The overexpression of a single oncogene (ERBB2/HER2) alters the proteomic landscape of extracellular vesicles

ERBB2/HER2 amplification activates signaling cascades that lead to a tumor cell phenotype. However, despite its remarkable importance in oncology, the consequences of HER2 amplification over the extracellular vesicles (EVs) content have not yet been investigated. Here, we isolated EVs secreted by HB4a, a mammary luminal epithelial cell line and C5.2, its HER2‐overexpressing clone. We isolated two EV sets (20 and 100 K) by ultracentrifugation and used electron microscopy and nanoparticle tracking analysis for their morphological characterization. We employed GeLC‐MS/MS combined with isotope‐coded protein labeling to evaluate cell‐derived proteins and LC‐MS/MS label free spectral counting to quantify the EVs proteome. We found higher HER2 levels in both C5.2‐derived EVs when compared with C5.2 cells, suggesting its preferential shuttling. Proteins capable of inducing malignant transformation are enriched in both C5.2 EV subsets, including two HER2‐related proteins involved in cell motility and invasion, cofilin and CD44. MetaCore? analysis indicated an enrichment of cell adhesion and cytoskeleton‐remodeling pathways in C5.2 EVs, as well as proteins related to HER2 signaling, such as sphingosine‐1‐phosphate pathway. Together, our data indicate that in terms of protein content, distinct vesicle sets reinforce and complement each other. Our results also suggest that HER2‐upregulated proteins from EVs may be relevant for cellular malignancy and can be potential biomarkers for HER2⁺ cancer patients.     

Differential expression of complement proteins in cerebrospinal fluid from active multiple sclerosis patients

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system with complex immunopathogenesis. Using the 2‐D DIGE technology, we separate CSF proteins from patients with active MS and control subjects. Three of the seven differential proteins identified were related with complement system, and the network analysis of the differential proteins revealed complement activation involvement in active MS. Complement C4b (gamma chain) was confirmed elevated by performing western blotting analysis (P < 0.01). The present results are an independent quantitative proteomic measure in CSF from active MS patients. The differential expression of the complement C4b and related proteins in CSF provides potential biomarkers as well as evidence for the involvement of complement activation in the pathogenesis of MS disease. J. Cell. Biochem. 112: 1930–1937, 2011. © 2011 Wiley‐Liss, Inc.     

Optimizing Size Exclusion Chromatography for Extracellular Vesicle Enrichment and Proteomic Analysis from Clinically Relevant Samples

The field of extracellular vesicle (EV) research has rapidly expanded in recent years, with particular interest in their potential as circulating biomarkers. Proteomic analysis of EVs from clinical samples is complicated by the low abundance of EV proteins relative to highly abundant circulating proteins such as albumin and apolipoproteins. To overcome this, size exclusion chromatography (SEC) has been proposed as a method to enrich EVs whilst depleting protein contaminants; however, the optimal SEC parameters for EV proteomics have not been thoroughly investigated. Here, quantitative evaluation and optimization of SEC are reported for separating EVs from contaminating proteins. Using a synthetic model system followed by cell line‐derived EVs, it is found that a 10 mL Sepharose 4B column in PBS produces optimal resolution of EVs from background protein. By spiking‐in cancer cell‐derived EVs to healthy plasma, it is shown that some cancer EV‐associated proteins are detectable by nano‐LC‐MS/MS when as little as 1% of the total plasma EV number are derived from a cancer cell line. These results suggest that an optimized SEC and nanoLC‐MS/MS workflow may be sufficiently sensitive for disease EV protein biomarker discovery from patient‐derived clinical samples.     

Unique Protein Profiles of Extracellular Vesicles as Diagnostic Biomarkers for Early and Advanced Non‐Small Cell Lung Cancer

Extracellular vesicles (EVs) mediate intercellular communication via transferring proteins and other biological molecules and have been recently investigated as biomarkers of disease. Sensitive and specific biomarkers are required for lung cancer diagnosis and prognosis. The present study screens for abnormal EV proteins in non‐small cell lung cancer (NSCLC) using a quantitative proteomics strategy involving LC‐MS/MS to identify ideal biomarkers for NSCLC diagnosis. EVs are enriched from the sera of early and advanced NSCLC patients and healthy controls and from cell culture supernatants of lung adenocarcinoma and bronchial epithelial cell lines. In the sera and supernatants, 279 and 632 differentially expressed proteins, respectively, are associated with signaling pathways including extracellular membrane–receptor interaction, focal adhesion, and regulation of the actin cytoskeleton. Thirty‐two EV proteins are identified at the intersection of differentially expressed proteins between the NSCLC groups and cell lines. Based on bioinformatics analysis, in silico immunohistochemical, and PRM verification, fibronectin is selected for following in vitro studies and validation with an independent cohort. Fibronectin on EVs is estimated to perform well in the diagnosis of NSCLC patients based on AUC, showing great potential for clinical use and demonstrating the efficacy of this method for EV‐associated biomarker screening.     

LC‐MS/MS‐based serum proteomics for identification of candidate biomarkers for hepatocellular carcinoma

Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label‐free proteomic analysis by LC‐MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC‐associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 ( http://proteomecentral.proteomexchange.org/dataset/PXD001171 ).     

Application of Extracellular Vesicles Proteomics to Cardiovascular Disease: Guidelines,Data Analysis,and Future Perspectives

Extracellular vesicles (EVs) are a heterogeneous population of vesicles composed of a lipid bilayer that carry a large repertoire of molecules including proteins, lipids, and nucleic acids. In this review, some guidelines for plasma‐derived EVs isolation, characterization, and proteomic analysis, and the application of the above to cardiovascular disease (CVD) studies are provided. For EVs analysis, blood samples should be collected using a 21‐gauge needle, preferably in citrate tubes, and plasma stored for up to 1 year at ?80°, using a single freeze–thaw cycle. For proteomic applications, differential centrifugation (including ultracentrifugation steps) is a good option for EVs isolation. EVs characterization is done by transmission electron microscopy, particle enumeration techniques (nanoparticle‐tracking analysis, dynamic light scattering), and flow cytometry. Regarding the proteomics strategy, a label‐free and gel‐free quantitative method is a good choice due to its accuracy and because it minimizes the amount of sample required for clinical applications. Besides the above, main EVs proteomic findings in cardiovascular‐related diseases are presented and analyzed in this review, paying especial attention to overlapping results between studies. The latter might offer new insights into the clinical relevance and potential of novel EVs biomarkers identified to date in the context of CVD.     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

Database searching based methods for label‐free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross‐assignment among different runs. Here, we present a new label‐free fast quantitative analysis tool, LFQuant, for high‐resolution LC‐MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large‐scale label‐free data with fractionation such as SDS‐PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL‐Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/ .     

Label‐free profiling of skeletal muscle using high‐definition mass spectrometry

We report automated and time‐efficient (2 h per sample) profiling of muscle using ultra‐performance LC coupled directly with high‐definition MS (HDMS^E). Soluble proteins extracted from rat gastrocnemius (n = 10) were digested with trypsin and analyzed in duplicate using a 90 min RPLC gradient. Protein identification and label‐free quantitation were performed from HDMS^E spectra analyzed using Progenesis QI for Proteomics software. In total 1514 proteins were identified. Of these, 811 had at least three unique peptides and were subsequently used to assess the dynamic range and precision of LC‐HDMS^E label‐free profiling. Proteins analyzed by LC‐HDMS^E encompass the entire complement of glycolytic, β‐oxidation, and tricarboxylic acid enzymes. In addition, numerous components of the electron transport chain and protein kinases involved in skeletal muscle regulation were detected. The dynamic range of protein abundances spanned four orders of magnitude. The correlation between technical replicates of the ten biological samples was R² = 0.9961 ± 0.0036 (95% CI = 0.9940 – 0.9992) and the technical CV averaged 7.3 ± 6.7% (95% CI = 6.87 – 7.79%). This represents the most sophisticated label‐free profiling of skeletal muscle to date.     

Higher dimensional (Hi-D) separation strategies dramatically improve the potential for cancer biomarker detection in serum and plasma

The plasma proteome has a wide dynamic range of protein concentrations and is dominated by a few highly abundant proteins. Discovery of novel cancer biomarkers using proteomics is particularly challenging because specific biomarkers are expected to be low abundance proteins with normal blood concentrations of low nanograms per milliliter or less. Conventional, one- and two-dimensional proteomic methods including 2D PAGE, 2D DIGE, LC-MS/MS, and LC/LC-MS/MS do not have the capacity to consistently detect many proteins in this range. In contrast, new higher dimensional (Hi-D) separation strategies, utilizing more than two dimensions of fractionation, can profile the low abundance proteome.     

Tumor‐Derived Extracellular Vesicles as a Novel Source of Protein Biomarkers for Cancer Diagnosis and Monitoring

“Liquid biopsies” have received attention as a complementary tool for traditional tissue biopsies that may enhance the spectrum of analysis for tumor‐derived factors. One such factor gaining prominence in the liquid biopsy field is extracellular vesicles (EVs), membrane‐bound nanovesicles which are secreted by cells into biofluids such as blood, urine, and saliva. EVs are released in both physiological and pathological conditions and can transport a variety of molecules, including proteins, metabolites, RNA, microRNAs, and DNA, to distant sites throughout the body. As such, they are emerging as a promising source of tumor biomarkers for the noninvasive diagnosis, prognosis, and monitoring of cancer patients. In particular, the wealth of tumor‐related information that can be gleaned from the EV proteomic cargo has become apparent through mass spectrometric analysis, which has provided new benchmarks for clinically focused biomarker research. In this review, the current achievements in the use of MS for identifying potential EV‐derived protein biomarkers of cancer are explored, and the techniques and challenges involved in this pursuit are summarized.     

Characterization of multiple myeloma vesicles by label‐free relative quantitation

Multiple myeloma (MM) is a hematological malignancy caused by a microenviromentally aided persistence of plasma cells in the bone marrow. The role that extracellular vesicles (EVs), microvesicles and exosomes, released by MM cells have in cell‐to‐cell communication and signaling in the bone marrow is currently unknown. This paper describes the proteomic content of EVs derived from MM.1S and U266 MM cell lines. First, we compared the protein identifications between the vesicles and cellular lysates of each cell line finding a large overlap in protein identifications. Next, we applied label‐free spectral count quantitation to determine proteins with differential abundance between the groups. Finally, we used bioinformatics to categorize proteins with significantly different abundances into functional groups. The results illustrate the first use of label‐free spectral counting applied to determine relative protein abundances in EVs.     

Tissue Proteome Signatures Associated with Five Grades of Prostate Cancer and Benign Prostatic Hyperplasia

The histology‐based Gleason score (GS) of prostate cancer (PCa) tissue biopsy is the most accurate predictor of disease aggressiveness and an important measure to guide treatment strategies and patient management. The variability associated with PCa tumor sampling and the subjective determination of the GS are challenges that limit accurate diagnostication and prognostication. Thus, novel molecular signatures are needed to distinguish between indolent and aggressive forms of PCa for better patient management and outcomes. Herein, label‐free LC‐MS/MS proteomics is used to profile the proteome of 50 PCa tissues spanning five grade groups (n = 10 per group) relative to tissues from individuals with benign prostatic hyperplasia (BPH). Over 2000 proteins are identified albeit at different levels between and within the patient groups, revealing biological processes associated with specific grades. A panel of 11 prostate‐derived proteins including IGKV3D‐20, RNASET2, TACC2, ANXA7, LMOD1, PRCP, GYG1, NDUFV1, H1FX, APOBEC3C, and CTSZ display the potential to stratify patients from low and high PCa grade groups. Parallel reaction monitoring of the same sample cohort validate the differential expression of LMOD1, GYG1, IGKV3D‐20, and RNASET2. The four proteins associated with low and high PCa grades reported here warrant further exploration as candidate biomarkers for PCa aggressiveness.     

Stopping the clock on proteomic degradation by heat treatment at the point of tissue excision

The effectiveness of rapid and controlled heating of intact tissue to inactivate native enzymatic activity and prevent proteome degradation has been evaluated. Mouse brains were bisected immediately following excision, with one hemisphere being heat treated followed by snap freezing in liquid nitrogen while the other hemisphere was snap frozen immediately. Sections were cut by cryostatic microtome and analyzed by MALDI‐MS imaging and minimal label 2‐D DIGE, to monitor time‐dependent relative changes in intensities of protein and peptide signals. Analysis by MALDI‐MS imaging demonstrated that the relative intensities of markers varied across a time course (0–5 min) when the tissues were not stabilized by heat treatment. However, the same markers were seen to be stabilized when the tissues were heat treated before snap freezing. Intensity profiles for proteins indicative of both degradation and stabilization were generated when samples of treated and nontreated tissues were analyzed by 2‐D DIGE, with protein extracted before and after a 10‐min warming of samples. Thus, heat treatment of tissues at the time of excision is shown to prevent subsequent uncontrolled degradation of tissues at the proteomic level before any quantitative analysis, and to be compatible with downstream proteomic analysis.     

Highly sensitive saturation labeling reveals changes in abundance of cell cycle‐associated proteins and redox enzyme variants during oocyte maturation in vitro

Oocyte maturation is a complex process and a critical issue in assisted reproduction techniques (ART) in humans and other mammals. We used a sensitive 2‐D DIGE saturation labeling approach including an internal pooled standard for quantitative proteome profiling of immature versus in vitro matured bovine oocytes in six independent samples. The study comprised 48 2D gel images representing 24 DIGE experiments. From 250 ng sample analyzed per gel, quantitative analysis revealed an average of 2244 spots in pH 4–7 images and 1291 spots in pH 6–9 images. Thirty‐eight spots with different intensities were detected in total. Spots of a preparative gel from 2200 oocytes were identified by nano‐LC‐MS/MS analysis. The ten spots which could be unambiguously identified include the Ca²⁺‐binding protein translationally controlled tumor protein, enzymes of the Krebs and pentose phosphate cycles, clusterin, 14‐3‐3 ?, elongation factor‐1 gamma, and redox enzymes such as polymorphic forms of GST Mu 5 and peroxiredoxin‐3. The cellular distribution of two proteins was determined by confocal laser scanning microscopy. The interesting protein candidates identified by this study may help to improve the in vitro maturation process in order to increase the rate of successful in vitro fertilization and other ART in cattle and other mammals.     

Storage‐induced changes of the cytosolic red blood cell proteome analyzed by 2D DIGE and high‐resolution/high‐accuracy MS

The storage of packed red blood cells (RBCs) is associated with the development of morphological and biochemical changes leading to a reduced posttransfusion functionality and viability of the cells. Within this study, 2D DIGE and high‐resolution/high‐accuracy Orbitrap MS were used to analyze the storage‐induced changes of the cytosolic RBC proteome and identify characteristic protein patterns and potential marker proteins for the assessment of RBC storage lesions. Leukodepleted RBC concentrates were stored according to standard blood bank conditions for 0, 7, 14, 28, and 42 days and analyzed by using a characterized and validated protocol. Following statistical evaluation, a total of 14 protein spots were found to be significantly altered after 42 days of ex vivo storage. Protein identification was accomplished by tryptic digestion and LC‐MS/MS and three proteins potentially useful as biomarkers for RBC aging comprising transglutaminase 2, beta actin, and copper chaperone for superoxide dismutase were selected and validated by western blot analysis. These can serve as a basis for the development of a screening assay to detect RBC storage lesions and autologous blood doping in sports.     

Proteomic Screen of Brain Glycoproteome Reveals Prion Specific Marker of Pathogenesis

Transmissible spongiform encephalopathies (TSEs) are neurodegenerative disorders caused by the presence of an infectious prion protein. The primary site of pathology is the brain characterized by neuroinflammation, astrogliosis, prion fibrils, and vacuolation. The events preceding the observed pathology remain in question. We sought to identify biomarkers in the brain of TSE‐infected and aged‐matched control mice using two‐dimensional fluorescence difference gel electrophoresis (2D‐DIGE). Since the brain proteome is too complex to resolve all proteins using 2D‐DIGE, protein samples are initially filtered through either concanavalin A (ConA) or wheat‐germ agglutinin (WGA) columns. Four differentially abundant proteins are identified through screening of the two different glycoproteomes: Neuronal growth regulator 1 (NEGR1), calponin‐3 (CNN3), peroxiredoxin‐6 (Prdx6), and glial fibrillary acidic protein (GFAP). Confirmatory Western blots are performed with samples from TSE‐infected and comparative Alzheimer's disease (AD) affected brains and their respective controls from time points throughout the disease courses. The abundance of three of the four proteins increases significantly during later stages of prion disease whereas NEGR1 decreases in abundance. Comparatively, no significant changes are observed in later stages of AD. Our lab is the first to associate the glycosylated NEGR1 protein with prion disease pathology.     

Proteomic identification of rainbow trout blood plasma proteins and their relationship to seminal plasma proteins

The characterisation of fish blood proteomes is important for comparative studies of seminal and blood proteins as well as for the analysis of fish immune mechanisms and pathways. In this study, LC‐MS/MS and 2D‐DIGE were applied to compare rainbow trout seminal (SP) and blood plasma (BP) proteomes. The 54 differentially abundant proteins identified in SP are involved in a variety of signalling pathways, including protein ubiquitination, liver X receptor/retinoid X receptor (LXR/RXR) and farnesoid X receptor activation, cell cycle and acute phase signalling. These findings may indicate the prevalence of acute phase signalling pathways in trout SP, and its essential role in protecting spermatozoa and reproductive tissues. Our study provides the first in‐depth analysis of the trout BP proteome, with a total of 119 proteins identified. The major proteins of rainbow trout BP were recognised as acute phase proteins. Analysis of BP proteins indicated that acute phase response signalling, the complement system, liver X receptor/retinoid X receptor and farnesoid X receptor activation and the coagulation system are the top canonical pathways. This study enhances knowledge of the blood origin of trout SP proteins and understanding of fish reproductive biology. Our results provide new insight into blood proteins specifically important for fish physiology and innate immunity. The mass spectrometry data are available via ProteomeXchange with the identifier PXD005988 and https://doi.org/10.6019/PXD005988 .