Plasma exosomal protein PLG and SERPINA1 in colorectal cancer diagnosis and coagulation abnormalities

PURPOSE

Early diagnosis of colorectal cancer (CRC) is critical to patient prognosis; however, there is lack of non-invasive biomarkers that are extremely sensitive and specific for early screening and diagnosis. Exosomes are a novel tool applied to the diagnosis and treatment of cancer. Changes in plasma exosomal proteins have a certain relationship with the development of various diseases including tumors. Here, we aimed to find exosomal biomarkers for early diagnosis of CRC.

METHODS

Exosomes obtained by ultracentrifugation from CRC patients and healthy donors were characterized by transmission electron microscopy (TEM), qNano and western blotting. Proteomic and functional enrichment analyses confirmed differences in the specific expression of exosomal proteins in plasma between CRC patients and healthy donors. Western blotting with enzyme-linked immunosorbent assay (ELISA) was used to verify the difference proteins. Statistical methods were used to analyze the relationship between protein levels and CRC.

RESULTS

The expression levels of serpin peptidase inhibitor clade A member 1 (SERPINA1) and fibrinogen (PLG) in CRC patients were significantly higher than those in healthy groups. Receptor operating characteristic (ROC) curves analysis was superior to CEA and CA19-9 for the diagnosis of colorectal cancer and early-stage colorectal cancer. The two were related to TNM staging and coagulation, and the difference was statistically significant.

CONCLUSION

The results of this study have potential value in advancing the clinical diagnosis of colorectal cancer.

Proteomic identification of tumor- and metastasis-associated galectin-1 in claudin-low breast cancer

BACKGROUND

Metastasis and mortality remain high among breast cancer patients with the claudin-low subtype because these tumors are aggressive, chemoresistant, and lack targeted therapies. Our objective was to utilize discovery-based proteomics to identify proteins associated with claudin-low primary and metastatic tumors to gain insight into pathways and mechanisms of tumor progression.

METHODS

We used nano-LC-MS/MS proteomics to analyze orthotopic and metastatic tumors from the syngeneic murine T11 tumor model, which displays gene expression profiles mirroring human claudin-low tumors. Galectin-1 identity, expression and spatial distribution were investigated by biochemical and immunochemical methods and MALDI/IMS. RNA seq data from mouse and human tumors in our study and publicly available microarray data were analyzed for differential galectin-1 expression across breast cancer subtypes.

RESULTS

Galectin-1, an N-acetyllactosamine-binding protein, exhibited the highest sequence coverage and high abundance rank order among nano-LC-MS/MS-identified proteins shared by T11 claudin-low tumors but not normal tissue. Label-free quantitation, Western immunoblot and ELISA confirmed galectin-1 identity and significant differential expression. MALDI/IMS spatial mapping and immunohistochemistry detected galectin-1 in T11 metastatic lung foci. Immunohistochemistry of human claudin-low tumors demonstrated intermediate-to-high intensity galectin-1 staining of tumor and stroma. Gene expression analysis of mouse and human tumors found the highest galectin-1 levels in the claudin-low breast cancer subtype.

CONCLUSIONS

Proteomics and genomics reveal high expression of galectin-1 protein and RNA in primary and metastatic claudin-low breast cancer.

GENERAL SIGNIFICANCE

This work endorses proteomic approaches in cancer research and supports further investigations of the function and significance of galectin-1 overexpression in claudin-low tumor progression.

Evaluation of a combinational use of serum microRNAs as biomarkers for liver diseases

Circulating microRNAs (miRNA) have been widely recognized as a novel noninvasive biomarker in a variety of physiological and pathological conditions. In order to assess the sensitivity and reliability of potential miRNAs as diagnostic markers for liver disease related to viral infection, alcohol abuse, or chemical exposure, we collected serum samples from 326 participants and evaluated the single and combination diagnostic values of three serum miRNAs (miR-122, miR-125b, miR-192) compared with a conventional marker ALT. We found that serum miR-122 is significantly elevated in patients with active HBV. MiR-125b increased in HCV positive patients, whereas miR-192 and miR-122 were associated with chemical-induced liver injury. None of the aforementioned miRNAs were shown to increase significantly in alcohol-related liver injuries. Furthermore, we analyzed different combinations and found that a set of miR-122 and miR-125b enhanced the sensitivity of detecting liver injury. Among the 58 ALI/ALF patients, miR-122 responded more rapidly than ALT in successful treatments. Patients with spontaneous recovery from ALI/ALF showed significantly higher serum levels of miR-122 and miR-125b compared to non-recovered patients. In conclusion, our results suggest that the combination of miR-122 and miR-125b may serve as efficient biomarkers for liver injury and may be of a prognostic value in predicting ALI/ALF outcome.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Jagged 2 silencing inhibits motility and invasiveness of colorectal cancer cell lines

Although the Notch pathway has been reported to be activated in colorectal cancer (CRC), limited information is available regarding the expression and role of its ligand, Jagged 2 (JAG2), in CRC. Using immunohistochemistry, the present study demonstrated that JAG2 protein expression may be detected in up to 95% of CRC cases and is 3-fold upregulated in tumor cells compared to surrounding normal tissues. This finding suggests that JAG2 may have a role in the tumorigenicity of CRC. To further investigate the cellular functions of JAG2 expression in CRC, two different small interfering RNAs (siRNAs) were used to downregulate JAG2 expression in CRC cell lines (HCT116, DLD-1 and HT-29). The results indicated that JAG2 knockdown inhibits the motility and invasiveness of CRC cell lines without significantly affecting cell proliferation. These findings implicate JAG2 in promoting aggressiveness of CRC, and lay the foundation for its future development as a therapeutic target for the treatment of CRC.

Establishment of a decision tree model for diagnosis of early rheumatoid arthritis by proteomic fingerprinting

AIM

The objective of this study was to identify proteomic biomarkers specific for rheumatoid arthritis (RA) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in combination with weak cationic exchange (WCX) magnetic beads.

METHODS

Serum samples from 50 patients with RA and 110 disease controls (50 SLE and 60 SS) and 51 healthy individuals were analyzed. The samples were randomly divided into a training set or test set to develop a diagnostic model for RA.

RESULTS

A total of 83 protein peaks were identified to be related with RA, in which four of the peaks with mass-charge ratio (m/z) at 8133.85, 5844.60, 13 541.3 and 14 029.0 were selected to establish a model for diagnosis of RA. This classification model could separate patients with RA from diseased and healthy controls with sensitivity of 84.0% and specificity of 92.5%, and its accuracy was confirmed in the blind testing set with high sensitivity and specificity of 80.0% and 93.3%, respectively.

CONCLUSIONS

This study suggested that potential serum biomarkers for RA diagnosis could be discovered by MALDI-TOF-MS. The classification tree model set up in this study might be used as a novel diagnostic tool for RA.

Capturing and identification of differentially expressed fucome by a gel free and label free approach

This research reports a proof-of-concept that describes an instrumental approach that is gel free and label free at both the separation and mass spectrometry ends for the capturing and identification of differentially expressed proteins (DEPs) in diseases, e.g., cancers. The research consists of subjecting/processing equalized and non-equalized (i.e., untreated) disease-free and hepatocellular carcinoma (HCC) human sera via a multicolumn platform for capturing/fractionating human serum fucome. The equalization was performed via the combinatorial peptide ligand library (CPLL) beads technology that ensured narrowing the protein concentration range, thus allowing the detection of low abundance proteins. The equalized and non-equalized disease-free and HCC sera were first fractionated online onto two lectin columns specific to fucose, namely Aleuria aurantia lectin (AAL) and Lotus tetragonolobus agglutinin (LTA) followed by the online fractionation of the lectin captured fucome by reversed phase chromatography. The online desalted fractions were first subjected to trypsinolysis and then to liquid chromatography-mass spectrometry (LC-MS/MS) analysis. In comparison with untreated serum, the CPLL treated serum is superior in terms of the total number of identified DEPs, which reflected an increased number of DEPs in a wide abundance range. The DEPs in HCC serum were found to be 70 and 40 in both LTA and AAL fractions for the serum treated by CPLL and untreated serum, respectively. In addition, the platform combined with the CPLL treatment was accomplished with virtually no sample loss and dilution as well as with no experimental biases and sample labeling when comparing the diseased-free and cancer sera using LC-MS/MS.

Nanoproteomic assays on hematopoietic stem cells

Dysregulation of cytokine signaling pathways is associated with benign and malignant hematologic disorders. Improvements in therapy rely on understanding the biology of the pathways and the proteins involved. Studying these pathways in patient samples is challenging as samples are difficult to obtain, contain fewer cells, and are heterogeneous in nature. To address some of these difficulties, we have utilized the technique of microcapillary electrophoresis. Using the NanoPro 1000 system (ProteinSimple) which is built on an automated, capillary-based immunoassay platform, we have developed rapid and quantitative assays for specific proteins from relatively small sample sizes. The NanoPro provides precise and quantitative data of the phosphorylation states of a specific protein of interest. We describe our experience with NanoPro assay development and optimization with specific application toward understanding aberrant cytokine signaling in human leukemia cells.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

Matrix-assisted laser desorption/ionization mass spectrometry imaging of cardiolipins in rat organ sections

Cardiolipin (CL) is a class of phospholipid tightly associated with the mitochondria functions and a prime target of oxidative stress. Peroxidation of CL dissociates its bound cytochrome C, a phenomenon that reflects oxidative stress sustained by the organ and a trigger for the intrinsic apoptotic pathway. However, CL distribution in normal organ tissues has yet to be documented. Fresh rat organs were snap-frozen, cut into cryosections that were subsequently desalted with ammonium acetate solution, and vacuum-dried. CL distribution in situ was determined using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technique on sections sublimed with 2,5-dihydroxybenzoic acid. CL images in rat cardiac ventricular section showed a homogeneous distribution of a single m/z 1447.9 ion species that was confirmed as the (18:2)4 CL by tandem mass spectrometry. The presence of low abundant (18:2)3(18:1) CL with the bulk (18:2)4 CL in quadriceps femoris rendered the muscle CL exhibiting a slightly deviated isotopic pattern from that of cardiac muscle. In rat liver, MALDI-MSI unveiled three CL-containing mass ranges, each with a unique in situ distribution pattern. Co-registration of the CL ion images with its stained liver section image further revealed the association of CLs in each mass range with the functional zones in the liver parenchyma and suggests the participation of in situ CLs with localized hepatic functions such as oxidation, conjugation, and detoxification. The advances in CL imaging offer an approach with molecular accuracy to reveal potentially dysregulated metabolic machineries in acute and chronic diseased states.

Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

Improved proteomic analysis pipeline for LC-ETD-MS/MS using charge enhancing methods

Electron transfer dissociation (ETD) is a useful and complementary activation method for peptide fragmentation in mass spectrometry. However, ETD spectra typically receive a relatively low score in the identifications of 2+ ions. To overcome this challenge, we, for the first time, systematically interrogated the benefits of combining ion charge enhancing methods (dimethylation, guanidination, m-nitrobenzyl alcohol (m-NBA) or Lys-C digestion) and differential search algorithms (Mascot, Sequest, OMSSA, pFind and X!Tandem). A simple sample (BSA) and a complex sample (AMJ2 cell lysate) were selected in benchmark tests. Clearly distinct outcomes were observed through different experimental protocol. In the analysis of AMJ2 cell lines, X!Tandem and pFind revealed 92.65% of identified spectra; m-NBA adduction led to a 5-10% increase in average charge state and the most significant increase in the number of successful identifications, and Lys-C treatment generated peptides carrying mostly triple charges. Based on the complementary identification results, we suggest that a combination of m-NBA and Lys-C strategies accompanied by X!Tandem and pFind can greatly improve ETD identification.

Chemistry-based functional proteomics for drug target deconvolution

Drug target deconvolution, a process that identifies targets to small molecules in complex biological samples, which underlie the biological responses that are observed when a drug is administered, plays an important role in current drug discovery. Despite the fact that genomics and proteomics have provided a flood of information that contributes to the progress of drug target identification and validation, the current approach to drug target deconvolution still poses dilemmas. Chemistry-based functional proteomics, a multidisciplinary strategy, has become the preferred method of choice to deconvolute drug target pools, based on direct interactions between small molecules and their protein targets. This approach has already identified a broad panel of previously undefined enzymes with potential as drug targets and defined targets that can rationalize side effects and toxicity for new drug candidates and existing therapeutics. Herein, the authors discuss both activity-based protein profiling and compound-centric chemical proteomics approaches used in chemistry-based functional proteomics and their applications for the identification and characterization of small molecular targets.

Elucidation of N-glycosites within human plasma glycoproteins for cancer biomarker discovery

Glycans are an important class of post-translational modifications that decorate a wide array of protein substrates. These cell-type specific molecules, which are modulated during developmental and disease processes, are attractive biomarker candidates as biology regarding altered glycosylation can be used to guide the experimental design. The mass spectrometry (MS)-based workflow described here incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan motifs. The goal was to design a relatively simple method for the rapid analysis of small plasma volumes (e.g., clinical specimens). As increases in sialylation and fucosylation are prominent among cancer-associated modifications, we focused on Sambucus nigra agglutinin and AAL, which bind sialic acid- and fucose-containing structures, respectively. Positive controls (fucosylated and sialylated human lactoferrin glycopeptides), and negative controls (high-mannose glycopeptides from Saccharomyces cerevisiae invertase) were used to monitor the specificity of lectin capture and optimize the workflow. Multiple Affinity Removal System 14-depleted, trypsin-digested human plasma from healthy donors served as the target analyte. Samples were loaded onto the lectin columns and separated by high performance liquid chromatography (HPLC) into flow through and bound fractions, which were treated with PNGase F, an amidase that removes N-linked glycans and marks the underlying asparagine glycosite by a +1 Da mass shift. The deglycosylated peptide fractions were interrogated by HPLC ESI-MS/MS on a quadrupole time-of-flight mass spectrometer. The method allowed identification of 122 human plasma glycoproteins containing 247 unique glycosites. Notably, glycoproteins that circulate at ng/mL levels (e.g., cadherin-5 at 0.3-4.9 ng/mL, and neutrophil gelatinase-associated lipocalin which is present at ∼2.5 ng/mL) were routinely observed, suggesting that this method enables the detection of low-abundance cancer-specific glycoproteins.

The role of cytochrome c oxidase subunit Va in non-small cell lung carcinoma cells: association with migration, invasion and prediction of distant metastasis

Background

Lung cancer is one of the most lethal malignancies worldwide, but useful biomarkers of lung cancer are still insufficient. The aim of this study is to identify some membrane-bound protein(s) associated with migration and invasion in human non-small cell lung cancer (NSCLC) cells.

Methods

We classified four NSCLC cell lines into high and low migration/invasion groups by Transwell and Matrigel assays. Using two-dimensional gel electrophoresis and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), we identified 10 membrane-associated proteins being significantly overexpressed in the high migration/invasion group. The expression of the target protein in the four NSCLC cell lines was then confirmed by reverse transcription polymerase chain reaction (RT-PCR), western blot and immunostaining. RNA interference technique was applied to observe the influence of the target protein on migration and invasion. Gelatin zymography was also performed to evaluate the activities of matrix metalloproteinase (MMP)-2 and MMP-9. Expression condition of the target protein on surgical specimens was further examined by immunohistochemical staining and the clinicopathologic data were analyzed.

Results

We identified a mitochondria-bound protein cytochrome c oxidase subunit Va (COX Va) because of its abundant presence found exclusively in tumorous areas. We also demonstrated that migration and invasion of NSCLC cells decreased substantially after knocking down COX Va by siRNA. Meanwhile, we found a positive correlation between COX Va expression, Bcl-2 expression and activities of MMP-2 and MMP-9 in NSCLC cells. Immunohistochemical staining of surgically resected lung adenocarcinomas in 250 consecutive patients revealed that strong COX Va expression was found in 54.8% (137/250) of patients and correlated positively with the status of lymph node metastasis (P = 0.032). Furthermore, strong COX Va expression was associated with the presence of distant metastasis (P = 0.033).

Conclusions

Our current study showed that COX Va may play a role in migration and invasion of NSCLC cells and can be used as a biomarker to predict aggressiveness of NSCLC.

Biomarker discovery by novel sensors based on nanoproteomics approaches

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.

Advances in biomarker research for pancreatic cancer

Pancreatic cancer (PC) is a leading cause of cancer related deaths in United States. The lack of early symptoms results in latestage detection and a high mortality rate. Currently, the only potentially curative approach for PC is surgical resection, which is often unsuccessful because the invasive and metastatic nature of the tumor masses makes their complete removal difficult. Consequently, patients suffer relapses from remaining cancer stem cells or drug resistance that eventually lead to death. To improve the survival rate, the early detection of PC is critical. Current biomarker research in PC indicates that a serum carbohydrate antigen, CA 19-9, is the only available biomarker with approximately 90% specificity to PC. However, the efficacy of CA 19-9 for assessing prognosis and monitoring patients with PC remains contentious. Thus, advances in technology and the detection of new biomarkers with high specificity to PC are needed to reduce the mortality rate of pancreatic cancer.

Application of proteomics to the study of polycystic ovary syndrome

BACKGROUND

Clinical proteomics consists of qualitative and quantitative profiling of proteins present in clinical specimens such as body fluids or tissues, with the aim of discovering novel proteins and cellular pathways associated with the disease of interest.

AIM

To review the proteomic studies conducted to date that addressed different aspects of the pathogenesis of polycystic ovary syndrome (PCOS).

METHODS

Descriptive review of studies that applied proteomic techniques to the study of PCOS. Published articles were identified using the Entrez-PubMed online search facilities.

RESULTS

Most studies conducted to date focused on protein variations in plasma and different target tissues. Plasma proteomics analysis revealed that PCOS associates changes in protein expression in several acute-phase response proteins. Moreover, some of these molecules play major roles in iron metabolism and low-grade chronic inflammation. Studies using omental adipose tissue from morbidly obese women with or without PCOS revealed differences in abundance of proteins that may be involved in lipid and glucose metabolism, oxidative stress processes, and adipocyte differentiation. Moreover, identification of differentially expressed proteins in ovarian tissue, granulosa cells or T lymphocites may help to characterize more clearly some aspects of this disorder.

CONCLUSIONS

Although the application of proteomic techniques to the study of PCOS is in its early infancy, studies conducted to date highlight its heterogeneous nature. Aside from androgen excess, several pathways related to intermediate metabolism, oxidative stress processes, inflammation and iron metabolism appear to be involved in the pathophysiology of PCOS.

The application of a three-step proteome analysis for identification of new biomarkers of pancreatic cancer

We searched for novel tumor markers of pancreatic cancer by three-step serum proteome analysis. Twelve serum abundant proteins were depleted using immunoaffinity columns followed by fractionation by reverse-phase high-performance liquid chromatography. Proteins in each fraction were separated by two-dimensional gel electrophoresis. Then the gel was stained by Coomassie Brilliant Blue. Protein spots in which the expression levels were significantly different between cancer and normal control were identified by LC-MS/MS. One hundred and two spots were upregulated, and 84 spots were downregulated in serum samples obtained from patients with pancreatic cancers, and 58 proteins were identified by mass spectrometry. These candidate proteins were validated using western blot analysis and enzyme-linked immunosorbent assay (ELISA). As a result of these validation process, we could confirm that the serum levels of apolipoprotein A-IV, vitamin D-binding protein, plasma retinol-binding protein 4, and tetranectin were significantly decreased in patients with pancreatic cancer.

Discovery of serum protein biomarkers in rheumatoid arthritis using MALDI-TOF-MS combined with magnetic beads

The aim of this study was to discover potential biomarkers for rheumatoid arthritis (RA) using Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with magnetic beads. Proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS was used to profile and compare the proteomes in serum samples from 60 patients with RA, 35 patients with osteoarthritis and 36 healthy controls. The proteomic pattern associated with RA was identified by Biomarker Patterns Software. Model of biomarkers was constructed and evaluated through the Biomarker Patterns Software. A total of 33 discriminative peaks were identified to be related with RA, in which the 5 peaks with the mass-charge ratio (m/z) peaks at 15,715.5, 7,771.4, 8,959.4, 8,469.8 and 8,710.8 Da were used to construct a model for the diagnosis of RA by pattern recognition software. The blind testing data indicated a sensitivity of 86.7% and a specificity of 90.0% in RA diagnosis. These results demonstrated that potential protein biomarkers for RA could be discovered in serum by MALDI-TOF-MS combined with WCX magnetic beads. The diagnosis mode tree based on the five candidate biomarkers could provide a powerful and reliable diagnostic method for RA with high sensitivity and specificity.

Relative quantification: characterization of bias, variability and fold changes in mass spectrometry data from iTRAQ-labeled peptides

Shotgun proteomics via mass spectrometry (MS) is a powerful technology for biomarker discovery that has the potential to lead to noninvasive disease screening mechanisms. Successful application of MS-based proteomics technologies for biomarker discovery requires accurate expectations of bias, reproducibility, variance, and the true detectable differences in platforms chosen for analyses. Characterization of the variability inherent in MS assays is vital and should affect interpretation of measurements of observed differences in biological samples. Here we describe observed biases, variance structure, and the ability to detect known differences in spike-in data sets for which true relative abundance among defined samples were known and were subsequently measured with the iTRAQ technology on two MS platforms. Global biases were observed within these data sets. Measured variability was a function of mean abundance. Fold changes were biased toward the null and variance of a fold change was a function of protein mass and abundance. The information presented herein will be valuable for experimental design and analysis of the resulting data.

Nutriproteomics: technologies and applications for identification and quantification of biomarkers and ingredients

Nutrition refers to the process by which a living organism ingests and digests food and uses the nutrients therein for growth, tissue maintenance and all other functions essential to life. Food components interact with our body at molecular, cellular, organ and system level. Nutrients come in complex mixtures, in which the presence and concentration of single compounds as well as their interactions with other compounds and the food matrix influence their bioavailability and bioefficacy. Traditionally, nutrition research mainly concentrated on supplying nutrients of quality to nourish populations and on preventing specific nutrient deficiencies. More recently, it investigates health-related aspects of individual ingredients or of complete diets, in view of health promotion, performance optimisation, disease prevention and risk assessment. This review focuses on proteins and peptides, their role as nutrients and biomarkers and on the technologies developed for their analysis. In the first part of this review, we provide insights into the way proteins are currently characterised and analysed using classical and emerging proteomic approaches. The scope of the second part is to review major applications of proteomics to nutrition, from characterisation of food proteins and peptides, via investigation of health-related food benefits to understanding disease-related mechanisms.

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.

Proteomics for development of vaccine

The success of genome projects has provided us with a vast amount of information on genes of many pathogenic species and has raised hopes for rapid progress in combating infectious diseases, both by construction of new effective vaccines and by creating a new generation of therapeutic drugs. Proteomics, a strategy complementary to the genomic-based approach, when combined with immunomics (looking for immunogenic proteins) and vaccinomics (characterization of host response to immunization), delivers valuable information on pathogen-host cell interaction. It also speeds the identification and detailed characterization of new antigens, which are potential candidates for vaccine development. This review begins with an overview of the global status of vaccinology based on WHO data. The main part of this review describes the impact of proteomic strategies on advancements in constructing effective antibacterial, antiviral and anticancer vaccines. Diverse aspects of disease mechanisms and disease preventions have been investigated by proteomics.

The evolving field of imaging mass spectrometry and its impact on future biological research

Within the past decade, imaging mass spectrometry (IMS) has been increasingly recognized as an indispensable technique for studying biological systems. Its rapid evolution has resulted in an impressive array of instrument variations and sample applications, yet the tools and data are largely confined to specialists. It is therefore important that at this junction the IMS community begin to establish IMS as a permanent fixture in life science research thereby making the technology and/or the data approachable by non-mass spectrometrists, leading to further integration into biological and clinical research. In this perspective article, we provide insight into the evolution and current state of IMS and propose some of the directions that IMS could develop in order to stay on course to become one of the most promising new tools in life science research.

Conditioned media from cell lines: a complementary model to clinical specimens for the discovery of disease-specific biomarkers

In the strictest sense, the cell secretome (conditioned media) refers to the collection of proteins that contain a signal peptide and are processed via the endoplasmic reticulum and Golgi apparatus through the classical secretion pathway. More generally, the secretome also encompasses proteins shed from the cell surface and intracellular proteins released through non-classical secretion pathway or exosomes. These secreted proteins include numerous enzymes, growth factors, cytokines and hormones or other soluble mediators. They are fundamental in the processes of cell growth, differentiation, invasion and angiogenesis by regulating cell-to-cell and cell-to-extracellular matrix interactions. The main aim of this review is to provide a synopsis of findings from the analysis of the secretome taking diabetes, cancer and neurodegenerative diseases as examples. We will also discuss the preparation of conditioned media and on the main proteomic-based methodological approaches that have been developed for the study of secreted/shed proteins.

Biosensors: the new wave in cancer diagnosis

The earlier cancer can be detected, the better the chance of a cure. Currently, many cancers are diagnosed only after they have metastasized throughout the body. Effective, accurate methods of cancer detection and clinical diagnosis are urgently needed. Biosensors are devices that are designed to detect a specific biological analyte by essentially converting a biological entity (ie, protein, DNA, RNA) into an electrical signal that can be detected and analyzed. The use of biosensors in cancer detection and monitoring holds vast potential. Biosensors can be designed to detect emerging cancer biomarkers and to determine drug effectiveness at various target sites. Biosensor technology has the potential to provide fast and accurate detection, reliable imaging of cancer cells, and monitoring of angiogenesis and cancer metastasis, and the ability to determine the effectiveness of anticancer chemotherapy agents. This review will briefly summarize the current obstacles to early detection of cancer and the expanding use of biosensors as a diagnostic tool, as well as some future applications of biosensor technology.

Plasma microRNA-122 as a biomarker for viral-, alcohol-, and chemical-related hepatic diseases

BACKGROUND

The liver is frequently subject to insult because of viral infection, alcohol abuse, or toxic chemical exposure. Extensive research has been conducted to identify blood markers that can better discern liver damage, but little progress has been achieved in clinical practice. Recently, circulating microRNAs (miRNAs) have been reported as potential biomarkers for the noninvasive diagnosis of cancer. In this study, we investigated whether plasma miRNAs have diagnostic utility in identifying liver disease.

METHODS

The study was divided into 2 phases: marker selection by real-time quantitative PCR analysis of a small set of plasma samples, and marker validation with a large set of plasma samples from 83 patients with chronic hepatitis B viral infections, 15 patients with skeletal muscle disease, and 40 healthy controls. Two mouse model systems, d-galactosamine- and alcohol-induced liver injury, were also developed to evaluate whether differences in miRNA concentration were associated with various liver diseases.

RESULTS

Among the miRNA candidates identified, miR-122 presented a disease severity-dependent change in plasma concentration in the patients and animal models. Compared with an increase in aminotransferase activity in the blood, the change in miR-122 concentration appeared earlier. Furthermore, this change was more specific for liver injury than for other organ damage and was more reliable, because the change was correlated with liver histologic stage.

CONCLUSIONS

Our findings suggest that circulating miR-122 has potential as a novel, predictive, and reliable blood marker for viral-, alcohol-, and chemical-induced liver injury.

Application of proteomic technologies for prostate cancer detection, prognosis, and tailored therapy

Prostate cancer affects 3 in 10 men over the age of 50 years, and, unfortunately, the clinical course of the disease is poorly predicted. At present, there is no means that can distinguish indolent from aggressive/metastatic tumors. Thus, a personalized clinical approach could be helpful in diagnosing clinically relevant disease and guiding appropriate patient therapy. Individualized medicine requires a deep knowledge of the molecular mechanisms underpinning prostate cancer carcinogenesis. Proteomics may be the most powerful way to uncover biomarkers of detection, prognosis, and prediction, as proteins do the work of the cell and represent the majority of the diagnostic markers and drug targets today. Proteomic technologies are rapidly advancing beyond the two-dimensional gel separation techniques of the past to new types of mass spectrometry and protein microarray analyses. Biological fluids and tissue-cell proteomes from men with prostate cancer are being explored to identify diagnostic and prognostic biomarkers and therapeutic targets using these new proteomic approaches. Traditional and novel proteomic technology and their application to prostate cancer studies in translational research will be presented and discussed in this review. Proteomics coupled with powerful nanotechnology-based biomarker discovery approaches may provide a new and exciting opportunity for body fluid-borne biomarker discovery and characterization. While innovative mass spectrometry technology and nanotrap could be applied to improve the discovery and measurement of biomarkers for the early detection of prostate cancer, the use of tissue proteomic tools such as the reverse-phase protein microarray may provide new approaches for personalization of therapies tailored to each tumor's unique pathway activation network.

Proteomic profiling of cancer--opportunities, challenges, and context

The article by Roesch-Ely and colleagues in a recent issue of The Journal of Pathology describes the use of proteomic techniques to examine mucosal biopsies in patients with head and neck squamous cell cancer (HNSCC) and in corresponding control samples. The authors were able to determine the anatomical site of origin of the biopsies based on modelling of multiplex protein datasets, and to use the information to analyse field cancerization as a means of predicting tumour recurrence. Although the study included only a relatively small number of cases, and will require future validation in a larger patient cohort, the results point to the potential of proteomics to increase our understanding of cancer biology, and in this instance to offer clinical value.

Molecular markers in the treatment of metastatic colorectal cancer

Although significant progress has been made in colorectal cancer (CRC) treatment within the last decade with the approval of multiple new agents, the prognosis for patients with metastatic CRC remains poor with 5-year survival rates of approximately 8%. Resistance to chemotherapy remains a major obstacle in effective CRC treatment and many patients do not receive any clinical benefit from chemotherapy. In addition, other patients will experience adverse reactions to treatment resulting in dose modifications or treatment withdrawal, which can severely reduce treatment efficacy. Currently, significant research efforts are attempting to identify reliable and validated biomarkers with which will guide clinicians to make more informed treatment decisions. Specifically, the use of molecular profiling has the potential to assist the clinician in administering the correct drug, dose, or intervention for the patient before the onset of therapy thereby selecting a treatment strategy likely to have the greatest clinical outcome while minimizing adverse events. However, until recently, personalized medicine is a paradigm that has existed more in conceptual terms than in reality with very few validated biomarkers used routinely in metastatic CRC treatment. Rapid advances in genomic, transcriptomic and proteomic technologies continues to improve our understanding of tumor biology, but the search for reliable biomarkers has turned out to be more challenging than previously anticipated with significant disparity in published literature and limited translation into routine clinical practice. Recent progress with the identification and validation of biomarkers to the anti-epidermal growth factor receptor monoclonal antibodies including KRAS and possibly BRAF provide optimism that the goal of individualized treatment is within reach. This review will highlight and discuss current progress in the search for biomarkers, the challenges this emerging field presents, and the future role of biomarkers in advancing CRC treatment.

Characterizations and validations of novel antibodies toward translational research

PURPOSE

There is significant need for well-characterized antibodies to the spectrum of human proteins encoded by the genome. Advances in tissue-based proteomic profiling have led to the discovery of many candidate molecular biomarkers and therapeutic targets for which development of clinical assays is depending on high quality antibodies. We developed an antibody validation approach for screening of new mAbs.

EXPERIMENTAL DESIGN

We utilized a multi-stage approach of protein array and immunohistochemistry. In the first phase, we screened the NCI60 panel of cell lines by means of protein array and select antibodies based on concordance of mRNA expression to protein array signal. Results of this assay are used to predict antibody titer for immunohistochemistry on the NCI60 cell lines, presented as a tissue microarray. In the final stage, we created a tissue-based protein expression map by performing immunohistochemistry on a multi-tumor tissue microarray.

RESULTS

The success rate of this systematic antibody-screening tool was approximately 93% as measured by the results from the protein array. Data from the NCI60 protein array could be used to predict antibody titer for immunohistochemistry, improving the success rate of immunohistochemical assay development.

CONCLUSIONS AND CLINICAL RELEVANCE

The presented strategy of antibody validation and characterization can be provided a new tool for exploration of human proteome.

Oncoproteomic analysis reveals co-upregulation of RELA and STAT5 in carboplatin resistant ovarian carcinoma

Background

Ovarian cancer is one of the most lethal types of female malignancy. Although most patients are initially responsive to platinum-based chemotherapy, almost all develop recurrent chemoresistant tumors and succumb to their diseases. Elucidating the pathogenesis underlying drug resistance is fundamental to the development of new therapeutics, leading to improved clinical outcomes in these patients.

Methods and Findings

We compared the proteomes of paired primary and recurrent post-chemotherapy ovarian high-grade serous carcinomas from nine ovarian cancer patients using CIEF/Nano-RPLC coupled with ESI-Tandem MS. As compared to their primary tumors, more than half of the recurrent tumors expressed higher levels of several proteins including CP, FN1, SYK, CD97, AIF1, WNK1, SERPINA3, APOD, URP2, STAT5B and RELA (NF-κB p65), which were also validated by quantitative RT-PCR. Based on shRNA screening for the upregulated genes in in vitro carboplatin-resistant cells, we found that simultaneous knockdown of RELA and STAT5B was most effective in sensitizing tumor cells for carboplatin treatment. Similarly, the NF-κB inhibitor, BMS-345541, and the STAT5 inhibitor, Dasatinib, significantly enhanced cell sensitivity to carboplatin. Moreover, both RELA and STAT5 are known to bind to the promoter region of Bcl-X, regulating its promoter activity. In this regard, augmented Bcl-xL expression was detected in carboplatin-resistant cells. Combined ectopic expression of RELA and STAT5B enhanced Bcl-xL promoter activity while treatment with BMS-345541 and Dasatinib decreased it. Chromatin immunoprecipitation of the Bcl-X promoter region using a STAT5 antibody showed induction of RELA and STAT5 DNA-binding segments both in naïve cells treated with a high concentration of carboplatin as well as in carboplatin-resistant cells.

Conclusions

Proteomic analysis identified RELA and STAT5 as two major proteins associated with carboplatin resistance in ovarian tumors. Our results further showed that NF-κB and STAT5 inhibitor could sensitize carboplatin-resistant cells and suggest that such inhibitors can be used to benefit patients with carboplatin-resistant recurrent ovarian cancer.

Glioma pathophysiology: insights emerging from proteomics

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein-protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.

Sweetening the pot: adding glycosylation to the biomarker discovery equation

BACKGROUND

Cancer has profound effects on gene expression, including a cell's glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones.

CONTENT

In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies--multiple reaction monitoring and lectin-antibody arrays--as potential tools for biomarker validation studies in pursuit of clinically useful tests.

SUMMARY

The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.