Deep depletion of abundant serum proteins reveals low-abundant proteins as potential biomarkers for human ovarian cancer

The function of the inter-alpha-trypsin inhibitors in the development of disease

Through the formation of covalent connections with hyaluronic acid (HA), the inter-α-trypsin inhibitor (IαI) family collaborates to preserve the stability of the extracellular matrix (ECM). The five distinct homologous heavy chains (ITIH) and one type of light chain make up the IαI family. ITIH alone or in combination with bikunin (BK) has been proven to have important impacts in a number of earlier investigations. This implies that BK and ITIH might be crucial to both physiological and pathological processes. The functions of BK and ITIH in various pathophysiological processes are discussed independently in this paper. In the meanwhile, this study offers suggestions for further research on the roles of BK and ITIH in the course of disease and summarizes the plausible mechanisms of the previous studies.

Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis-Support Vector Machine (PCA-SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9-92.5% CA, 80-95% sensitivity and 80-90% specificity. AUC scores in the range of 0.82-0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.

Study on the regulatory mechanism and experimental verification of icariin for the treatment of ovarian cancer based on network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

Herba Epimedii (Berberidaceae) has the advantages of "nourishing the kidney and reinforcing the Yang". Many species in this genus have long been used in traditional Chinese medicine (TCM) and have been used as anticancer drugs in traditional Chinese herbal medicine formulations. Icariin, a major flavonoid glycoside extracted from Epimedium brevicornum Maxim, has been widely proven to exert an inhibitory effect on ovarian cancer (OC), and icariin can induce apoptosis and inhibit invasion and migration. However, the underlying mechanism remains unclear, so further research is necessary to verify its traditional use.

AIM OF THE STUDY

This study aimed to explore the regulatory mechanism of icariin in the biological network and signalling pathway of OC through network pharmacology and cytological experiments.

METHODS

Public databases and R × 3.6.2 software were adopted to predict the potential targets, construct the protein-protein interaction (PPI) network, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. After the network pharmacological analysis, cytological experiments, real-time quantitative PCR (qPCR) and Western blot (WB) analyses were used to verify the key signalling pathway.

RESULTS

The targets related to treatment were TNF, MMP9, STAT3, PIK3CA, ERBB2, MTOR, IL2, PTGS2, KDR, and F2. GO and KEGG enrichment analyses indicated that various kinases and the PI3K/AKT signalling pathway were the most enriched molecules and pathways. Icariin inhibited OC SKOV3 cell proliferation, migration and invasion in vitro and promoted apoptosis by inhibiting the PI3K/AKT signalling pathway.

CONCLUSION

Icariin promotes apoptosis and suppresses SKOV3 cell activities through the PI3K-Akt signalling pathway. This research not only provides a theoretical and experimental basis for more in-depth studies but also offers an efficient method for the rational utilization of a series of icariin flavonoids as anti-tumour drugs.

Update on Proteomic approaches to uncovering virus-induced protein alterations and virus -host protein interactions during the progression of viral infection

INTRODUCTION

Viruses induce profound changes in the cells they infect. Understanding these perturbations will assist in designing better therapeutics to combat viral infection. System-based proteomic assays now provide unprecedented opportunity to monitor large numbers of cellular proteins.

AREAS COVERED

This review will describe various quantitative and functional mass spectrometry-based methods, and complementary non-mass spectrometry-based methods, such as aptamer profiling and proximity extension assays, and examples of how each are used to delineate how viruses affect host cells, identify which viral proteins interact with which cellular proteins, and how these change during the course of a viral infection. PubMed was searched multiple times prior to manuscript submissions and revisions, using virus, viral, proteomics; in combination with each keyword. The most recent examples of published works from each search were then analyzed.

EXPERT OPINION

There has been exponential growth in numbers and types of proteomic analyses in recent years. Continued development of reagents that allow increased multiplexing and deeper proteomic probing of the cell, at quantitative and functional levels, enhancements that target more important protein modifications, and improved bioinformatics software tools and pathway prediction algorithms will accelerate this growth and usher in a new era of host proteome understanding.

Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives

Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.

ANGPTL3: a novel biomarker and promising therapeutic target

Angiopoietin-like protein 3 (ANGPTL3) belongs to a multifunctional secreted protein that mainly expresses in the liver, and is regulated by numerous post-translational modifications, including multiple cleavage and glycosylation. Accumulating evidences have revealed that ANGPTL3 plays a critical role in both biological processes, such as lipid metabolism, angiogenesis and haematopoietic function and pathological changes, including atherosclerosis, carcinogenesis, nephrotic syndrome, diabetes, liver diseases and so on. Thus, ANGPTL3 may serve as a potential biomarker in these diseases. Furthermore, ANGPTL3 signalling pathways including LXR/ANGPTL3, thyroid hormone/ANGPTL3, insulin/ANGPTL3 and leptin/ANGPTL3 are also involved in physiological and pathological processes. Some biological ANGPTL3 inhibitors, chemical drugs and traditional Chinese medicine exert beneficial effects by targeting ANGPTL3 directly or indirectly. Therefore, elucidating the effects and underlying mechanisms of ANGPTL3 is essential to develop promising strategies in the diagnosis and treatment of related diseases.

In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion

Identification of cancer and other disease biomarkers in human plasma has been exceptionally challenging due to the complex nature of plasma and the presence of a moderate number of high- and medium-abundance proteins which mask low-abundance proteins of interest. As a result, immunoaffinity depletion formats combining multiple antibodies to target the most abundant plasma proteins have become the first stage in most plasma proteome discovery schemes. This protocol describes the use of tandem IgY 14 and SuperMix immunoaffinity depletion to reproducibly remove >99% of total plasma protein. This greatly increases the depth of analysis of human plasma proteomes. Depleted plasma samples can then be analyzed in a single high-resolution LC-MS/MS run on a Q Exactive Plus mass spectrometer, followed by label-free quantitation. If greater depth of analysis is desired, the depleted plasma can be further fractionated by separating the sample for a short distance on a 1D SDS gel and cutting the gel into uniform slices prior to trypsin digestion. Alternatively, the depleted plasma can be reduced, alkylated, and digested with trypsin followed by high-pH reversed-phase HPLC separation.

Glycoproteomic Analysis of Malignant Ovarian Cancer Ascites Fluid Identifies Unusual Glycopeptides

Ovarian cancer is a major cause of cancer mortality among women, largely due to late diagnosis of advanced metastatic disease. More extensive molecular analysis of metastatic ovarian cancer is needed to identify post-translational modifications of proteins, especially glycosylation that is particularly associated with metastatic disease to better understand the metastatic process and identify potential therapeutic targets. Glycoproteins in ascites fluid were enriched by affinity binding to lectins (ConA or WGA) and other affinity matrices. Separate glycomic, proteomic, and glycopeptide analyses were performed. Relative abundances of different N-glycan groups and proteins were identified from ascites fluids and a serum control. Levels of biomarkers CA125, MUC1, and fibronectin were also monitored in OC ascites samples by Western blot analysis. N-Glycan analysis of ascites fluids showed the presence of large, highly fucosylated and sialylated complex and hybrid glycans, some of which were not observed in normal serum. OC ascites glycoproteins, haptoglobin, fibronectin, lumican, fibulin, hemopexin, ceruloplasmin, alpha-1-antitrypsin, and alpha-1-antichymotrypsin were more abundant in OC ascites or not present in serum control samples. Further glycopeptide analysis of OC ascites identified N- and O-glycans in clusterin, hemopexin, and fibulin glycopeptides, some of which are unusual and may be important in OC metastasis.

Oxyntomodulin Identified as a Marker of Type 2 Diabetes and Gastric Bypass Surgery by Mass-spectrometry Based Profiling of Human Plasma

Low-abundance regulatory peptides, including metabolically important gut hormones, have shown promising therapeutic potential. Here, we present a streamlined mass spectrometry-based platform for identifying and characterizing low-abundance regulatory peptides in humans. We demonstrate the clinical applicability of this platform by studying a hitherto neglected glucose- and appetite-regulating gut hormone, namely, oxyntomodulin. Our results show that the secretion of oxyntomodulin in patients with type 2 diabetes is significantly impaired, and that its level is increased by more than 10-fold after gastric bypass surgery. Furthermore, we report that oxyntomodulin is co-distributed and co-secreted with the insulin-stimulating and appetite-regulating gut hormone glucagon-like peptide-1 (GLP-1), is inactivated by the same protease (dipeptidyl peptidase-4) as GLP-1 and acts through its receptor. Thus, oxyntomodulin may participate with GLP-1 in the regulation of glucose metabolism and appetite in humans. In conclusion, this mass spectrometry-based platform is a powerful resource for identifying and characterizing metabolically active low-abundance peptides.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Quantification, 2DE analysis and identification of enriched glycosylated proteins from mouse muscles: Difficulties and alternatives

One of the problems with 2DE is that proteins present in low amounts in a sample are usually not detected, since their signals are masked by the predominant proteins. The elimination of these abundant proteins is not a guaranteed solution to achieve the desired results. The main objective of this study was the comparison of common and simple methodologies employed for 2DE analysis followed by MS identification, focusing on a pre-purified sample using a wheat germ agglutinin (WGA) column. Adult male C57Black/Crj6 (C57BL/6) mice were chosen as the model animal in this study; the gastrocnemius muscles were collected and processed for the experiments. The initial fractionation with succinylated WGA was successful for the elimination of the most abundant proteins. Two quantification methods were employed for the purified samples, and bicinchoninic acid (BCA) was proven to be most reliable for the quantification of glycoproteins. The gel staining method, however, was found to be decisive for the detection of specific proteins, since their structures affect the interaction of the dye with the peptide backbone. The Coomassie Blue R-250 dye very weakly stained the gel with the WGA purified sample. When the same gel was stained with silver nitrate, however, MS could positively assign 12 new spots. The structure of the referred proteins was not found to be prone to interaction with Coomassie blue.

Insulin-like growth factor binding proteins 4-6

Insulin-like growth factor binding proteins (IGFBPs) 4-6 have important roles as modulators of IGF actions. IGFBP-4 and IGFBP-6 predominantly inhibit IGF actions, whereas IGFBP-5 may enhance these actions under some circumstances. IGFBP-6 is unique among the IGFBPs for its marked IGF-II binding preference. IGFBPs 4-6 are found in the circulation as binary complexes with IGFs that can enter tissues. Additionally, about half of the circulating IGFBP-5 is found in ternary complexes with IGFs and an acid labile subunit; this high molecular complex cannot leave the circulation and acts as an IGF reservoir. IGFBPs 4-6 also have IGF-independent actions. These IGFBPs are regulated in a cell-specific manner and their dysregulation may play a role in a range of diseases including cancer. However, there is no clear clinical indication for measuring serum levels of these IGFBPs at present.

Recent insights into the actions of IGFBP-6

IGFBP-6 is an O-linked glycoprotein that preferentially binds IGF-II over IGF-I. It is a relatively selective inhibitor of IGF-II actions including proliferation, survival and differentiation of a wide range of cells. IGFBP-6 has recently been shown to have a number of IGF-independent actions, including promotion of apoptosis in some cells and inhibition of angiogenesis. IGFBP-6 also induces migration of tumour cells including rhabdomyosarcomas by an IGF-independent mechanism. This chemotactic effect is mediated by MAP kinases. IGFBP-6 binds to prohibitin-2 on the cell surface and the latter is required for IGFBP-6-induced migration by a mechanism that is independent of MAP kinases. IGFBP-6 may enter the nucleus and modulate cell survival and differentiation. IGFBP-6 expression is decreased in a number of cancer cells and it has been postulated to act as a tumour suppressor. IGFBP-6 expression is increased in a smaller number of cancers, which may reflect a compensatory mechanism to control IGF-II actions or IGF-independent actions. The relative balance of IGF-dependent and IGF-independent actions of IGFBP-6 in vivo together with the related question regarding the roles of IGFBP-6 binding to IGF and non-IGF ligands are keys to understanding the physiological role of this protein.

Sample treatment methods involving combinatorial peptide ligand libraries for improved proteomes analyses

If used in an optimized manner, the technology of combinatorial peptide solid-phase libraries can easily improve the analytical determinations of proteomes by several factors. The discovery of novel species and of early stage biomarkers becomes thus reachable with a simple sample treatment. This report describes the most important point to consider (overloading and full recovery) along with a minimum scientific background and gives then detailed recipes to laboratory technicians. Orientations for optional routes are also given according to the objective of the experimental investigations. This covers different approaches to capture proteins of very low abundance. Total protein harvestings to prevent partial losses are also described such as single exhaustive desorption and fractionated elutions for more detailed analyses. Documented results are also reported demonstrating the capability of the technology well beyond what is the common assumption.

Antibody-based proteomics and biomarker research - current status and limitations

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

Towards an animal model of ovarian cancer: cataloging chicken blood proteins using combinatorial peptide ligand libraries coupled with shotgun proteomic analysis for translational research

Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune- and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here the most comprehensive survey of the chicken blood proteome to date.

Metabolomic profiling of ovarian carcinomas using mass spectrometry

Most of the research on tumor cell metabolism has focused on glucose utilization. However, when glucose is limited, solid tumors are forced to catabolize alternative substrates such as fatty acids and amino acids as an energy source. Measuring these alternations in tumor cell metabolism enables us to track neoplastic changes in the tissue to lead towards a more reliable diagnostic outcome. Although a very small number of elements are used in biochemistry, the metabolome is structurally diverse for the production of simple compounds such as phosphate and amino acids as well as more structurally complex compounds such as nucleotides, oligosaccharides, and complex lipids. Characterization of the metabolome, therefore, requires analytical methods that can handle a wide range of molecular structures and physicochemical properties, including solubility, polarity, and molecular weight. A further factor for consideration in the selection of technology for metabolomics is the wide range of concentrations of biochemical typically present in biological systems. MS has established itself as the high-throughput, information-rich, industrially stable approach to assess both the composition of diverse sample types as well as changes to that composition following perturbation.

Differential Effects of Insulin-Like Growth Factor Binding Protein-6 (IGFBP-6) on Migration of Two Ovarian Cancer Cell Lines

INTRODUCTION

IGFBP-6 inhibits angiogenesis as well as proliferation and survival of rhabdomyosarcoma cells. However, it promotes migration of these cells in an IGF-independent manner. The IGF system is implicated in ovarian cancer, so we studied the effects of IGFBP-6 in ovarian cancer cells.

METHODS

The effects of wild type (wt) and a non-IGF-binding mutant (m) of IGFBP-6 on migration of HEY and SKOV3 ovarian cancer cells, which, respectively, represent aggressive and transitional cancers, were studied. ERK and JNK phosphorylation were measured by Western blotting.

RESULTS

IGF-II, wt-, and mIGFBP-6 each promoted SKOV3 cell migration by 77-98% (p < 0.01). In contrast, IGF-II also increased HEY cell migration to 155 ± 13% of control (p < 0.001), but wt-IGFBP-6 and mIGFBP-6 decreased migration to 62 ± 5 and 66 ± 3%, respectively (p < 0.001). In these cells, coincubation of IGF-II with wt but not mIGFBP-6 increased migration. MAP kinase pathways are involved in IGFBP-6-induced rhabdomyosarcoma cell migration, so activation of these pathways was studied in HEY and SKOV3 cells. Wt and mIGFBP-6 increased ERK phosphorylation by 62-99% in both cell lines (p < 0.05). Wt-IGFBP-6 also increased JNK phosphorylation by 139-153% in both cell lines (p < 0.05), but the effect of mIGFBP-6 was less clear. ERK and JNK inhibitors partially inhibited the migratory effects of wt and mIGFBP-6 in SKOV3 cells, whereas the ERK inhibitor partially restored wt and mIGFBP-6-induced inhibition of HEY cell migration. The JNK inhibitor had a lesser effect on the actions of wtIGFBP-6 and no effect on the actions of mIGFBP-6 in HEY cells.

CONCLUSION

IGFBP-6 has opposing effects on migration of HEY and SKOV3 ovarian cancer cells, but activates MAP kinase pathways in both. Delineating the pathways underlying the differential effects on migration will increase our understanding of ovarian cancer metastasis and shed new light on the IGF-independent effects of IGFBP-6.

Proteomics applied to transfusion plasma: the beginning of the story

'Safe blood' is and has always been the major concern in transfusion medicine. Plasma can undergo virus inactivation treatments based on physicochemical, photochemical or thermal methodologies for pathogen inactivation. The validation of these treatments is essentially based on clottability assays and clotting factors' titration; however, their impact on plasma proteins at the molecular level has not yet been evaluated. Proteomics appears as particularly adapted to identify, to localize and, consequently, to correlate these modifications to the biological activity change. At the crossroads of biology and analytical sciences, proteomics is the large-scale study of proteins in tissues, physiological fluids or cells at a given moment and in a precise environment. The proteomic strategy is based on a set of methodologies involving separative techniques like mono- and bidimensional gel electrophoresis and chromatography, analytical techniques, especially mass spectrometry, and bioinformatics. Even if plasma has been extensively studied since the very beginning of proteomics, its application to transfusion medicine has just begun. In the first part of this review, we present the principles of proteomics analysis. Then, we propose a state of the art of proteomics applied to plasma analysis. Finally, the use of proteomics for the evaluation of the impact of storage conditions and pathogen inactivation treatments applied to transfusion plasma and for the evaluation of therapeutic protein fractionated is discussed.

Insulin-like growth factor-binding protein-6 and cancer

The IGF (insulin-like growth factor) system is essential for physiological growth and it is also implicated in a number of diseases including cancer. IGF activity is modulated by a family of high-affinity IGF-binding proteins, and IGFBP-6 is distinctive because of its marked binding preference for IGF-II over IGF-I. A principal role for IGFBP-6 is inhibition of IGF-II actions, but recent studies have indicated that IGFBP-6 also has IGF-independent effects, including inhibition of angiogenesis and promotion of cancer cell migration. The present review briefly summarizes the IGF system in physiology and disease before focusing on recent studies on the regulation and actions of IGFBP-6, and its potential roles in cancer cells. Given the widespread interest in IGF inhibition in cancer therapeutics, increasing our understanding of the mechanisms underlying the actions of the IGF ligands, receptors and binding proteins, including IGFBP-6, will enhance our ability to develop optimal treatments that can be targeted to the most appropriate patients.

Cancer proteomics

Cancer presents high mortality and morbidity globally, largely due to its complex and heterogenous nature, and lack of biomarkers for early diagnosis. A proteomics study of cancer aims to identify and characterize functional proteins that drive the transformation of malignancy, and to discover biomarkers to detect early-stage cancer, predict prognosis, determine therapy efficacy, identify novel drug targets, and ultimately develop personalized medicine. The various sources of human samples such as cell lines, tissues, and plasma/serum are probed by a plethora of proteomics tools to discover novel biomarkers and elucidate mechanisms of tumorigenesis. Innovative proteomics technologies and strategies have been designed for protein identification, quantitation, fractionation, and enrichment to delve deeper into the oncoproteome. In addition, there is the need for high-throughput methods for biomarker validation, and integration of the various platforms of oncoproteome data to fully comprehend cancer biology.

Smoking and lung cancer-induced changes in N-glycosylation of blood serum proteins

Glycosylation is a key post-translational protein modification which appears important in malignant transformation and tumor metastasis. Abnormal glycosylation of different proteins can often be measured in the blood serum. In this study, we extend our serum-based structural investigations to samples provided by patients diagnosed with lung cancer, paying particular attention to the effects of smoking on the serum glycomic traces. Following a battery of glycomic tests, we find that several fucosylated tetra-antennary structures with varying degrees of sialylation are increased in their abundances in control samples provided by the former smokers, with further elevations in the lung cancer patients who were former smokers. Further detailed investigations demonstrated that the level of outer-arm fucosylation was elevated in the control samples of the former smokers and again in the lung cancer samples provided by the former smokers. This trend was particularly noticeable for the tri- and tetra-antennary structures. Different ratios of sialylation linkages were also observed that could be correlated with the different states of health and smoking status. Decreases in the abundance levels of isomers with two and three α2,3-linked sialic acids and an increased abundance of an isomer with two α2,6-linked sialic acids were noted for a fucosylated tri-sialylated tri-antennary glycan. These results demonstrate the long-term effects of smoking on glycomic profiles and that this factor needs to be considered in these and other serum-based analyses.

Protein biomarkers of ovarian cancer: the forest and the trees

The goal of effective population-based screening for ovarian cancer remains elusive despite intense efforts aimed at improving upon biomarker and imaging modalities. While dozens of potential serum biomarkers for ovarian cancer have been identified in recent years, none have yet overcome the limitations that have hindered the clinical use of CA-125. Avenues of opportunity in biomarker development are emerging as investigators are beginning to appreciate the significance of remote, as well as local or regional, sources of biomarkers in the construction of diagnostic panels, as well as the importance of evaluating biomarkers in prediagnostic settings. As the list of candidate biomarkers of ovarian cancer continues to grow, refinements in the methods through which specific proteins are selected for further development as components of diagnostic panels are desperately sought. Such refinements must take into account both the bioinformatic and biological significance of each candidate. Approaches incorporating these considerations may potentially overcome the challenges to early detection posed by the histological heterogeneity of ovarian cancer. Here, we review the recent progress achieved in efforts to develop diagnostic biomarker panels for ovarian cancer and discuss the challenges that remain.

Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

Liquid-phase-based separation systems for depletion, prefractionation and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis--an update covering the period 2008-2011

This review article expands on the previous one (Jmeian, Y. and El Rassi, Z. Electrophoresis 2009, 30, 249-261) by reviewing pertinent literature in the period extending from early 2008 to the present. Similar to the previous review article, the present one is concerned with proteomic sample preparation (e.g. depletion of high-abundance proteins, reduction of the protein dynamic concentration range, enrichment of a particular subproteome), and the subsequent chromatographic and/or electrophoretic prefractionation prior to peptide separation and identification by LC-MS/MS. This review article differs from the first version published in Electrophoresis 2009, 30, 249-261 by expanding on capturing/enriching subglycoproteomics by lectin affinity chromatography. Ninety-eight articles published in the period extending from early 2008 to the present have been reviewed. By no means is this review article exhaustive: its aim is to give a concise report on the latest developments in the field.

"The quest for biomarkers": are we on the right technical track?

The discovery phase of biomarkers of diagnostic or therapeutic interest started a decade ago with the very rapid development of proteomic investigations. In spite of the development of innovative technologies and multiple approaches, the "harvest" is still modest. Various reasons justified the encountered difficulties and most of them have been circumvented by specific sample treatments or dedicated analytical approaches. Nevertheless, the situation of very modest biomarker discovery level did not change much. This review intends to specifically analyze the main approaches used for biomarker discovery phase and evaluate related advantages and disadvantages. Thus, preliminary sample treatments such as fractionation, depletion and reduction of dynamic concentration range will critically be discussed and then the main differential expression investigation methods analyzed. Combinations of technologies are also discussed along with possible proposals to federate associations of complementary technologies for better chances of success.

Lung cancer signatures in plasma based on proteome profiling of mouse tumor models

We investigated the potential of in-depth quantitative proteomics to reveal plasma protein signatures that reflect lung tumor biology. We compared plasma protein profiles of four mouse models of lung cancer with profiles of models of pancreatic, ovarian, colon, prostate, and breast cancer and two models of inflammation. A protein signature for Titf1/Nkx2-1, a known lineage-survival oncogene in lung cancer, was found in plasmas of mouse models of lung adenocarcinoma. An EGFR signature was found in plasma of an EGFR mutant model, and a distinct plasma signature related to neuroendocrine development was uncovered in the small-cell lung cancer model. We demonstrate relevance to human lung cancer of the protein signatures identified on the basis of mouse models.

Identification of metabolites in the normal ovary and their transformation in primary and metastatic ovarian cancer

In this study, we characterized the metabolome of the human ovary and identified metabolic alternations that coincide with primary epithelial ovarian cancer (EOC) and metastatic tumors resulting from primary ovarian cancer (MOC) using three analytical platforms: gas chromatography mass spectrometry (GC/MS) and liquid chromatography tandem mass spectrometry (LC/MS/MS) using buffer systems and instrument settings to catalog positive or negative ions. The human ovarian metabolome was found to contain 364 biochemicals and upon transformation of the ovary caused changes in energy utilization, altering metabolites associated with glycolysis and β-oxidation of fatty acids--such as carnitine (1.79 fold in EOC, p<0.001; 1.88 fold in MOC, p<0.001), acetylcarnitine (1.75 fold in EOC, p<0.001; 2.39 fold in MOC, p<0.001), and butyrylcarnitine (3.62 fold, p<0.0094 in EOC; 7.88 fold, p<0.001 in MOC). There were also significant changes in phenylalanine catabolism marked by increases in phenylpyruvate (4.21 fold; p = 0.0098) and phenyllactate (195.45 fold; p<0.0023) in EOC. Ovarian cancer also displayed an enhanced oxidative stress response as indicated by increases in 2-aminobutyrate in EOC (1.46 fold, p = 0.0316) and in MOC (2.25 fold, p<0.001) and several isoforms of tocopherols. We have also identified novel metabolites in the ovary, specifically N-acetylasparate and N-acetyl-aspartyl-glutamate, whose role in ovarian physiology has yet to be determined. These data enhance our understanding of the diverse biochemistry of the human ovary and demonstrate metabolic alterations upon transformation. Furthermore, metabolites with significant changes between groups provide insight into biochemical consequences of transformation and are candidate biomarkers of ovarian oncogenesis. Validation studies are warranted to determine whether these compounds have clinical utility in the diagnosis or clinical management of ovarian cancer patients.

The proteome buccaneers: how to unearth your treasure chest via combinatorial peptide ligand libraries

The latest advances in combinatorial peptide ligand libraries, with their unique performance in discovering low-abundance species in proteomes, are reviewed here. Explanations of mechanism, potential applications, capture of proteomes at different pH values to enhance the total catch and quantitative elutions, such as boiling in the presence of 5% sodium dodecyl sulfate and 3% dithiothreitol are included. The reproducibility of protein capture among different experiments with the same batch of beads or with different batches is also reported to be very high, with coefficient of variations in the order of 10-20%. Miniaturized operations, consisting of capture with as little as 20 or even 5 microl of peptide beads are reported, thus demonstrating that the described technology could be exploited for routine biomarker discovery in a biomedical environment. Finally, it is shown that the signal of captured proteins is linear over approximately three orders of magnitude, ranging from nM to microM, thus ensuring that differential quantitative proteomics for biomarker discovery can be fully implemented, providing species do not saturate their ligands.

Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients

BACKGROUND

New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry.

METHODS

LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry.

RESULTS

Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001). LRG1 mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry.

CONCLUSIONS

Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.

Quantitative proteomic analysis by iTRAQ(R) for the identification of candidate biomarkers in ovarian cancer serum

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ(R).

RESULTS

Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ(R) to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified.

CONCLUSIONS

This study provides the first analysis of immunodepleted serum in combination with iTRAQ(R) to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins

In clinical and pharmaceutical proteomics, serum and plasma are frequently used for detection of early diagnostic biomarkers for therapeutic targets. Although obtaining these body fluid samples is non-invasive and easy, they contain some abundant proteins that mask other protein components present at low concentrations. The challenge in identifying serum biomarkers is to remove the abundant proteins, uncovering and enriching at the same time the low-abundance ones. The depletion strategies, however, could lead to the concomitant removal of some non-targeted proteins that may be of potential interest. In this study, we compared three different methods aimed to deplete high-abundance proteins from human serum, focusing on the identification of non-specifically bound proteins which might be eventually removed. A Cibacron blue-dye-based method for albumin removal, an albumin and IgG immunodepletion method and an immunoaffinity column (Multiple Affinity Removal System) that simultaneously removes a total of six high-abundance proteins, were investigated. The bound proteins were eluted, separated by two-dimensional gel electrophoresis and identified by Nano LC-CHIP-MS system. Flow-through fractions and bound fractions were also analysed with the ProteinChip technology SELDI-TOF-MS. Our results showed that the methods tested removed not only the targeted proteins with high efficiency, but also some non-targeted proteins. We found that the Multiple Affinity Removal Column improved the intensity of low-abundance proteins, displayed new protein spots and increased resolution. Notably, the column showed the lowest removal of untargeted proteins, proved to be the most promising depletion approach and a reliable method for serum preparation prior to proteomic studies.

Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker

Background

Breast cancer is one of the leading causes of women's death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood.

Methods

Plasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays.

Results

A total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, α1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels.

Conclusions

Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer.