Opportunities and limitations of SELDI-TOF-MS in biomedical research: practical advices

SELDI-TOF MS analysis of alkylphenol exposed Atlantic cod with phenotypic variation in gonadosomatic index

Proteomics is a new and promising approach to evaluate potential effects of pollution. In order to investigate if there is a direct link between the protein expression profiles obtained by the SELDI-TOF MS technology and effects observed at the organism level in fish, plasma samples from unexposed and 20 ppb alkylphenol exposed female Atlantic cod (Gadus morhua) with high phenotypic variation in gonadosomatic index (GSI) were analyzed by SELDI-TOF MS. Principle component analysis (PCA) showed that the major proteomic variation present in the dataset (i.e. 23.6%) could be significantly correlated to the individual variation in GSI, which indicates that SELDI-TOF MS data can reflect effects observed at higher levels of organization in fish. Further exploration of the other principal components revealed an additional proteomic pattern specific for the alkylphenol exposed females. Hence, this study supports the usefulness of SELDI-TOF MS as a proteomic tool in ecotoxicological research.

Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms

Background

There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS) studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached.

Results

In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE) peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR) control approach and that the reproducibility of DE peak detection could thereby be increased.

Conclusions

Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

Novel Sample Preparation for Mass Spectral Analysis of Complex Biological Samples

The ability to combine a selective capture strategy with on chip MALDI-TOF analysis allows for rapid, sensitive analysis of a variety of different analytes. In this overview a series of applications of capture enhanced laser desorption ionization time of flight (CELDI-TOF) mass spectrometry are described. The key feature of the assay is an off-chip capture step that utilizes high affinity bacterial binding proteins to capture a selected ligand. This allows large volumes of sample to be used and provides for a concentration step prior to transfer to a gold chip for traditional mass spectral analysis. The approach can also be adapted to utilize specific antibody as the basis of the capture step. The direct and indirect CELDI-TOF assays are rapid, reproducible and can be a valuable proteomic tool for analysis of low abundance molecules present in complex mixtures like blood plasma.

Proteome technologies in studying the pathogenesisof psoriasis

Psoriasis is one of the most prevalent inflammatory dermatoses. At the same time, its pathogenesis has not been studied in full. Proteome profiling is currently a promising method to study the biological mechanisms of developing different diseases. Proteome technologies make it possible to detect changes in the skin protein profile in psoriatic patients and identify the revealed proteins. The proteins serve as potential targets for drugs or biomarkers for assessing the patients individual drug response. The article describes the key achievements in the field of studying the pathogenesis of psoriasis using proteome technologies (two-dimensional electrophoresis and mass spectrometry) set out in the latest literature sources, and also analyzes the results of the authors studies aimed at detecting proteins being markers of the patients response to the infliximab therapy.

Identification of low abundant secreted proteins and peptides from primary culture supernatants of human T-cells

Live cells continually communicate with their surroundings by the secretion of biomolecules, among which proteins and/or peptides are an important class. As such, these protein/peptide signals which end up in the extracellular medium, reflect the state of a cell in a certain condition, and as by definition are potential biomarkers indicative for specific physiological/pathological processes. We here report on a mass spectrometry based method for the detection and analysis of peptides and proteins secreted in a highly complex background, such as cell culture supernatant. Our method, which combines chromatography, high duty cycle tandem mass spectrometry and bio-informatics, enables the detection of interleukin-2 (IL-2), a cytokine secreted by activated T-cells, present in cell supernatant while representing only 0.006‰ of the total protein content. Moreover, the method allows the mass spectrometric analysis of signaling proteins in a non-targeted way and without any prior immunodepletion of the highest abundant cell culture medium proteins. In this study this is exemplified by the detection of yet two other secretory peptides, i.e., the granulins A and B, in the primary culture supernatant of non-activated T-cells.

Detection of cancer cells in the cerebrospinal fluid: current methods and future directions

The spread of cancer into the central nervous system is a serious problem leading to neurological symptoms and rapid mortality. The current tools available for detecting the spread of cancer into the cerebrospinal fluid (CSF) are cytology, neurologic examination, and neuroimaging. All three of these methods can be applied in concert to reach a diagnosis, but they all suffer from a lack of sensitivity, leading to delays in treatment in many cases. An overview of research tools in the field of CSF cancer detection reveals a variety of promising technologies that can be used to answer questions about the biology of metastatic cancer and to develop more powerful clinical detection methods. Methods currently under investigation include new immunocytochemistry methods and flow cytometry for the in vitro detection of cells. Additionally, polymerase chain reaction, fluorescence in situ hybridization, capillary electrophoresis with laser-induced fluorescence, and mass spectrometry using matrix-assisted laser absorption-deionization time-of-flight and surface-enhanced laser desorption/ionization time-of-flight techniques are being tested for in vitro assessment of the non-cellular biomarkers in CSF. For in vivo detection of cancer in the CSF, research techniques include certain quantum dot platforms as well as magnetic iron oxide nanoparticles. As systemic therapies for cancer improve, the CNS is becoming a more common site of disease recurrence. This increases the importance of effective detection methods in the CSF, since early intervention can maximize therapeutic benefit. Furthermore, many cell-based detection methods can be combined with therapeutic agents to serve multiple medical functions through a common targeting system.

Detection of mitochondrial biomarkers in eutopic endometria of endometriosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

OBJECTIVES

To detect specific mitochondrial proteins in eutopic endometrial samples from women with and without endometriosis and to build diagnostic models.

DESIGN

Eutopic endometrial samples from women with endometriosis (excluding adenomyosis) and women with benign indications as control were studied by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein-chip technology. After finding the biomarkers, the diagnostic model was evaluated and validated by leave-one cross-validation.

SETTING

Collaborative investigation in an academic research environment.

PATIENT(S)

Twenty-four patients with endometriosis (excluding adenomyosis) and 29 patients with benign indications as control.

INTERVENTION(S)

Surgical excision of eutopic endometrial biopsy of patients with endometriosis and controls.

MAIN OUTCOME MEASURE(S)

Mitochondrial protein expression.

RESULT(S)

Seventy-eight qualified mitochondrial protein peaks were detected, ten of them had a significant difference. Three combined potential biomarkers, with mass-to-charge ratios (m/z) of 15,334, 15,128, and 16,069, were found, and the diagnostic system distinguished endometriosis from control samples with a specificity of 86.2% and a sensitivity of 87.5%.

CONCLUSION(S)

We discovered potential mitochondrial biomarkers of eutopic endometrium in endometriosis and set up a diagnostic model. Further identification of the proteins we found will help to explain pathology, new diagnoses, and therapeutic approaches for endometriosis.

Analyses of PCSK9 post-translational modifications using time-of-flight mass spectrometry

Post-translational modification(s) can affect a protein's function - changing its half-life/stability, its protein-protein interactions, biological activity and/or sub-cellular localization. Following translation, a protein can be modified in several ways, including (i) disulfide bridge formation, (ii) chemical conversion of its constituent amino acids (for instance, glutamine can undergo deamidation to glutamic acid), (iii) sulfation, phosphorylation, de/acetylation, and glycosylation (to name a few), (iv) addition of other proteins as occurs during sumoylation and ubiquitination, and (v) proteolytic cleavage(s). There are several techniques available to identify and monitor post-translational modifications of proteins and peptides including mass spectrometry, two-dimensional sodium dodecyl sulfate polyacrylamide electrophoresis (2D-SDS-PAGE), radiolabeling, and immunoblotting. Ciphergen's surface-enhanced laser desorption/ionization time-of-flight mass spectrometer (SELDI-TOF-MS) has been used successfully for protein/peptide profiling in disease states and for the detection of protein/peptide biomarkers (1-4). In this chapter, the secreted proprotein convertase subtilisin/kexin 9 (PCSK9), which we study in our lab, is used to demonstrate coupling of immunoprecipitation with Ciphergen's time-of-flight mass spectrometer and its ProteinChip software to detect and analyze the common post-translational modifications of phosphorylation and glycosylation. The following topics are covered (1): preparation of cell extracts/samples/spent media (2), processing of samples by immunoprecipitation including optimization of conditions and (3) data acquisition by mass spectrometry and its subsequent analyses.

Protein microarrays: novel developments and applications

Protein microarray technology possesses some of the greatest potential for providing direct information on protein function and potential drug targets. For example, functional protein microarrays are ideal tools suited for the mapping of biological pathways. They can be used to study most major types of interactions and enzymatic activities that take place in biochemical pathways and have been used for the analysis of simultaneous multiple biomolecular interactions involving protein-protein, protein-lipid, protein-DNA and protein-small molecule interactions. Because of this unique ability to analyze many kinds of molecular interactions en masse, the requirement of very small sample amount and the potential to be miniaturized and automated, protein microarrays are extremely well suited for protein profiling, drug discovery, drug target identification and clinical prognosis and diagnosis. The aim of this review is to summarize the most recent developments in the production, applications and analysis of protein microarrays.

SELDI-TOF serum proteomics and colorectal cancer: a current overview

Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a widely used technology platform for diagnostic biomarker discovery in tissue, plasma and serum. High-throughput and simplicity of experimental procedures have allowed this technology to become an important research tool for biomarker discovery during the last years. This review provides an overview of SELDI-TOF functionality, its advantages and drawbacks and gives a current literature overview of colorectal cancer based serum biomarker detection. Further improvements in instrumentation sensitivity and labelling chemistries will enable detection of novel, tissue-leakage biomarkers in serum. However, major emphasis should be given on subsequent identification of differentially observed protein peaks detected by SELDI-TOF. Clinical validation in large patient cohorts will then allow transferring novel biomarkers into clinical use.

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.

Recent advances in clinical proteomics using mass spectrometry

The ultimate objective of clinical proteomics is the successful discovery, validation and translation of biomarkers, together with new therapeutic targets into medical practices. New highly developed technologies in proteomics and their use in understanding tumor biology have significant clinical potential in the diagnosis, prognosis and treatment of disease. Areas such as MS, new labeling technologies and advancements in bioinformatics systems are now used to successfully detect disease-associated biomarkers together with therapeutic targets in complex biological specimens, including biofluids, cell lysates and tissue biopsies. Recent improvements in sample preparation (specifically focused on fractionation and enrichment) are enabling the analysis of low-abundance proteins together with many types of post-translational modifications. Targeted proteomic diagnostics will play a significant role in the development of personalized molecular medicine, a process that will be vital in modernizing healthcare structures.

A magnetic bead-based serum proteomic fingerprinting method for parallel analytical analysis and micropreparative purification

ProteinChip surface-enhanced laser desorption/ionization technology and magnetic beads-based ClinProt system are commonly used for semi-quantitative profiling of plasma proteome in biomarker discovery. Unfortunately, the proteins/peptides detected by MS are non-recoverable. To obtain the protein identity of a MS peak, additional time-consuming and material-consuming purification steps have to be done. In this study, we developed a magnetic beads-based proteomic fingerprinting method that allowed semi-quantitative proteomic profiling and micropreparative purification of the profiled proteins in parallel. The use of different chromatographic magnetic beads allowed us to obtain different proteomic profiles, which were comparable to those obtained by the ProteinChip surface-enhanced laser desorption/ionization technology. Our assays were semi-quantitative. The normalized peak intensity was proportional to concentration measured by immunoassay. Both intra-assay and inter-assay coefficients of variation of the normalized peak intensities were in the range of 4-30%. Our method only required 2 microL of serum or plasma for generating enough proteins for semi-quantitative profiling by MALDI-TOF-MS as well as for gel electrophoresis and subsequent protein identification. The protein peaks and corresponding gel spots could be easily matched by comparing their intensities and masses. Because of its high efficiency and reproducibility, our method has great potentials in clinical research, especially in biomarker discovery.

Identification of disease- and therapy-associated proteome changes in the sera of patients with myelodysplastic syndromes and del(5q)

Using ProteinChip array technology, which is based on the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, we performed proteomic analyses on sera from myelodysplastic syndromes (MDSs) patients with an interstitial deletion of the long arm of chromosome 5 (del(5q)) and those from control individuals. One analysis with 80 samples from 29 patients and 51 control subjects resulted in the detection of 61 peak differences. Another analysis with 36 paired-samples from 18 patients collected before and after the treatment with lenalidomide (Revlimid) identified 19 differential peak features. We also observed differential profiles between the pre-treatment samples from the responders and those from the non-responders reflected by eight peak differences. On the basis of these data we developed two classification models that could distinguish between the diseased and the control subjects or between the responders and the non-responders. Efforts were made to purify and identify a range of differential peak proteins. We conclude that inter-α trypsin inhibitor, heavy chain H4 (fragments), serum transferrin, transthyretin (variants), haemoglobin and a protein peak at m/z 2791 could be potential disease-associated markers for del(5q) MDS. Platelet factor 4 (PF-4) and a peak at m/z 8559 may serve as therapy-associated markers and be potentially useful for monitoring and predicting the response to therapy.

A proteomic analysis reveals differential regulation of the σ(S)-dependent yciGFE(katN) locus by YncC and H-NS in Salmonella and Escherichia coli K-12

The stationary phase sigma factor σ(S) (RpoS) controls a regulon required for general stress resistance of the closely related enterobacteria Salmonella and Escherichia coli. The σ(S)-dependent yncC gene encodes a putative DNA binding regulatory protein. Application of the surface-enhanced laser desorption/ionization-time of flight (SELDI-TOF) ProteinChip technology for proteome profiling of wild-type and mutant strains of Salmonella enterica serovar Typhimurium revealed potential protein targets for YncC regulation, which were identified by mass spectrometry, and subsequently validated. These proteins are encoded by the σ(S)-dependent operon yciGFEkatN and regulation of their expression by YncC operates at the transcriptional level, as demonstrated by gene fusion analyses and by in vitro transcription and DNase I footprinting experiments with purified YncC. The yciGFE genes are present (without katN) in E. coli K-12 but are poorly expressed, compared with the situation in Salmonella. We report that the yciGFE(katN) locus is silenced by the histone-like protein H-NS in both species, but that σ(S) efficiently relieves silencing in Salmonella but not in E. coli K-12. In Salmonella, YncC acts in concert with σ(S) to activate transcription at the yciG promoter (pyciG). When overproduced, YncC also activated σ(S)-dependent transcription at pyciG in E. coli K-12, but solely by countering the negative effect of H-NS. Our results indicate that differences between Salmonella and E. coli K-12, in the architecture of cis-acting regulatory sequences upstream of pyciG, contribute to the differential regulation of the yciGFE(katN) genes by H-NS and YncC in these two enterobacteria. In E. coli, this locus is subject to gene rearrangements and also likely to horizontal gene transfer, consistent with its repression by the xenogeneic silencer H-NS.

Host-response biomarkers for diagnosis of late-onset septicemia and necrotizing enterocolitis in preterm infants

Preterm infants are highly susceptible to life-threatening infections that are clinically difficult to detect, such as late-onset septicemia and necrotizing enterocolitis (NEC). Here, we used a proteomic approach to identify biomarkers for diagnosis of these devastating conditions. In a case-control study comprising 77 sepsis/NEC and 77 nonsepsis cases (10 in each group being monitored longitudinally), plasma samples collected at clinical presentation were assessed in the biomarker discovery and independent validation phases. We validated the discovered biomarkers in a prospective cohort study with 104 consecutively suspected sepsis/NEC episodes. Proapolipoprotein CII (Pro-apoC2) and a des-arginine variant of serum amyloid A (SAA) were identified as the most promising biomarkers. The ApoSAA score computed from plasma apoC2 and SAA concentrations was effective in identifying sepsis/NEC cases in the case-control and cohort studies. Stratification of infants into different risk categories by the ApoSAA score enabled neonatologists to withhold treatment in 45% and enact early stoppage of antibiotics in 16% of nonsepsis infants. The negative predictive value of this antibiotic policy was 100%. The ApoSAA score could potentially allow early and accurate diagnosis of sepsis/NEC. Upon confirmation by further multicenter trials, the score would facilitate rational prescription of antibiotics and target infants who require urgent treatment.

Application of "omics" to prion biomarker discovery

The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrP^Sc, a pathological isoform of the host protein PrP^C, which is an essential component of the infectious prion. Immunochemical detection of PrP^Sc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrP^Sc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

The isolation and identification of a secreted biomarker associated with cell stress in serum-free CHO cell culture

One approach to improving mammalian culture productivity has been to reduce cell stress and cell death in the bioreactor, thus enhancing productivity through a longer phase of viability. Here we describe the isolation and identification of a biomarker for stress and viability loss in CHO culture. Using SELDI-TOF mass spectrometry to profile the protein component of supernatant culture media we have identified a peak at 7.7 kDa that was associated with loss of viability toward the end of the culture and simulated stress from both toxic metabolite accumulation and nutrient depletion. The relative intensity (signal/noise ratio) of the peak increased rapidly at the onset of dropping viability toward the end of the growth phase. Also, the peak height was seen to increase significantly when cells were grown under conditions emulating ammonia accumulation and glutamine deprivation. The species has been identified as a fragment of Galectin-1 (Gal-1) via MS/MS fingerprinting. We propose that this peak could be utilized as a marker for early onset of stress in cell culture. This work demonstrates the efficacy of SELDI technology to identify biomarkers in mammalian cell culture and highlights its value as a tool for the monitoring and improvement of culture processes.

Fiber evanescent wave spectroscopy using the mid-infrared provides useful fingerprints for metabolic profiling in humans

Fiber evanescent wave spectroscopy (FEWS) explores the mid-infrared domain, providing information on functional chemical groups represented in the sample. Our goal is to evaluate whether spectral fingerprints obtained by FEWS might orientate clinical diagnosis. Serum samples from normal volunteers and from four groups of patients with metabolic abnormalities are analyzed by FEWS. These groups consist of iron overloaded genetic hemochromatosis (GH), iron depleted GH, cirrhosis, and dysmetabolic hepatosiderosis (DYSH). A partial least squares (PLS) logistic method is used in a training group to create a classification algorithm, thereafter applied to a test group. Patients with cirrhosis or DYSH, two groups exhibiting important metabolic disturbances, are clearly discriminated from control groups with AUROC values of 0.94+/-0.05 and 0.90+/-0.06, and sensibility/specificity of 8684% and 8787%, respectively. When pooling all groups, the PLS method contributes to discriminate controls, cirrhotic, and dysmetabolic patients. Our data demonstrate that metabolic profiling using infrared FEWS is a possible way to investigate metabolic alterations in patients.

Proteomics and opportunities for clinical translation in urological disease

PURPOSE

Proteomics is a rapidly growing new discipline that has the potential to increase and improve the understanding of protein function and interaction in the context of systems biology. As a translational science it has the potential to identify many new therapeutic targets as well as diagnostic and prognostic biomarkers of disease. Proteomics approaches consist of a combination of powerful technologies such as protein/peptide separation, identification and bioinformatic detection, and quantitation based on powerful computational data processing tools. We present an overview of current proteomics technologies, a review of proteomics applications in urology and a perspective on the future of proteomics in clinical medicine.

MATERIALS AND METHODS

A literature search was performed on the basic concepts of proteomics and technologies commonly used in this field. Advantages, challenges and limitations of current proteomics approaches are discussed, and proteomics applications in the field of urology are presented.

RESULTS

The proteomics approaches to answer clinical questions have only recently been introduced. Many different technologies have been used in this field, which is moving from simple description to quantitative clinical applications.

CONCLUSIONS

Proteomics offers new approaches to the study of genitourinary tract diseases, and the potential to identify clinically relevant biomarkers and new therapeutic targets.

Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics. Thus, to carry out these studies Transcriptomics, Proteomics and Metabolomics approaches are employed together with an adequate integration of the information that they provide. In this article, an overview of the current methodologies and a thorough revision of the advances in analytical technologies and their possibilities for future developments and applications in the field of Nutrigenomics is provided.

Quantitative mass spectrometry-based techniques for clinical use: biomarker identification and quantification

The potential for development of personalised medicine through the characterisation of novel biomarkers is an exciting prospect for improved patient care. Recent advances in mass spectrometric (MS) techniques, liquid phase analyte separation and bioinformatic tools for high throughput now mean that this goal may soon become a reality. However, there are challenges to be overcome for the identification and validation of robust biomarkers. Bio-fluids such as plasma and serum are a rich source of protein, many of which may reflect disease status, and due to the ease of sampling and handling, novel blood borne biomarkers are very much sought after. MS-based methods for high throughput protein identification and quantification are now available such that the issues arising from the huge dynamic range of proteins present in plasma may be overcome, allowing deep mining of the blood proteome to reveal novel biomarker signatures for clinical use. In addition, the development of sensitive MS-based methods for biomarker validation may bypass the bottleneck created by the need for generation and usage of reliable antibodies prior to large scale screening. In this review, we discuss the MS-based methods that are available for clinical proteomic analysis and highlight the progress made and future challenges faced in this cutting edge area of research.

Application of SELDI-TOF-MS to identify serum biomarkers for renal cell carcinoma

PURPOSE

Early diagnosis is critical for improving the outcome of patients with renal cell carcinoma (RCC). In this study, we applied a proteomic approach to identify serum biomarkers associated with different stages of renal tumor development.

MATERIALS AND METHODS

The protein expression profiles in patient serum samples were analyzed using surface enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF-MS). The subjects included 65 patients with renal cell carcinomas, 34 with benign renal tumors, and 69 normal controls. A diagnostic decision tree was developed and validated based on the differentially expressed proteins between the serum of patients with small (<or=3 cm) RCC tumors and normal controls.

RESULTS

The numbers of proteins differentially expressed in the serum samples were 29 between the patients with RCC and normal controls, 18 between patients with RCC and benign renal tumors, and 35 between patients with small RCC tumors and normal controls, respectively. The diagnostic decision tree generated from the differentially expressed proteins between patients with small RCC tumors and normal controls proved efficient in the early diagnosis of renal cell carcinoma, with a sensitivity of 81.8% and specificity of 100%. The eukaryotic initiation factor 2B delta subunit (eIF2B-delta) was identified as the most highly up-regulated protein in the serum of patients with RCC.

CONCLUSIONS

SELDI-TOF-MS is a simple, sensitive and highly reproducible technique that can be used to identify serum biomarkers. The serum biomarkers identified by this study may facilitate early diagnosis of RCC and offer new targets for mechanistic understanding and clinical therapy of this disease.

Comparative analysis of differential serum low molecular weight proteins between colorectal cancer and other malignant tumors

AIM: To evaluate the diagnostic specificity of differentially expressed serum low molecular proteins for colorectal cancer by comparative analysis between the patients with colorectal cancer and with other malignant tumors.

METHODS: A total of 218 serum samples from patients with colorectal cancer (n = 68) and other malignant tumors (breast, gastric, esophagus, liver, lung and kidney, 25 cases each) were collected. Their serum protein fingerprinting was read by surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Biomarker Wizard software was used to analyze the distinct proteins between colorectal cancer and other malignant tumors and to create receiver operating characteristic (ROC) curves. Then Fisher's discriminant model was established using the distinct proteins with the area under the curve (AUC) > 0.8.

RESULTS: Relatively 12 proteins were highly expressed and 102 proteins were lowly expressed in the sera of colorectal cancer compared with that of the other malignant tumors. Of all the 75 proteins with AUC > 0.5 by ROC analysis, six proteins (AUC > 0.8) were selected to establish the Fisher's discriminant model. The accuracy of distinguishing colorectal cancer from other malignant tumors was 91.7%, and the sensitivity and specificity were 88.2% and 93.3%, respectively.

CONCLUSION: The significantly differentially expressed serum low molecular proteins have a high diagnostic specificity for distinguishing colorectal cancer from other malignant tumors, which deserves further research.

Plant proteomics: concepts, applications, and novel strategies for data interpretation

Proteomics is an essential source of information about biological systems because it generates knowledge about the concentrations, interactions, functions, and catalytic activities of proteins, which are the major structural and functional determinants of cells. In the last few years significant technology development has taken place both at the level of data analysis software and mass spectrometry hardware. Conceptual progress in proteomics has made possible the analysis of entire proteomes at previously unprecedented density and accuracy. New concepts have emerged that comprise quantitative analyses of full proteomes, database-independent protein identification strategies, targeted quantitative proteomics approaches with proteotypic peptides and the systematic analysis of an increasing number of posttranslational modifications at high temporal and spatial resolution. Although plant proteomics is making progress, there are still several analytical challenges that await experimental and conceptual solutions. With this review I will highlight the current status of plant proteomics and put it into the context of the aforementioned conceptual progress in the field, illustrate some of the plant-specific challenges and present my view on the great opportunities for plant systems biology offered by proteomics.

Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm

Single biomarker detection is common in clinical laboratories due to the currently available method spectrum. For various diseases, however, no specific single biomarker could be identified. A strategy to overcome this diagnostic void is to shift from single analyte detection to multiplexed biomarker profiling. Mass spectrometric methods were employed for biomarker discovery in body fluids. The enormous complexity of biofluidic proteome compartments implies upstream fractionation. For this reason, mass spectrometry (MS) was coupled to two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization, or capillary electrophoresis (CE). Differences in performance and operating characteristics make them differentially suited for routine laboratory applications. Progress in the field of clinical proteomics relies not only on the use of an adequate technological platform, but also on a fast and efficient proteomic workflow including standardized sample preparation, proteomic data processing, statistical validation of biomarker selection, and sample classification. Based on CE-MS analysis, we describe how proteomic technology can be implemented in a clinical laboratory environment. In the last part of this review, we give an overview of CE-MS-based clinical studies and present information on identity and biological significance of the identified peptide biomarkers providing evidence of disease-induced changes in proteolytic processing and posttranslational modification.

Sevelamer restores bone volume and improves bone microarchitecture and strength in aged ovariectomized rats

Sevelamer hydrochloride, a noncalcium phosphate binder, has been shown to reduce coronary artery and aortic calcification, and to improve trabecular bone mineral density in hemodialysis patients with chronic kidney disease. Here, we examined whether sevelamer given orally for 12 wk with normal food could restore bone volume (BV) and strength in aged ovariectomized (OVX) rats starting at 4 wk after OVX. Dual-energy x-ray absorptiometry, microcomputerized tomography, and bone histomorphometry analyses showed that OVX animals receiving sevelamer had increased trabecular BV (51%), trabecular number (43%), trabecular thickness (9%), cortical thickness (16%), mineral apposition rate (103%), bone formation rate (25%), and enhanced cortical and trabecular bone mechanical strength as compared with OVX rats. Sevelamer decreased collagen C telopeptide, increased osteocalcin levels, and decreased phosphate and magnesium levels without affecting calcium levels in the blood. Although sevelamer was not absorbed systemically, it stimulated osteoblast differentiation in BM-derived mesenchymal stem cell cultures, as evaluated by alkaline phosphatase positive colony-forming units, and inhibited recombinant human soluble receptor activator of nuclear factor-kappaB ligand-induced osteoclast differentiation, as evaluated by tartrate-resistant acid phosphatase positive cells in bone mineral-hematopoietic stem cell cultures. Surface enhanced laser desorption/ionization time-of-flight mass spectrometry analysis revealed that 69 proteins were differently expressed after OVX, of which 30% (20 of 69) were reversed to sham activity after sevelamer intake. PTH, fibroblast growth factor-23, and cytokine profile in serum were not significantly changed. Together, these results suggest that sevelamer in food increases the BV and improves biomechanical properties of bone in OVX rats.

The cancer secretome: a reservoir of biomarkers

Biomarkers are pivotal for cancer detection, diagnosis, prognosis and therapeutic monitoring. However, currently available cancer biomarkers have the disadvantage of lacking specificity and/or sensitivity. Developing effective cancer biomarkers becomes a pressing and permanent need. The cancer secretome, the totality of proteins released by cancer cells or tissues, provides useful tools for the discovery of novel biomarkers. The focus of this article is to review the recent advances in cancer secretome analysis. We aim to elaborate the approaches currently employed for cancer secretome studies, as well as its applications in the identification of biomarkers and the clarification of carcinogenesis mechanisms. Challenges encountered in this newly emerging field, including sample preparation, in vivo secretome analysis and biomarker validation, are also discussed. Further improvements on strategies and technologies will continue to drive forward cancer secretome research and enable development of a wealth of clinically valuable cancer biomarkers.

Multidimensional protein fractionation using ProteomeLab PF 2D for profiling amyotrophic lateral sclerosis immunity: A preliminary report

Background

The ProteomeLab™ PF 2D platform is a relatively new approach to global protein profiling. Herein, it was used for investigation of plasma proteome changes in amyotrophic lateral sclerosis (ALS) patients before and during immunization with glatiramer acetate (GA) in a clinical trial.

Results

The experimental design included immunoaffinity depletion of 12 most abundant proteins from plasma samples with the ProteomeLab™ IgY-12 LC10 column kit as first dimension separation, also referred to as immuno-partitioning. Second and third dimension separations of the enriched proteome were performed on the PF 2D platform utilizing 2D isoelectric focusing and RP-HPLC with the resulting fractions collected for analysis. 1D gel electrophoresis was added as a fourth dimension when sufficient protein was available. Protein identification from collected fractions was performed using nano-LC-MS/MS approach. Analysis of differences in the resulting two-dimensional maps of fractions obtained from the PF 2D and the ability to identify proteins from these fractions allowed sensitivity threshold measurements. Masked proteins in the PF 2D fractions are discussed.

Conclusion

We offer some insight into the strengths and limitations of this emerging proteomic platform.

Proteomic profiling of ovine serum by SELDI-TOF MS: optimisation, reproducibility and feasibility of biomarker discovery using routinely collected samples

The diagnosis of infectious diseases in animals may be enhanced by study of the serum proteome in which myriad components are influenced by physiological and pathological processes. Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS) has the capacity to detect known and unknown immunologically relevant molecules in the serum proteome. Optimum combinations of ProteinChip array surfaces, energy absorbing molecules, sample dilutions and instrument settings were determined for spectral generation from whole ovine sera. The coefficient of variation for within and between chip mass/charge and peak intensity were <0.03% and <23%, respectively. There were minor alterations in spectra associated with storage of chips or machine drift. Clotting times of 30 min to 3h did not greatly alter protein spectra although storage of sera at -20 degrees C led to alterations. However, routinely collected serum samples stored at -20 degrees C were useful for identification of biomarkers associated with vaccination with a bacterial antigen. This information will inform future studies on serum proteome profiling in livestock, but independent assessments are recommended for each species.

Urine in clinical proteomics

Urine has become one of the most attractive biofluids in clinical proteomics as it can be obtained non-invasively in large quantities and is stable compared with other biofluids. The urinary proteome has been studied by almost any proteomics technology, but mass spectrometry-based urinary protein and peptide profiling has emerged as most suitable for clinical application. After a period of descriptive urinary proteomics the field is moving out of the discovery phase into an era of validation of urinary biomarkers in larger prospective studies. Although mainly due to the site of production of urine, the majority of these studies apply to the kidney and the urinary tract, but recent data show that analysis of the urinary proteome can also be highly informative on non-urogenital diseases and used in their classification. Despite this progress in urinary biomarker discovery, the contribution of urinary proteomics to the understanding of the pathophysiology of disease upon analysis of the urinary proteome is still modest mainly because of problems associated to sequence identification of the biomarkers. Until now, research has focused on the highly abundant urinary proteins and peptides, but analysis of the less abundant and naturally existing urinary proteins and peptides still remains a challenge. In conclusion, urine has evolved as one of the most attractive body fluids in clinical proteomics with potentially a rapid application in the clinic.

Mass spectrometry and serum pattern profiling for analyzing the individual risk for endometriosis: promising insights?

OBJECTIVE

To evaluate whether distinct patterns of serum proteins in symptomatic women are of value to predict endometriosis before laparoscopy.

DESIGN

Prospective exploratory cohort study.

SETTING

Tertiary care center.

PATIENT(S)

A total of 91 consecutive symptomatic patients suffering from dysmenorrhea, dyspareunia, chronic pelvic pain, or unexplained infertility.

INTERVENTION(S)

Collection of serum samples and a standardized protocol for patients' history before laparoscopic diagnosis.

MAIN OUTCOME MEASURE(S)

Protein expression was analyzed by mass spectrometric analysis according to surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) standards. The analysis of data was performed using a genetic algorithm (ClinProTools 2.0 software) and a rule-based decision-tree algorithm (XLminer software).

RESULT(S)

A total of 90 out of 91 samples were eligible for analysis. At laparoscopy, 51 of 90 patients (56.7%) exhibited endometriosis and 39 of 90 (43.3%) were disease free. Analyzing the serum samples, the software revealed a unique selection of mass peaks between 2,000 and 20,000 Da, which allowed for discrimination between patients suffering from endometriosis and control subjects. Overall recognition capacity was 70.8%, exhibiting a sensitivity of 81.3% (95% confidence interval [CI] 66.5-92.5) and a specificity of 60.3% (95% CI 46.1-74.2]) using the genetic algorithm, and a sensitivity of 78.4% and a specificity of 59.0% using the rule-based decision-tree algorithm.

CONCLUSION(S)

These findings provide direct evidence that screening for serum protein patterns using SELDI-TOF MS before laparoscopy might be of discriminative value in the prediction of disease and partly confirms recently published data. However, in this prospective setting, we found both low sensitivity and low specificity, which disqualifies the screening for serum protein patterns by SELDI-TOF MS as a "quick fix" diagnostic test.

Proteomics Discovery of Disease Biomarkers

Recent technological developments in proteomics have shown promising initiatives in identifying novel biomarkers of various diseases. Such technologies are capable of investigating multiple samples and generating large amount of data end-points. Examples of two promising proteomics technologies are mass spectrometry, including an instrument based on surface enhanced laser desorption/ionization, and protein microarrays. Proteomics data must, however, undergo analytical processing using bioinformatics. Due to limitations in proteomics tools including shortcomings in bioinformatics analysis, predictive bioinformatics can be utilized as an alternative strategy prior to performing elaborate, high-throughput proteomics procedures. This review describes mass spectrometry, protein microarrays, and bioinformatics and their roles in biomarker discovery, and highlights the significance of integration between proteomics and bioinformatics.

Population proteomics: investigation of protein diversity in human populations

Outlined in this review is the concept of population proteomics, its aspects, enabling approaches, and significance in understanding proteins' roles in physiological processes and diseases. Population proteomics addresses the need for individual assessment of proteins across large populations to delineate the existence of structural variations, determine their frequency, and explore the association of the modifications with specific diseases. Besides the basic concepts and underlying reasons for such protein diversity studies, also reviewed here are the results of two fundamental studies that investigated human plasma protein diversity across the healthy population in the United States. Such studies of protein diversity are needed to map all the post-expression protein modifications and determine the wild-type protein profiles, similar to the human diversity studies at the genome level that have helped redefine the "normal" human genome.

Use of SELDI-TOF mass spectrometry for identification of new biomarkers: potential and limitations

Surface-enhanced laser desorption time of flight mass spectrometry (SELDI-TOF-MS) is an important proteomic technology that is immediately available for the high throughput analysis of complex protein samples. Over the last few years, several studies have demonstrated that comparative protein profiling using SELDI-TOF-MS breaks new ground in diagnostic protein analysis particularly with regard to the identification of novel biomarkers. Importantly, researchers have acquired a better understanding also of the limitations of this technology and various pitfalls in biomarker discovery. Bearing these in mind, great emphasis must be placed on the development of rigorous standards and quality control procedures for the pre-analytical as well as the analytical phase and subsequent bioinformatics applied to analysis of the data. To avoid the risk of false-significant results studies must be designed carefully and control groups accurately selected. In addition, appropriate tools, already established for analysis of highly complex microarray data, need to be applied to protein profiling data. To validate the significance of any candidate biomarker derived from pilot studies in appropriately designed prospective multi-center studies is mandatory; reproducibility of the clinical results must be shown over time and in different diagnostic settings. SELDI-TOF-MS-based studies that are in compliance with these requirements are now required; only a few have been published so far. In the meantime, further evaluation and optimization of both technique and marker validation strategies are called for before MS-based proteomic algorithms can be translated into routine laboratory testing.

Identifying biomarkers of endometriosis using serum protein fingerprinting and artificial neural networks

OBJECTIVES

To use surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) protein chip array technology to detect proteomic patterns in the serum of women with endometriosis; build diagnostic models; and evaluate their clinical significance.

METHODS

Serum samples from women with endometriosis and healthy women were studied using SELDI-TOF-MS protein chip technology. For every matched pair, two-thirds of the samples were used to look for different patterns and one-third was used for cross-validation.

RESULTS

Five potential biomarkers were found and the diagnostic system distinguished endometriosis from validation samples with a sensitivity of 91.7% and a specificity of 90.0%.

CONCLUSION

This method shows great potential in identifying biomarkers to be used for endometriosis screening.