Proteomics: New technologies and clinical applications

Identification of proteins related to SIS3 by iTRAQ and PRM-based comparative proteomic analysis in cisplatin-induced acute kidney injury

Background

Cisplatin is a commonly used nephrotoxic drug and can cause acute kidney injury (AKI). In the present study, isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM)-based comparative proteomics were used to analyze differentially expressed proteins (DEPs) to determine the key molecular mechanism in mice with cisplatin-induced AKI in the presence or absence of SIS3, a specific p-smad3 inhibitor, intervention.

Methods

The cisplatin-induced AKI mouse model was established and treated with SIS3. We used iTRAQ to search for DEPs, PRM to verify key DEPs and combined Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for bioinformatics analysis. We then assessed lipid deposition, malondialdehyde (MDA) and reactive oxygen species (ROS) and detected the expression of SREBF1, SCD1, CPT1A, PPARα and NDRG1 in vitro.

Results

Proteomic analysis showed that the identified DEPs were mainly enriched in energy metabolism pathways, especially in lipid metabolism. When SIS3 was applied to inhibit the phosphorylation of Smad3, the expression of NDRG1 and fatty acid oxidation key proteins CPT1A and PPARα increased, the expression of lipid synthesis related proteins SREBF1 and SCD1 decreased and the production of lipid droplets, MDA and ROS decreased.

Conclusion

SIS3 alleviates oxidative stress, reduces lipid accumulation and promotes fatty acid oxidation through NDRG1 in cisplatin-induced AKI. Our study provides a new candidate protein for elucidating the molecular mechanisms of fatty acid metabolism disorders in cisplatin-induced acute kidney injury.

Decoding Hidden Messengers: Proteomic Profiling of Exosomes in Mammary Cancer Research

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although a histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease's development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy can detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes attracted significant attention in cancer research because of their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play important roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discusses several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, studies conducted in canine species are scarce. This emphasis sheds light on the limited research available in this field. In addition, we present a curated selection of studies that explored exosomal proteins as potential biomarkers, aiming to achieve benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.

Integration of transcriptomic and proteomic analyses reveals several levels of metabolic regulation in the excess starch and early senescent leaf mutant lses1 in rice

BACKGROUND

The normal metabolism of transitory starch in leaves plays an important role in ensuring photosynthesis, delaying senescence and maintaining high yield in crops. OsCKI1 (casein kinase I1) plays crucial regulatory roles in multiple important physiological processes, including root development, hormonal signaling and low temperature-treatment adaptive growth in rice; however, its potential role in regulating temporary starch metabolism or premature leaf senescence remains unclear. To reveal the molecular regulatory mechanism of OsCKI1 in rice leaves, physiological, transcriptomic and proteomic analyses of leaves of osckI1 allele mutant lses1 (leaf starch excess and senescence 1) and its wild-type varieties (WT) were performed.

RESULTS

Phenotypic identification and physiological measurements showed that the lses1 mutant exhibited starch excess in the leaves and an obvious leaf tip withering phenotype as well as high ROS and MDA contents, low chlorophyll content and protective enzyme activities compared to WT. The correlation analyses between protein and mRNA abundance are weak or limited. However, the changes of several important genes related to carbohydrate metabolism and apoptosis at the mRNA and protein levels were consistent. The protein-protein interaction (PPI) network might play accessory roles in promoting premature senescence of lses1 leaves. Comprehensive transcriptomic and proteomic analysis indicated that multiple key genes/proteins related to starch and sugar metabolism, apoptosis and ABA signaling exhibited significant differential expression. Abnormal increase in temporary starch was highly correlated with the expression of starch biosynthesis-related genes, which might be the main factor that causes premature leaf senescence and changes in multiple metabolic levels in leaves of lses1. In addition, four proteins associated with ABA accumulation and signaling, and three CKI potential target proteins related to starch biosynthesis were up-regulated in the lses1 mutant, suggesting that LSES1 may affect temporary starch accumulation and premature leaf senescence through phosphorylation crosstalk ABA signaling and starch anabolic pathways.

CONCLUSION

The current study established the high correlation between the changes in physiological characteristics and mRNA and protein expression profiles in lses1 leaves, and emphasized the positive effect of excessive starch on accelerating premature leaf senescence. The expression patterns of genes/proteins related to starch biosynthesis and ABA signaling were analyzed via transcriptomes and proteomes, which provided a novel direction and research basis for the subsequent exploration of the regulation mechanism of temporary starch and apoptosis via LSES1/OsCKI1 in rice.

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.

New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease

Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

ProtRank: bypassing the imputation of missing values in differential expression analysis of proteomic data

Background

Data from discovery proteomic and phosphoproteomic experiments typically include missing values that correspond to proteins that have not been identified in the analyzed sample. Replacing the missing values with random numbers, a process known as “imputation”, avoids apparent infinite fold-change values. However, the procedure comes at a cost: Imputing a large number of missing values has the potential to significantly impact the results of the subsequent differential expression analysis.

Results

We propose a method that identifies differentially expressed proteins by ranking their observed changes with respect to the changes observed for other proteins. Missing values are taken into account by this method directly, without the need to impute them. We illustrate the performance of the new method on two distinct datasets and show that it is robust to missing values and, at the same time, provides results that are otherwise similar to those obtained with edgeR which is a state-of-art differential expression analysis method.

Conclusions

The new method for the differential expression analysis of proteomic data is available as an easy to use Python package.

Human salivary protein extraction from RNAPro·SAL™, Pure·SAL™, and passive drooling method

Objective:

The aim of the current study was to carry out a preliminary validation of devices for standardized collection of whole mouth fluid (WMF) in comparison to the passive drooling method for protein analysis in healthy subjects.

Materials and Methods:

A carefully designed sample collection/pretreatment protocol is crucial to the success of any saliva proteomics project. In this study, WMF was collected from healthy volunteers (n = 10, ages: 18–26 years). Individuals with any oral disease were excluded from the study group. In our study, we evaluated the following collection methods; the classical passive drooling method (unstimulated whole saliva) and standardized tools for saliva collection (Pure·SAL™, and RNAPro·SAL™) from Oasis Diagnostics^® Corporation (Vancouver WA, USA). For estimation of protein levels, we used the bicinchoninic acid assay and protein assay kit (Thermo Fisher). The two-dimensional gel electrophoresis sample analysis was carried out for the estimation of proteins in one of the samples.

Results:

When gels were compared, the difference was seen in the resolution of spots. Protein spots were fading from high- to low-molecular weight masses. Hence, advanced devices in comparison to spitting method resulted in much clearer protein spots which in turn prove the validation of devices.

Conclusions:

In this study, we concluded that protein extraction could be possible by both methods such as passive drooling method and through advanced saliva collection devices (Pure·SAL™ and RNAPro·SAL™).

Screening and Identification of Pregnancy Zone Protein and Leucine-Rich Alpha-2-Glycoprotein as Potential Serum Biomarkers for Early-Onset Myocardial Infarction using Protein Profile Analysis

PURPOSE

The present study aims to discover novel serum biomarkers of early-onset myocardial infarction (MI) using proteomic analysis.

EXPERIMENTAL DESIGN

In the first stage, the iTRAQ-coupled LC-MS/MS technique is utilized to investigate protein profiles of patients with early-onset MI. In the second stage, these candidate proteins are validated using ELISA.

RESULTS

A total of 538 proteins are quantified, with pregnancy zone protein (PZP), leucine-rich α-2-glycoprotein (LRG) and Apolipoprotein C-I (Apo C-I) being upregulated and Apolipoprotein A-I (Apo A-I) and Apolipoprotein A-IV (Apo A-IV) downregulated in early-onset MI patients. Results from the validation stage demonstrate that the serum concentrations of PZP and LRG are significantly increased in the early-onset MI group. The correlation between the concentrations of C-reactive protein (CRP) and the two candidate biomarkers is positive. Area under the curve values used to diagnose early-onset MI for LRG and PZP are 0.939 and 0.874, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

Five differential serum proteins are identified in early-onset MI using proteomic analysis. Lipoprotein-related biomarkers further demonstrate the close relationship between lipid metabolism and the disease. Inflammation-associated LRG and PZP may be novel biomarkers of the disease. In addition, changes in these proteins may partly reveal the possible mechanisms in the pathogenesis and pathophysiology of early-onset MI.

Uncovering the basis of viability loss in desiccation sensitive Trichilia dregeana seeds using differential quantitative protein expression profiling by iTRAQ

Recalcitrant seeds, unlike orthodox types, are desiccation sensitive and hence, cannot be stored using conventional seed storage methods In this study, relative changes of protein expression in T. dregeana seeds during desiccation and hydrated storage (a short- to medium-term storage method) were analysed to understand the basis of their desiccation- and storage-induced viability loss. Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) were used to compare (selected) protein expression levels across fresh, partially dehydrated and stored seeds. A total of 114 proteins were significantly differentially expressed in embryonic axes of fresh seeds and those seeds exposed to dehydration and hydrated storage (which exposed seeds to a mild dehydration stress). Proteins involved in protein synthesis were up-regulated in stored and dehydrated seeds, possibly in response to dehydration-induced repair processes and/or germinative development. A range of proteins related to antioxidant protection were variably up- and down-regulated in stored and dehydrated seeds, respectively. Additionally, a class I heat shock protein was down-regulated in dehydrated and stored seeds; no late embryogenesis abundant proteins were identified in both stored and dehydrated seeds; and storage and dehydration up-regulated proteins involved in the provision of energy for cell survival. The results suggest that dehydration- and storage-induced viability loss in recalcitrant seeds may be based on proteomic changes that lead to cellular redox imbalance and increased cell energy demands. This, together with the absence/down-regulation of proteins associated with desiccation tolerance in plant tissues may form part of the proteomic footprint for desiccation sensitivity in seeds.

Proteins Differentially Expressed in the Pancreas of Hepatic Alcohol Dehydrogenase-Deficient Deer Mice Fed Ethanol For 3 Months

OBJECTIVES

The aim of this study was to identify differentially expressed proteins in the pancreatic tissue of hepatic alcohol dehydrogenase-deficient deer mice fed ethanol to understand metabolic basis and mechanism of alcoholic chronic pancreatitis.

METHODS

Mice were fed liquid diet containing 3.5 g% ethanol daily for 3 months, and differentially expressed pancreatic proteins were identified by protein separation using 2-dimensional gel electrophoresis and identification by mass spectrometry.

RESULTS

Nineteen differentially expressed proteins were identified by applying criteria established for protein identification in proteomics. An increased abundance was found for ribosome-binding protein 1, 60S ribosomal protein L31-like isoform 1, histone 4, calcium, and adenosine triphosphate (ATP) binding proteins and the proteins involved in antiapoptotic processes and endoplasmic reticulum function, stress, and/or homeostasis. Low abundance was found for endoA cytokeratin, 40S ribosomal protein SA, amylase 2b isoform precursor, serum albumin, and ATP synthase subunit β and the proteins involved in cell motility, structure, and conformation.

CONCLUSIONS

Chronic ethanol feeding in alcohol dehydrogenase-deficient deer mice differentially expresses pancreatic functional and structural proteins, which can be used to develop biomarker(s) of alcoholic chronic pancreatitis, particularly amylase 2b precursor, and 60 kDa heat shock protein and those involved in ATP synthesis and blood osmotic pressure.

Proteomic identification of potential biomarkers for cervical squamous cell carcinoma and human papillomavirus infection

It is known that high-risk human papillomavirus infection is the main etiological factor in cervical carcinogenesis. However, human papillomavirus screening is not sufficient for early diagnosis. In this study, we aimed to identify potential biomarkers common to cervical carcinoma and human papillomavirus infection by proteomics for human papillomavirus-based early diagnosis and prognosis. To this end, we collected 76 cases of fresh cervical tissues and 116 cases of paraffin-embedded tissue slices, diagnosed as cervical squamous cell carcinoma, cervical intraepithelial neoplasia II-III, or normal cervix from ethnic Uighur and Han women. Human papillomavirus infection by eight oncogenic human papillomavirus types was detected in tissue DNA samples using a quantitative polymerase chain reaction. The protein profile of cervical specimens from human papillomavirus 16-positive squamous cell carcinoma and human papillomavirus-negative normal controls was analyzed by proteomics and bioinformatics. The expression of candidate proteins was further determined by quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry. We identified 67 proteins that were differentially expressed in human papillomavirus 16-positive squamous cell carcinoma compared to normal cervix. The quantitative reverse transcriptase-polymerase chain reaction analysis verified the upregulation of ASAH1, PCBP2, DDX5, MCM5, TAGLN2, hnRNPA1, ENO1, TYPH, CYC, and MCM4 in squamous cell carcinoma compared to normal cervix ( p < 0.05). In addition, the transcription of PCBP2, MCM5, hnRNPA1, TYPH, and CYC was also significantly increased in cervical intraepithelial neoplasia II-III compared to normal cervix. Immunohistochemistry staining further confirmed the overexpression of PCBP2, hnRNPA1, ASAH1, and DDX5 in squamous cell carcinoma and cervical intraepithelial neoplasia II-III compared to normal controls ( p < 0.05). Our data suggest that the expression of ASAH1, PCBP2, DDX5, and hnRNPA1, and possibly MCM4, MCM5, CYC, ENO1, and TYPH, is upregulated during cervical carcinogenesis and potentially associated with human papillomavirus infection. Further validation studies of the profile will contribute to establishing auxiliary diagnostic markers for human papillomavirus-based cancer prognosis.

Tubulin Beta-3 Chain as a New Candidate Protein Biomarker of Human Skin Aging: A Preliminary Study

Skin aging is a complex process, and a lot of efforts have been made to identify new and specific targets that could help to diagnose, prevent, and treat skin aging. Several studies concerning skin aging have analyzed the changes in gene expression, and very few investigations have been performed at the protein level. Moreover, none of these proteomic studies has used a global quantitative labeled proteomic offgel approach that allows a more accurate description of aging phenotype. We applied such an approach on human primary keratinocytes obtained from sun-nonexposed skin biopsies of young and elderly women. A total of 517 unique proteins were identified, and 58 proteins were significantly differentially expressed with 40 that were downregulated and 18 upregulated with aging. Gene ontology and pathway analysis performed on these 58 putative biomarkers of skin aging evidenced that these dysregulated proteins were mostly involved in metabolism and cellular processes such as cell cycle and signaling pathways. Change of expression of tubulin beta-3 chain was confirmed by western blot on samples originated from several donors. Thus, this study suggested the tubulin beta-3 chain has a promising biomarker in skin aging.

Acute Aortic Dissection Biomarkers Identified Using Isobaric Tags for Relative and Absolute Quantitation

The purpose of this study was to evaluate the utility of potential serum biomarkers for acute aortic dissection (AAD) that were identified by isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approaches. Serum samples from 20 AAD patients and 20 healthy volunteers were analyzed using iTRAQ technology. Protein validation was performed using samples from 120 patients with chest pain. A total of 355 proteins were identified with the iTRAQ approach; 164 proteins reached the strict quantitative standard, and 125 proteins were increased or decreased more than 1.2-fold (64 and 61 proteins were up- and downregulated, resp.). Lumican, C-reactive protein (CRP), thrombospondin-1 (TSP-1), and D-dimer were selected as candidate biomarkers for the validation tests. Receiver operating characteristic (ROC) curves show that Lumican and D-dimer have diagnostic value (area under the curves [AUCs] 0.895 and 0.891, P < 0.05). For Lumican, the diagnostic sensitivity and specificity were 73.33% and 98.33%, while the corresponding values for D-dimer were 93.33% and 68.33%. For Lumican and D-dimer AAD combined diagnosis, the sensitivity and specificity were 88.33% and 95%, respectively. In conclusion, Lumican has good specificity and D-dimer has good sensitivity for the diagnosis of AAD, while the combined detection of D-dimer and Lumican has better diagnostic value.

Human Saliva Collection Devices for Proteomics: An Update

There has been a rapid growth in the interest and adaptation of saliva as a diagnostic specimen over the last decade, and in the last few years in particular, there have been major developments involving the application of saliva as a clinically relevant specimen. Saliva provides a “window” into the oral and systemic health of an individual, and like other bodily fluids, saliva can be analyzed and studied to diagnose diseases. With the advent of new, more sensitive technologies to detect smaller concentrations of analytes in saliva relative to blood levels, there have been a number of critical developments in the field that we will describe. In particular, recent advances in standardized saliva collection devices that were not available three to four years ago, have made it easy for safe, simple, and non-invasive collection of samples to be carried out from patients. With the availability of these new technologies, we believe that in the next decade salivary proteomics will make it possible to predict and diagnose oral as well as systemic diseases, cancer, and infectious diseases, among others. The aim of this article is to review recent developments and advances in the area of saliva specimen collection devices and applications that will advance the field of proteomics.

Advances of Proteomic Sciences in Dentistry

Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.

Characterization and comparison of proteomes of albino sea cucumber Apostichopus japonicus (Selenka) by iTRAQ analysis

Sea cucumber is a commercially important marine organism in China. Of the different colored varieties sold in China, albino sea cucumber has the greatest appeal among consumers. Identification of factors contributing to albinism in sea cucumber is therefore likely to provide a scientific basis for improving the cultivability of these strains. In this study, two-dimensional liquid chromatography-tandem mass spectrometry coupled with isobaric tags for relative and absolute quantification labeling was used for the first time to quantitatively define the proteome of sea cucumbers and reveal proteomic characteristics unique to albino sea cucumbers. A total of 549 proteins were identified and quantified in albino sea cucumber and the functional annotations of 485 proteins have been exhibited based on COG database. Compared with green sea cucumber, 12 proteins were identified as differentially expressed in the intestine and 16 proteins in the body wall of albino sea cucumber. Among them, 5 proteins were up-regulated in the intestine and 8 proteins were down-regulated in body wall. Gene ontology annotations of these differentially expressed proteins consisted mostly of 'biological process'. The large number of differentially expressed proteins identified here should be highly useful in further elucidating the mechanisms underlying albinism in sea cucumber.

Identification of haptoglobin peptide as a novel serum biomarker for lung squamous cell carcinoma by serum proteome and peptidome profiling

To date, a number of potential biomarkers for lung squamous cell cancer (SCC) have been identified; however, sensitive biomarkers are currently lacking to detect early stage SCC due to low sensitivity and specificity. In the present study, we compared the 7 serum proteomic profiles of 11 SCC patients, 7 chronic obstructive pulmonary disease (COPD) patients and 7 healthy smokers as controls to identify potential serum biomarkers associated with SCC and COPD. Two-dimensional difference gel electrophoresis (2D-DIGE) and mass-spectrometric analysis (MS) using an affinity column revealed two candidate proteins, haptoglobin (HP) and apolipoprotein 4, as biomarkers of SCC, and α-1-antichymotrypsin as a marker of COPD. The iTRAQ technique was also used to identify SCC-specific peptides. HP protein expression was significantly higher in SCC patients than in COPD patients. Furthermore, two HP protein peptides showed significantly higher serum levels in SCC patients than in COPD patients. We established novel polyclonal antibodies for the two HP peptides and subsequently a sandwich enzyme-linked immunosorbent assay (ELISA) for the quantification of these specific peptides in patient and control sera. The sensitivity of detection by ELISA of one HP peptide (HP216) was 70% of SCC patients, 40% of COPDs patients and 13% of healthy controls. We also measured CYFRA, a cytokeratin fragment clinically used as an SCC tumor marker, in all the 28 cases and found CYFRA was detected in only seven SCC cases. However, when the measurement of HP216 was combined with that of CYFRA, 100% (10 of 10 patients) of SCC cases were detected. Our proteomic profiling demonstrates that the SCC-specific HP peptide HP216 may potentially be used as a diagnostic biomarker for SCC.

Differential Proteomic Analysis Using iTRAQ Reveals Alterations in Hull Development in Rice (Oryza sativa L.)

Rice hull, the outer cover of the rice grain, determines grain shape and size. Changes in the rice hull proteome in different growth stages may reflect the underlying mechanisms involved in grain development. To better understand these changes, isobaric tags for relative and absolute quantitative (iTRAQ) MS/MS was used to detect statistically significant changes in the rice hull proteome in the booting, flowering, and milk-ripe growth stages. Differentially expressed proteins were analyzed to predict their potential functions during development. Gene ontology (GO) terms and pathways were used to evaluate the biological mechanisms involved in rice hull at the three growth stages. In total, 5,268 proteins were detected and characterized, of which 563 were differentially expressed across the development stages. The results showed that the flowering and milk-ripe stage proteomes were more similar to each other (r=0.61) than either was to the booting stage proteome. A GO enrichment analysis of the differentially expressed proteins was used to predict their roles during rice hull development. The potential functions of 25 significantly differentially expressed proteins were used to evaluate their possible roles at various growth stages. Among these proteins, an unannotated protein (Q7X8A1) was found to be overexpressed especially in the flowering stage, while a putative uncharacterized protein (B8BF94) and an aldehyde dehydrogenase (Q9FPK6) were overexpressed only in the milk-ripe stage. Pathways regulated by differentially expressed proteins were also analyzed. Magnesium-protoporphyrin IX monomethyl ester [oxidative] cyclase (Q9SDJ2), and two magnesium-chelatase subunits, ChlD (Q6ATS0), and ChlI (Q53RM0), were associated with chlorophyll biosynthesis at different developmental stages. The expression of Q9SDJ2 in the flowering and milk-ripe stages was validated by qRT-PCR. The 25 candidate proteins may be pivotal markers for controlling rice hull development at various growth stages and chlorophyll biosynthesis pathway related proteins, especially magnesium-protoporphyrin IX monomethyl ester [oxidative] cyclase (Q9SDJ2), may provide new insights into the molecular mechanisms of rice hull development and chlorophyll associated regulation.

Ribosomal proteomics: Strategies, approaches, and perspectives

Over the past few decades, proteomic research has seen unprecedented development due to technological advancement. However, whole-cell proteomics still has limitations with respect to sample complexity and the accuracy of determining protein locations. To deal with these limitations, several subcellular proteomic studies have been initiated. Nevertheless, compared to other subcellular proteomic fields, such as mitochondrial proteomics, ribosomal proteomics has lagged behind due to the long-held idea that the ribosome is just a translation machine. Recently, with the proposed ribosome filter hypothesis and subsequent studies of ribosome-specific regulatory capacity, ribosomal proteomics has become a promising chapter for both proteomic and ribosomal research. In this review, we discuss the current strategies and approaches in ribosomal proteomics and the efficacies as well as disadvantages of individual approaches for further improvement.

Identification of potential biomarkers by serum proteomics analysis in rats with sepsis

This study was aimed to find new biomarkers for diagnosis and prediction of prognosis of sepsis. Serum samples from nonsurvivor, survivor, and control groups were obtained at 12 h after the induction of sepsis and labeled with isobaric tags (iTRAQ) and then analyzed by two-dimensional liquid chromatography and tandem mass spectrometry. Protein identification and quantification were obtained using mass spectrometry and the ProteinPilot software. Bioinformatics annotation was performed by searching against the PANTHER database. Enzyme-linked immunosorbent assays were used to further confirm the protein identification and differential expression. A logistic regression was then used to screen the index set for diagnosis and prognosis of sepsis. We found that 47 proteins were preferentially elevated in septic rats (both nonsurvivors and survivors) compared with the control rats, and 28 proteins were preferentially elevated in the NS rats as compared with the S group. Several biomarkers, such as multimerin 1, ficolin 1, carboxypeptidase N (CPN2), serine protease 1, and platelet factor 4, were tightly correlated with the diagnosis of sepsis. Logistic regression analyses established multimerin 1, pro-platelet basic protein, fibrinogen-α, and fibrinogen-β for prognosis of sepsis.

Mass spectrometry-based proteomic quest for diabetes biomarkers

Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Investigation of male infertility using quantitative comparative proteomics

Male factors account for 40% of infertility cases. The identification of differentially expressed proteins on spermatozoa from fertile and infertile men can help in the elucidation of the molecular basis of male infertility. The aim of this study was to compare sperm proteomes from 3 different groups: fertile men, normozoospermic men consulting for infertility, and normozoospermic men with an impaired capacity for fertilization (IVF-failure). We used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling, and LC-MS analysis to identify proteins that are differentially expressed. A total of 348 unique proteins were identified and quantified. The analysis identified 33 proteins that were differentially expressed in the IVF-failure group vs the fertile group. Comparison of the infertile and fertile groups revealed that 18 proteins appeared to be differentially expressed. Four proteins were similarly altered in the IVF-failure and infertile groups: semenogelin 1 (SEMG1), prolactin-induced protein (PIP), glyceraldehyde-3-phosphate dehydrogenase (GAPDHS), and phosphoglycerate kinase 2 (PGK2). These protein markers were selected for validation using multiple reactions monitoring mass spectrometry (MRM-MS) and further confirmed by Western blot analysis. Overall, these results suggest that a panel of proteins may be used as biomarkers for future studies of infertility.

Method validation for preparing serum and plasma samples from human blood for downstream proteomic, metabolomic, and circulating nucleic acid-based applications

BACKGROUND

Formal method validation for biospecimen processing in the context of accreditation in laboratories and biobanks is lacking. Serum and plasma processing protocols were validated for fitness-for-purpose in terms of key downstream endpoints, and this article demonstrates methodology for biospecimen processing method validation.

METHODS

Serum and plasma preparation from human blood was optimized for centrifugation conditions with respect to microparticle counts. Optimal protocols were validated for methodology and reproducibility in terms of acceptance criteria based on microparticle counts, DNA and hemoglobin concentration, and metabolomic and proteomic profiles. These parameters were also used to evaluate robustness for centrifugation temperature (4°C versus room temperature [RT]), deceleration (low, medium, high) and blood stability (after a 2-hour delay).

RESULTS

Optimal protocols were 10-min centrifugation for serum and 20-min for plasma at 2000 g, medium brake, RT. Methodology and reproducibility acceptance criteria were met for both protocols except for reproducibility of plasma metabolomics. Overall, neither protocol was robust for centrifugation at 4°C versus RT. RT gave higher microparticles and free DNA yields in serum, and fewer microparticles with less hemolysis in plasma. Overall, both protocols were robust for fast, medium, and low deceleration, with a medium brake considered optimal. Pre-centrifugation stability after a 2-hour delay was seen at both temperatures for hemoglobin concentration and proteomics, but not for microparticle counts.

CONCLUSIONS

We validated serum and plasma collection methods suitable for downstream protein, metabolite, or free nucleic acid-based applications. Temperature and pre-centrifugation delay can influence analytic results, and laboratories and biobanks should systematically record these conditions in the scope of accreditation.

Estimating influence of cofragmentation on peptide quantification and identification in iTRAQ experiments by simulating multiplexed spectra

Isobaric tag-based quantification such as iTRAQ and TMT is a promising approach to mass spectrometry-based quantification in proteomics as it provides wide proteome coverage with greatly increased experimental throughput. However, it is known to suffer from inaccurate quantification and identification of a target peptide due to cofragmentation of multiple peptides, which likely leads to under-estimation of differentially expressed peptides (DEPs). A simple method of filtering out cofragmented spectra with less than 100% precursor isolation purity (PIP) would decrease the coverage of iTRAQ/TMT experiments. In order to estimate the impact of cofragmentation on quantification and identification of iTRAQ-labeled peptide samples, we generated multiplexed spectra with varying degrees of PIP by mixing the two MS/MS spectra of 100% PIP obtained in global proteome profiling experiments on gastric tumor-normal tissue pair proteomes labeled by 4-plex iTRAQ. Despite cofragmentation, the simulation experiments showed that more than 99% of multiplexed spectra with PIP greater than 80% were correctly identified by three different database search engines-MODa, MS-GF+, and Proteome Discoverer. Using the multiplexed spectra that have been correctly identified, we estimated the effect of cofragmentation on peptide quantification. In 74% of the multiplexed spectra, however, the cancer-to-normal expression ratio was compressed, and a fair number of spectra showed the "ratio inflation" phenomenon. On the basis of the estimated distribution of distortions on quantification, we were able to calculate cutoff values for DEP detection from cofragmented spectra, which were corrected according to a specific PIP and probability of type I (or type II) error. When we applied these corrected cutoff values to real cofragmented spectra with PIP larger than or equal to 70%, we were able to identify reliable DEPs by removing about 25% of DEPs, which are highly likely to be false positives. Our experimental results provide useful insight into the effect of cofragmentation on isobaric tag-based quantification methods. The simulation procedure as well as the corrected cutoff calculation method could be adopted for quantifying the effect of cofragmentation and reducing false positives (or false negatives) in the DEP identification with general quantification experiments based on isobaric labeling techniques.

A novel highly reactive Fab antibody for breast cancer tissue diagnostics and staging also discriminates a subset of good prognostic triple-negative breast cancers

The discovery of novel markers for breast cancer (BC) has been recently relied on antibody combinatorial libraries and selection through phage display. We constructed a recombinant Fab library, and after selections against BC tissues, the FabC4 clone was thoroughly investigated by immunohistochemistry in 232 patients with long-term follow-up. The FabC4 ligand was determined by mass spectrometry. The FabC4 expression was associated with younger age, lack of progesterone receptor, higher histological grades and non-luminal subtypes, and it also identified a subset of good prognostic triple-negative BCs, possibly targeting a conformational epitope of Cytokeratin-10 (CK10). This new CK10-epitope specific antibody may open new possibilities in diagnostic and therapeutic strategies.

Biotechnology advances: a perspective on the diagnosis and research of Rabies Virus

Rabies is a widespread zoonotic disease responsible for approximately 55,000 human deaths/year. The direct fluorescent antibody test (DFAT) and the mouse inoculation test (MIT) used for rabies diagnosis, have high sensitivity and specificity, but are expensive and time-consuming. These disadvantages and the identification of new strains of the virus encourage the use of new techniques that are rapid, sensitive, specific and economical for the detection and research of the Rabies Virus (RABV). Real-time RT-PCR, phylogeographic analysis, proteomic assays and DNA recombinant technology have been used in research laboratories. Together, these techniques are effective on samples with low virus titers in the study of molecular epidemiology or in the identification of new disease markers, thus improving the performance of biological assays. In this context, modern advances in molecular technology are now beginning to complement more traditional approaches and promise to revolutionize the diagnosis of rabies. This brief review presents some of the recent molecular tools used for RABV analysis, with emphasis on rabies diagnosis and research.

The identification of plasma proteins associated with cancer-related fatigue syndrome (CRFS) in disease-free breast cancer patients using proteomic analysis

CONTEXT

Cancer-related fatigue syndrome (CRFS) affects a significant minority of women successfully treated for breast cancer, with symptoms lasting up to several years after finishing therapy.

OBJECTIVES

This analysis was conducted to identify plasma proteins associated with CRFS in disease-free breast cancer patients.

METHODS

Women were divided into those meeting the CRFS criteria (cases) and a control group on the basis of a diagnostic interview. Plasma samples were collected from 45 cases and 45 controls. Proteomic analysis was conducted using surface-enhanced laser desorption/ionization, a mass spectrometry (MS) technique. This was followed by further sample processing using one-dimensional gels and trypsin digest for protein identification using liquid chromatography and database searching.

RESULTS

CRFS was associated with a statistically significant increase in the intensity of seven MS spectra. A subsequent search of proteins corresponding to the MS spectra identified four acute phase proteins associated with a nonspecific immune response (serum amyloid A, collectin, and subunits of immunoglobulin G and complement C1Q).

CONCLUSION

These novel results (using a technique not previously used in fatigue research) add further weight to the hypothesis that CRFS may be precipitated and prolonged by a nonspecific sustained inflammatory response. Importantly, this has been identified from a global analysis of plasma, which was conducted with no prior assumptions. Although these results need confirmation, we would suggest that future treatments for CRFS should consider focusing on the modulation of this presumed prolonged immune response.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.

Current status and advances in quantitative proteomic mass spectrometry

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

Additions to the Human Plasma Proteome via a Tandem MARS Depletion iTRAQ-Based Workflow

Robust platforms for determining differentially expressed proteins in biomarker and discovery studies using human plasma are of great interest. While increased depth in proteome coverage is desirable, it is associated with costs of experimental time due to necessary sample fractionation. We evaluated a robust quantitative proteomics workflow for its ability (1) to provide increased depth in plasma proteome coverage and (2) to give statistical insight useful for establishing differentially expressed plasma proteins. The workflow involves dual-stage immunodepletion on a multiple affinity removal system (MARS) column, iTRAQ tagging, offline strong-cation exchange chromatography, and liquid chromatography tandem mass spectrometry (LC-MS/MS). Independent workflow experiments were performed in triplicate on four plasma samples tagged with iTRAQ 4-plex reagents. After stringent criteria were applied to database searched results, 689 proteins with at least two spectral counts (SC) were identified. Depth in proteome coverage was assessed by comparison to the 2010 Human Plasma Proteome Reference Database in which our studies reveal 399 additional proteins which have not been previously reported. Additionally, we report on the technical variation of this quantitative workflow which ranges from ±11 to 30%.

Proteomic approaches for investigation of therapy resistance in cancer

Resistance to anticancer therapy is a major obstacle for successful management of patients in oncology. Although in the past, various biological mechanisms involved in therapy resistance, in particular multidrug resistance, have been identified, cancer patients did not really benefit. The mechanisms include the enhanced activity of drug extrusion pumps, modulation of cellular death pathways, alteration and repair of target molecules and various other mechanisms. Together they build a complex network mediating an individual therapy-resistant phenotype. The improved description of this multifactorial network should be useful for prediction of treatment response and would allow to design an individual-tailored therapy regiment. Proteome analyzing technologies appear as powerful tools for identifying new factors and protein expression profiles associated with anticancer therapy resistance. In the last years, the application of proteomic techniques identified multiple new factors or protein expression signatures in drug-resistant cell models and cancerous tissues. However, the functional role and the clinical impact of these findings are not yet clarified. So far, none of the proteomic data were useful for the development of improved diagnostic tests, for prediction of individual therapy response or for development of updated chemosensitizers. Here, the previous therapy resistance-related proteome data and future perspectives will be discussed.

Quantitative proteomic approaches in biomarker discovery of inflammatory bowel disease

Proteomics offers considerable opportunities for either enhancing our biological understanding or discovering biomarkers, blood and biopsied specimen-based proteomic approaches, provide reproducible and quantitative tools that can complement clinical assessments and aid clinicians in the diagnosis and treatment of inflammatory bowel disease (IBD). Sometimes a differential diagnosis of Crohn's disease (CD) and ulcerative colitis (UC) and the prediction of treatment response can be deduced by finding meaningful biomarkers, for which the central platform for proteomics is tandem mass spectrometry (MS/MS). A range of workflows are available for protein (or peptide) separation prior to MS/MS as well as bioinformatics analysis to achieve protein identification, for which two-dimensional electrophoresis (2-DE) and subsequent mass spectrometry (MS), liquid chromatography-MS, difference gel electrophoresis following 2-DE, isobaric tags for relative and absolute quantification (iTRAQ), stable isotope labeling by amino acids and label-free quantification are under development. In this article, the current status and perspective of these advanced proteomic technologies are introduced, with examples of recent biomarkers focused on the diagnosis, treatment response, prognosis of IBD, and even colitis-associated carcinogenesis in both animal models and human patients.

Alcohol-induced alterations in maternal uterine endothelial proteome: a quantitative iTRAQ mass spectrometric approach

OBJECTIVE

To quantitate alcohol-induced alterations in the maternal uterine endothelial proteome utilizing iTRAQ-based mass spectrometry.

STUDY DESIGN

Uterine artery endothelial cells from third trimester pregnant ewes were FAC sorted, validated and treated without or with binge-like alcohol. Lysates were trypsin digested, iTRAQ-labeled, and analyzed using nano LC MS/MS.

RESULTS

Alcohol significantly upregulated 14 and downregulated 17 proteins (P<0.05) including those related to cell structure, transcription/translation regulation, histones, Ca(2+)/NO, and redox balance. Gene Ontology and ArrayTrack analyses revealed alterations to protein processing, binding, and nutrient metabolism pathways. Further, alcohol altered proteins previously correlated with fetal alcohol spectrum disorders (FASD) and those that regulate epigenetic, transcriptional, and translational processes.

CONCLUSIONS

Alcohol differentially alters the proteome in the maternal uterine compartment at the level of the endothelium. iTRAQ mass spectrometry provides a robust high throughput platform to comprehend the multi-mechanistic actions of alcohol and develop appropriate biomarkers and ameliorative measures for FASD.

The tumorigenic liver fluke Opisthorchis viverrini--multiple pathways to cancer

Liver fluke infection caused by Opisthorchis viverrini is a major public health problem in Thailand and adjacent countries. In addition to infection-associated morbidity, infection with O. viverrini and the related Clonorchis sinensis are unarguable risk factors for cholangiocarcinoma (CAA, bile-duct cancer). Here we review the pathogenesis of opisthorchiasis and the association between O. viverrini infection and bile-duct cancer, focusing on the molecular parallels between wound healing, chronic inflammation, and cancer development. We review a schema for human disease progression from fluke infection, chronic opisthorchiasis, advanced periductal fibrosis, and cholangiocarcinogenesis, and present a rationale for biomarker discovery to facilitate early intervention. We conclude by addressing post-genomic advances with a view to developing new control strategies to combat this infectious cancer.

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.

Clinical proteomics and OMICS clues useful in translational medicine research

Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been used to identify distinctive molecular signatures in a wide array of biological systems, spanning areas of basic biological research, clinical diagnostics, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomic approaches, leading to enhancement of the depth and breadth of proteome coverage.

Proteomic signatures, specific for multiple diseases, including cancer and pre-invasive lesions, are emerging. This article combines, in a simple manner, relevant proteomic and OMICS clues used in the discovery and development of diagnostic and prognostic biomarkers that are applicable to all clinical fields, thus helping to improve applications of clinical proteomic strategies for translational medicine research.

Identification of the up-regulation of TP-alpha, collagen alpha-1(VI) chain, and S100A9 in esophageal squamous cell carcinoma by a proteomic method

Esophageal squamous cell carcinoma (ESCC) is one of the most common primary malignant tumor of digestive tract. However, the early diagnosis and molecular mechanisms that underlie tumor formation and progression have been progressed less. To identify new biomarkers for ESCC, we performed a comparative proteomic research. Isobaric tags for relative and absolute quantitation-based proteomic method was used to screen biomarkers between ESCC and normal. 802 non-redundant proteins were identified, 39 of which were differentially expressed with 1.5-fold difference (29 up-regulated and 10 down-regulated). Through Swiss-Prot and GO database, the location and function of differential proteins were analyzed, which are related to the biological processes of binding, cell structure, signal transduction, cell adhesion, etc. Among the differentially expressed proteins, TP-alpha, collagen alpha-1(VI) chain and S100A9 were verified to be upregulated in 77.19%, 75.44% and 59.65% of ESCC by immunohistochemistry and western-blot. Diagnostic value of these three proteins was validated. These results provide new insights into ESCC biology and potential diagnostic and therapeutic biomarkers, which suggest that TP-alpha, collagen alpha-1(VI) chain and S100A9 are potential biomarkers of ESCC, and may play an important role in tumorigenesis and development of ESCC.

Mutual information optimization for mass spectra data alignment

"Signal" alignments play critical roles in many clinical setting. This is the case of mass spectrometry data, an important component of many types of proteomic analysis. A central problem occurs when one needs to integrate (mass spectrometry) data produced by different sources, e.g., different equipment and/or laboratories. In these cases some form of "data integration'" or "data fusion'" may be necessary in order to discard some source specific aspects and improve the ability to perform a classification task such as inferring the "disease classes'" of patients. The need for new high performance data alignments methods is therefore particularly important in these contexts. In this paper we propose an approach based both on an information theory perspective, generally used in a feature construction problem, and on the application of a mathematical programming task (i.e. the weighted bipartite matching problem). We present the results of a competitive analysis of our method against other approaches. The analysis was conducted on data from plasma/ethylenediaminetetraacetic acid (EDTA) of "control" and Alzheimer patients collected from three different hospitals. The results point to a significant performance advantage of our method with respect to the competing ones tested.

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

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

Quantitative proteomics analysis by isobaric tags for relative and absolute quantitation identified Lumican as a potential marker for acute aortic dissection

Acute aortic dissection (AAD) is a serious vascular disease. Currently the diagnosis relies on clinical and radiological means whereas serum biomarkers are lacking. The purpose of this study was to identify potential serum biomarkers for AAD using isobaric tags for relative and absolute quantitation (iTRAQ) approach. A total of 120 serum samples were collected from three groups: AAD patients (n = 60), patients with acute myocardial infarction (AMI, n = 30), and healthy volunteers (n = 30), whereas the first 10 samples from each group were used for iTRAQ analysis. Using iTRAQ approach, a total of 174 proteins were identified as significantly different between AAD patients and healthy subjects. Among them, forty-six proteins increased more than twofold, full-scale analysis using serum sample for the entire 120 subjects demonstrated that Lumican level was significantly increased relative to control and AMI samples. Further, Lumican level correlated with time from onset to admission in AAD but not AMI samples. Using iTRAQ approach, our study showed that Lumican may be a potential AAD-related serum marker that may assist the diagnosis of AAD.

Identification of ERp29 as a biomarker for predicting nasopharyngeal carcinoma response to radiotherapy

Radioresistance continues to be a major problem in the treatment of nasopharyngeal carcinoma (NPC). This study aimed to identify novel proteins associated with NPC radio-resistance. We used a mass spectrometry driven-proteomic strategy to identify novel proteins associated with NPC radio-resistance, and differential proteins were subsequently processed by bio-informatic analysis. As a result, twelve proteins were identified with aberrant expression in radioresistant (RR) NPC tissues compare to radiosensitive (RS) NPC tissues. Among these proteins, ERp29, Mn-SOD, HSP27 and GST ω1 were found to be significantly up-regulated in RR NPC tissues, and ERp29 was selected for further validation. Immunohistochemistry analysis confirmed that ERp29 was overexpressed in RR NPC tissues compared with RS NPC tissues. To prove the role of ERp29 in the induction of NPC radioresistance, ERp29 was down-regulated in the ERp29 enriched NPC cells CNE-1 and 6-10B by specific shRNA. Radiosensitivity was measured using cell proliferation assay and clonogenic survival assay, and cell apoptosis was measured using flow cytometric analysis. We found that ERp29 knockdown attenuated CNE-1 and 6-10B cell radioresistance and enhanced cell apoptosis. These results suggest that ERp29 associates with radioresistance in NPC, and ERp29 could be a potential biomarker for predicting NPC response to radiotherapy.