchical clustering and pathway enrichment analyses were performed, as well as network enrichment and interactome analysis using MetaCore.

Results

In total, we identified 20 and 71 proteins that were significantly differentially expressed between benign and malignant serum and tissue samples, respectively. The differentially expressed protein sets in serum and tissue largely differed with only 2 proteins in common. MetaCore network analysis, however inferred GCR-alpha and Sp1 as common transcriptional regulators. Interactome analysis highlighted 14-3-3 zeta/delta, 14-3-3 beta/alpha, Alpha-actinin 4, HSP60, and PCBP1 as critical proteins in the tumor proteome signature based on their relative overconnectivity. The data have been deposited to the ProteomeXchange with identifier PXD001084.

Discussion

Our analysis identified proteins with both novel and previously known associations to ovarian cancer biology. Despite the small overlap between differentially expressed protein sets in serum and tissue, APOA1 and Serotransferrin were significantly lower expressed in both serum and cancer tissue samples, suggesting a tissue-derived effect in serum. Pathway and subsequent interactome analysis also highlighted common regulators in serum and tissue samples, suggesting a yet unknown role for PCBP1 in ovarian cancer pathophysiology.

Proteomics analysis for finding serum markers of ovarian cancer

A combination of peptide ligand library beads (PLLB) and 1D gel liquid chromatography-mass spectrometry/mass spectrometry (1DGel-LC-MS/MS) was employed to analyze serum samples from patients with ovarian cancer and from healthy controls. Proteomic analysis identified 1200 serum proteins, among which 57 proteins were upregulated and 10 were downregulated in the sera from cancer patients. Retinol binding protein 4 (RBP4) is highly upregulated in the ovarian cancer serum samples. ELISA was employed to measure plasma concentrations of RBP4 in 80 samples from ovarian cancer patients, healthy individuals, myoma patients, and patients with benign ovarian tumor, respectively. The plasma concentrations of RBP4 ranging from 76.91 to 120.08 ng/mL with the mean value 89.13 ± 1.67 ng/mL in ovarian cancer patients are significantly higher than those in healthy individuals (10.85 ± 2.38 ng/mL). Results were further confirmed with immunohistochemistry, demonstrating that RBP4 expression levels in normal ovarian tissue were lower than those in ovarian cancer tissues. Our results suggested that RBP4 is a potential biomarker for diagnostic of screening ovarian cancer.

In 2014, can we do better than CA125 in the early detection of ovarian cancer?

Ovarian cancer is a lethal gynecologic malignancy with greater than 70% of women presenting with advanced stage disease. Despite new treatments, long term outcomes have not significantly changed in the past 30 years with the five-year overall survival remaining between 20% and 40% for stage III and IV disease. In contrast patients with stage I disease have a greater than 90% five-year overall survival. Detection of ovarian cancer at an early stage would likely have significant impact on mortality rate. Screening biomarkers discovered at the bench have not translated to success in clinical trials. Existing screening modalities have not demonstrated survival benefit in completed prospective trials. Advances in high throughput screening are making it possible to evaluate the development of ovarian cancer in ways never before imagined. Data in the form of human “-omes” including the proteome, genome, metabolome, and transcriptome are now available in various packaged forms. With the correct pooling of resources including prospective collection of patient specimens, integration of high throughput screening, and use of molecular heterogeneity in biomarker discovery, we are poised to make progress in ovarian cancer screening. This review will summarize current biomarkers, imaging, and multimodality screening strategies in the context of emerging technologies.

The role of proteomics in understanding biological mechanisms of sepsis

Sepsis is a systemic inflammatory state caused by infection. Complications of this infection with multiple organ failure lead to more lethal conditions, such as severe sepsis and septic shock. Sepsis is one of the leading causes of US deaths. Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for improvement of patient outcomes through the development of new therapies. Mass spectrometry-based proteomics offers powerful tools to identify such biomarkers and furthermore to give insight to fundamental mechanisms of this clinical condition. In this review, we summarize findings from proteomics studies of sepsis and how their applications have provided more understanding into the pathogenesis of septic infection. Literatures related to "proteomics", "sepsis", "systemic inflammatory response syndrome", "severe sepsis", "septic infection", and "multiple organ dysfunction syndrome" were searched using PubMed. Findings about neonatal and adult sepsis are discussed separately. Within the adult sepsis studies, results are grouped based on the models (e.g., human or animal). Across investigations in clinical populations and in rodent and mammalian animal models, biological pathways, such as inflammatory and acute phase response, coagulation, complement, mitochondrial energy metabolism, chaperones, and oxidative stress, are altered at the protein level. These proteomics studies have discovered many novel biomarker candidates of septic infection. Validation the clinical use of these biomarker candidates may significantly impact the diagnosis and prognosis of sepsis. In addition, the molecular mechanisms revealed by these studies may also guide the development of more effective treatments.

Elevated apolipoprotein A-I levels are associated with favorable prognosis in metastatic nasopharyngeal carcinoma

The survival outcomes of patients with metastatic nasopharyngeal carcinoma (NPC) differ significantly between individuals. Serum lipids and lipoproteins have been reported to be associated with prognosis in some cancers, but it has not been studied in metastatic NPC. The aim of this study was to evaluate whether serum lipid and lipoproteins could predict the prognosis of metastatic NPC patients. Eight hundred and seven patients with metastatic NPC were analyzed retrospectively, and the values of serum lipids and lipoproteins at baseline were retrieved. Receiver operating characteristic curve analysis and univariate and multivariate Cox proportional hazards analyses were used to evaluate the associations of serum lipids and lipoproteins with overall survival (OS). Univariate analysis revealed that higher values of baseline cholesterol (≥4.655 mmol/L), baseline high-density lipoprotein cholesterol (≥0.965 mmol/L), and baseline apolipoprotein A-I (ApoA-I) (≥1.065 g/L) were significantly associated with superior OS (p < 0.001), respectively. Multivariate Cox proportional hazard analysis showed that higher ApoA-I level (vs. lower ApoA-I level, HR 0.64, 95 % CI 0.52-0.80, p < 0.001) was an independent protective factor against progression. In addition, higher body mass index, earlier N stages, single lesion, and absence of liver metastasis were also revealed to be independent protective factors. In conclusion, the elevated baseline ApoA-I level may predict those patients likely to have a favorable OS.

APOA1 mRNA expression in ovarian serous carcinoma effusions is a marker of longer survival

OBJECTIVES

We previously described the overexpression of APOA1 and GPX3 in ovarian/peritoneal serous carcinoma compared with breast carcinoma effusions using gene expression array analysis. The objective of the present study was to validate this finding and to analyze the association between these genes and clinicopathologic parameters, including survival, in advanced-stage ovarian serous carcinoma.

METHODS

APOA1 and GPX3 mRNA expression using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was analyzed in 121 effusions (101 ovarian, 20 breast carcinomas) and 85 solid ovarian carcinoma specimens (43 primary carcinomas, 42 metastases).

RESULTS

APOA1 and GPX3 transcript levels were significantly higher in ovarian carcinoma at all anatomic sites compared with breast carcinoma effusions (P < .001). GPX3 mRNA levels were significantly higher in primary carcinomas and solid metastases from patients who received neoadjuvant chemotherapy compared with chemo-naïve tumors (P = .016). APOA1 and GPX3 mRNA levels in the entire effusion series were unrelated to clinicopathologic parameters. However, higher APOA1 mRNA levels in primary diagnosis pre-chemotherapy effusions were significantly related to better overall survival (P = .045), a finding that retained its significance in Cox multivariate analysis (P = .016).

CONCLUSIONS

APOA1 and GPX3 mRNA levels on qRT-PCR effectively differentiate ovarian from breast carcinoma. APOA1 may be a novel prognostic marker in metastatic serous carcinoma.

Analysis of the differences of serum protein mass spectrometry in patients with triple negative breast cancer and non-triple negative breast cancer

The objective of the present study was to investigate differences of serum protein mass spectrometry in patients with triple negative breast cancer (TNBC) and non-TNBC and thus to search for candidate serum protein biomarkers for identification and diagnosis of TNBC. Thirty serum samples from patients with TNBC without any treatment and 30 serum samples from patients with non-TNBC without any treatment were detected by using two-dimensional gel electrophoresis and matrix-assisted laser dissociation tandem time-of-flight mass spectrometry (MALDI-TOF-MS). PDQest 7.0 software of Bio-Rad was adopted to screen differentially expressed proteins. Protein ID retrieval was conducted by using Mascot software to confirm the results of differential proteins. Two-dimensional gel electrophoresis profiles were obtained successfully. A total of 16 differential protein loci were discovered by analyzing patient sera of the two groups using two-dimensional gel electrophoresis analysis software. Ten differential proteins were identified by mass spectrometric analysis in the 16 differential proteins. Combined with database and literature search results, it is speculated that the specifically upregulated proteins and downregulated proteins including transthyretin, haptoglobin, and antitrypsin may be the potential markers for early diagnosis of TNBC. Comparing the TNBC patients with the non-TNBC patients, there are differences in serum protein compositions. The ten differential proteins discovered in the present study provide reference basis for further improving early diagnosis and identification and diagnosis index of TNBC. Especially, transthyretin, haptoglobin, and antitrypsin show dramatic significances for the early diagnosis of TNBC.

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

Introduction

Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.

Methods

Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.

Results

From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.

Conclusions

Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

Site-specific glycan microheterogeneity of inter-alpha-trypsin inhibitor heavy chain H4

Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) is a 120 kDa acute-phase glycoprotein produced primarily in the liver, secreted into the blood, and identified in serum. ITIH4 is involved in liver development and stabilization of the extracellular matrix (ECM), and its expression is altered in liver disease. In this study, we aimed to characterize glycosylation of recombinant and serum-derived ITIH4 using analytical mass spectrometry. Recombinant ITIH4 was analyzed to optimize glycopeptide analyses, followed by serum-derived ITIH4. First, we confirmed that the four ITIH4 N-X-S/T sequons (N81, N207, N517, and N577) were glycosylated by treating ITIH4 tryptic/GluC glycopeptides with PNGaseF in the presence of (18)O water. Next, we performed glycosidase-assisted LC-MS/MS analysis of ITIH4 trypsin-GluC glycopeptides enriched via hydrophilic interaction liquid chromatography to characterize ITIH4 N-glycoforms. While microheterogeneity of N-glycoforms differed between ITIH4 protein expressed in HEK293 cells and protein isolated from serum, occupancy of N-glycosylation sites did not differ. A fifth N-glycosylation site was discovered at N274 with the rare nonconsensus NVV motif. Site N274 contained high-mannose N-linked glycans in both serum and recombinant ITIH4. We also identified isoform-specific ITIH4 O-glycoforms and documented that utilization of O-glycosylation sites on ITIH4 differed between the cell line and serum.

Differential levels of L-homocysteic acid and lysophosphatidylcholine (16:0) in sera of patients with ovarian cancer

Ovarian cancer (OVC) is one of the most difficult types of cancer to detect in the early stages of its development. There have been numerous attempts to identify a biomarker for OVC; however, an accurate diagnostic marker has yet to be identified. The present study profiled OVC candidate metabolites from the serum to identify potential diagnostic markers for OVC. Data regarding low-mass ions (LMIs) in the serum were obtained using matrix-assisted laser desorption/ionization (MALDI)-time-of-flight analysis. MALDI-mass spectrometry (MS) analysis of each serum sample was repeated six times in order to reduce the likelihood of experimental errors. The intensity of the LMI mass peaks were normalized using total peak area sums. The normalized intensity of LMI was used in principal component analysis-discriminant analysis to differentiate between 142 patients with OVC and 100 healthy control participants. Liquid chromatography-MS/MS was used to identify the selected LMIs. Extracted ion chromatogram analysis was used to measure the relative quantity of candidate metabolites from the LMI mass peak areas. The concentration of common metabolites in the serum was determined using ELISA. The top 20 LMI mass peaks with a weigh factor over 0.05 were selected to distinguish between the patients with OVC and the controls. Among the LMIs, two with 184.05 and 496.30 m/z were identified as L-homocysteic acid (HCA) and lysophosphatidylcholine (LPC) (16:0), respectively. The relative quantity of LPC (16:0) was found to be decreased in the OVC serum (P=0.05), while the quantity of HCA was observed to be significantly higher in the OVC serum (P<0.001). HCA was not detected in 59 cases out of the 63 control participants; however, the majority of the cases of OVC (16/25) exhibited significantly higher quantities of HCA. When the cutoff was 10 nmol/ml, the sensitivity and specificity of HCA were 64.0 and 96.9%, respectively. The level of LPC (16:0) was significantly correlated with tumor grade (P=0.045). HCA and LPC (16:0) showed correlation with stage and tumor histology, but the limited sample size resulted in a lack of statistical significance. The findings of the present study suggest that HCA may have potential to be a biomarker for OVC. The stratified screening including LPC (16:0) did not significantly increase the power for OVC screening; however, the present study showed that profiling LMIs in serum may be useful for identifying candidate metabolites for OVC screening.

On best practices: the Institute of Medicine scheme for developing, validating, and demonstrating clinical utility of omics-based diagnostic and predictive tests

The Institute of Medicine of the US National Academy of Sciences issued a major report in 2012 that provides important guidance for the proteomics community for credible and transparent development of all kinds of omics-based diagnostic and prognostic tests. The key elements are summarized here to provide a compass that can guide the studies emerging from many laboratories as reported in this special issue of Proteomics Clinical Applications on "Diagnostic Proteomics."

Inter-alpha-trypsin inhibitor heavy chain H4 as a diagnostic and prognostic indicator in patients with hepatitis B virus-associated hepatocellular carcinoma

OBJECTIVES

Inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) is associated with various diseases. We evaluated the diagnostic and prognostic significance of serum ITIH4 levels in healthy controls and patients with chronic hepatitis B (CHB), hepatitis B virus (HBV)-related liver cirrhosis, and HBV-related hepatocellular carcinoma (HCC).

DESIGN AND METHODS

The study enrolled 300 individuals (50 healthy controls, 50 with CHB, 100 with HBV-associated cirrhosis, and 100 with HBV-associated HCC). Serum ITIH4 levels were determined by western blot analysis and expressed in densitometry units (DU).

RESULTS

ITIH4 levels were higher in CHB (mean: 252.96 DU) and liver cirrhosis (mean: 206.43 DU) patients than in healthy controls (mean: 75.92 DU) and HCC patients (mean: 92.86 DU) (P<0.001). The area under the receiver operating characteristic curve was 0.71 for the diagnosis of HCC in patients with HBV-related liver disease. Multivariate Cox regression analysis showed that large tumor size (≥5 cm) was independently associated with overall survival (hazard ratio 5.894, 95% confidence interval 1.373-25.300, P=0.017). A Kaplan-Meier survival analysis showed significantly worse survival among HCC patients with both low ITIH4 (<80 DU) and a large tumor size compared to that among other HCC patients (P<0.001), and among patients with high AFP (>200 ng/mL) and low ITIH4 compared to that among other HCC patients (P=0.041).

CONCLUSIONS

Serum ITIH4 levels are reduced in HCC patients compared to that in CHB and cirrhosis patients, and low serum ITIH4 levels are associated with shorter survival in HBV-associated HCC patients.

Alternatives to risk-reducing surgery for ovarian cancer

BRCA1 and BRCA2 mutation carriers have an 18%-60% and 11%-27% lifetime risk of developing ovarian carcinoma, respectively. Prophylactic bilateral salpingo-oophorectomy reduces the risk of this malignancy by up to 96%. Gynecological screening programs with periodical trans-vaginal ultrasound and serum CA125 assay have been widely used in women at hereditary high risk of ovarian carcinoma, but clinical results have been conflicting. These surveillance protocols have often fallen short of expectations because of the advanced stage of ovarian carcinoma in the identified screened women. Several investigations have been addressed to the detection of additional tumor markers able to generate more reliable screening tools. The combined serum assay of leptin, prolactin, osteopontin, CA125, macrophage inhibiting factor and insulin-like growth factor-II appears to have a significant better diagnostic reliability compared with serum CA125 alone in discriminating healthy individuals from ovarian carcinoma patients, and therefore, it could have a role in the screening of women at high risk for this malignancy. As far as chemoprevention is concerned, oral contraceptives significantly reduce the ovarian carcinoma risk also in BRCA mutation carriers, whereas the efficacy of fenretinide is still under investigation.