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

Recent Advances in the Detection of Food Toxins Using Mass Spectrometry

Edibles are the only source of nutrients and energy for humans. However, ingredients of edibles have undergone many physicochemical changes during preparation and storage. Aging, hydrolysis, oxidation, and rancidity are some of the major changes that not only change the native flavor, texture, and taste of food but also destroy the nutritive value and jeopardize public health. The major reasons for the production of harmful metabolites, chemicals, and toxins are poor processing, inappropriate storage, and microbial spoilage, which are lethal to consumers. In addition, the emergence of new pollutants has intensified the need for advanced and rapid food analysis techniques to detect such toxins. The issue with the detection of toxins in food samples is the nonvolatile nature and absence of detectable chromophores; hence, normal conventional techniques need additional derivatization. Mass spectrometry (MS) offers high sensitivity, selectivity, and capability to handle complex mixtures, making it an ideal analytical technique for the identification and quantification of food toxins. Recent technological advancements, such as high-resolution MS and tandem mass spectrometry (MS/MS), have significantly improved sensitivity, enabling the detection of food toxins at ultralow levels. Moreover, the emergence of ambient ionization techniques has facilitated rapid in situ analysis of samples with lower time and resources. Despite numerous advantages, the widespread adoption of MS in routine food safety monitoring faces certain challenges such as instrument cost, complexity, data analysis, and standardization of methods. Nevertheless, the continuous advancements in MS-technology and its integration with complementary techniques hold promising prospects for revolutionizing food safety monitoring. This review discusses the application of MS in detecting various food toxins including mycotoxins, marine biotoxins, and plant-derived toxins. It also explores the implementation of untargeted approaches, such as metabolomics and proteomics, for the discovery of novel and emerging food toxins, enhancing our understanding of potential hazards in the food supply chain.

Proteomics-Driven Biomarkers in Pancreatic Cancer

Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.

Proteomic studies on apoB-containing lipoprotein in cardiovascular research: A comprehensive review

The complexity of cardiovascular diseases (CVDs), which remains the leading cause of death worldwide, makes the current clinical pathway for cardiovascular risk assessment unsatisfactory, as there remains a substantial unexplained residual risk. Simultaneous assessment of a large number of plasma proteins may be a promising tool to further refine risk assessment, and lipoprotein-associated proteins have the potential to fill this gap. Technical advances now allow for high-throughput proteomic analysis in a reproducible and cost-effective manner. Proteomics has great potential to identify and quantify hundreds of candidate marker proteins in a sample and allows the translation from isolated lipoproteins to whole plasma, thus providing an individual multiplexed proteomic fingerprint. This narrative review describes the pathophysiological roles of atherogenic apoB-containing lipoproteins and the recent advances in their mass spectrometry-based proteomic characterization and quantitation for better refinement of CVD risk assessment.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Profiling of differentially expressed proteins between fresh and frozen-thawed Duroc boar semen using ProteinChip CM10

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis

Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.

From protein biomarkers to proteomics in dementia with Lewy Bodies

Dementia with Lewy Bodies (DLB) is the second most common neurodegenerative dementia. Despite considerable research progress, there remain gaps in our understanding of the pathophysiology and there is no disease-modifying treatment. Proteomics is a powerful tool to elucidate complex biological pathways across heterogenous conditions. This review summarizes the widely used proteomic methods and presents evidence for protein dysregulation in the brain and peripheral tissues in DLB. Proteomics of post-mortem brain tissue shows that DLB shares common features with other dementias, such as synaptic dysfunction, but retains a unique protein signature. Promising diagnostic biomarkers are being identified in cerebrospinal fluid (CSF), blood, and peripheral tissues, such as serum Heart-type fatty acid binding protein. Research is needed to track these changes from the prodromal stage to established dementia, with standardized workflows to ensure replicability. Identifying novel protein targets in causative biological pathways could lead to the development of new targeted therapeutics or the stratification of participants for clinical trials.

Selymatra: A web application for protein-profiling analysis of mass spectra

Surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry is a variant of the matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. It is used in many cases especially for the analysis of protein profiling and for preliminary screening of biomarkers in complex samples. Unfortunately, these analyses are time consuming and protein identification is generally strictly limited. SELDI-TOF analysis of mass spectra (SELYMATRA) is a web application (WA) developed to reduce these limitations by (i) automating the identification processes and (ii) introducing the possibility to predict proteins in complex mixtures from cells and tissues. The WA architectural pattern is the model-view-controller, commonly used in software development. The WA compares the mass value between two mass spectra (sample vs. control) to extract differences, and, according to the set parameters, it queries a local database to predict most likely proteins based on their masses and different expression amplification. The WA was validated in a cellular model overexpressing a tagged NURR1 receptor, being able to recognize the tagged protein in the profiling of transformed cells. A help page, including a description of parameters for WA use, is available on the website.

A brief review on novel biomarkers identified and advanced biosensing technologies developed for rapid diagnosis of Japanese Encephalitis Virus

Advanced biosensor technology research is imperative for the management of infectious disease outbreaks such as Japanese Encephalitis (JE), a zoonotic disease caused by the flavivirus JE virus (JEV) which is transmitted to humans (dead-end hosts) from the amplification host, pigs, via mosquitoes. To avoid future pandemic scenarios, proactive research rather than responsive research in the field of diagnostics is a requirement for development of rapid, sensitive and specific screening detection methods. In this mini-review, we have critically compared and evaluated the different types of biomarkers (antigen, antibody, nucleic acid) identified for JEV diagnostics and their specific roles in the manifestation of the infection which may be potentially used for therapeutics and drug development as no treatment is available for JE. Furthermore, different biosensors developed for the detection of JEV biomarkers have been discussed in detail to give an overview of the working principles (electrochemical, optical, etc.), fabrication components (signal amplifier, bioreceptor, etc.), detection limits and response times. This review provides a compact compiled base on available JEV diagnostic research work being currently carried out along with their limitations, future prospective, and major challenges faced. This will enable future development of rapid point-of-care diagnostic screening methods for JEV infection management, which may help reduce number of fatalities.

Understanding Cervical Cancer through Proteomics

Cancer is one of the leading public health issues worldwide, and the number of cancer patients increases every day. Particularly, cervical cancer (CC) is still the second leading cause of cancer death in women from developing countries. Thus, it is essential to deepen our knowledge about the molecular pathogenesis of CC and propose new therapeutic targets and new methods to diagnose this disease in its early stages. Differential expression analysis using high-throughput techniques applied to biological samples allows determining the physiological state of normal cells and the changes produced by cancer development. The cluster of differential molecular profiles in the genome, the transcriptome, or the proteome is analyzed in the disease, and it is called the molecular signature of cancer. Proteomic analysis of biological samples of patients with different grades of cervical intraepithelial neoplasia (CIN) and CC has served to elucidate the pathways involved in the development and progression of cancer and identify cervical proteins associated with CC. However, several cervical carcinogenesis mechanisms are still unclear. Detecting pathologies in their earliest stages can significantly improve a patient's survival rate, prognosis, and recurrence. The present review is an update on the proteomic study of CC.

MALDI-TOF MS-based total serum protein fingerprinting for liver cancer diagnosis

Serum is one of the most commonly used samples in many studies to identify protein biomarkers to diagnose cancer. Although conventional enzyme-linked immunosorbent assay (ELISA) or liquid chromatography-mass spectrometry (LC-MS)-based methods have been applied as clinical tools for diagnosing cancer, there have been troublesome problems, such as inferior multiplexing capabilities, high development costs and long turnaround times, which are inappropriate for high-throughput analytical platforms. Here, we developed a simple and robust cancer diagnostic method using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based total serum protein fingerprinting. First, serum samples were simply diluted with distilled water and subsequently spotted onto a MALDI plate without prior chromatographic purification or separation. The sample preparation method was enough to collect reproducible total serum protein fingerprints and would be highly advantageous for high-throughput assay. Each of the integrated main spectrum profiles (MSPs), which are representative of liver cancer patients (n = 40) or healthy controls (n = 80), was automatically generated by the MALDI Biotyper 3 software. The reliability of the integrated MSPs was successfully evaluated in comparison with a blind test set (n = 31), which consisted of 13 liver cancer patients and 18 healthy controls. Additionally, our partial least squares discriminant analysis (PLS-DA) demonstrated a statistically significant difference in MALDI-TOF MS-based total serum protein fingerprints between liver cancer patients and healthy controls. Taken together, this work suggests that this method may be an effective high-throughput platform technology for various cancer diagnoses and disease evaluations.

Complementarity of Matrix- and Nanostructure-Assisted Laser Desorption/Ionization Approaches

In recent years, matrix-assisted laser desorption/ionization (MALDI) has become the main tool for the study of biological macromolecules, such as protein nano-machines, especially in the determination of their molecular masses, structure, and post-translational modifications. A key role in the classical process of desorption and ionization of the sample is played by a matrix, usually a low-molecular weight weak organic acid. Unfortunately, the interpretation of mass spectra in the mass range of below m/z 500 is difficult, and hence the analysis of low molecular weight compounds in a matrix-assisted system is an analytical challenge. Replacing the classical matrix with nanomaterials, e.g., silver nanoparticles, allows improvement of the selectivity and sensitivity of spectrometric measurement of biologically important small molecules. Nowadays, the nanostructure-assisted laser desorption/ionization (NALDI) approach complements the classic MALDI in the field of modern bioanalytics. In particular, the aim of this work is to review the recent advances in MALDI and NALDI approaches.

[Detection of Serum Peptides in Patients with Lung Squamous Cell Carcinoma by MALDI-TOF-MS and Analysis of Their Correlation with Chemotherapy Efficacy]

BACKGROUND

Treatment options for patients with squamous cell carcinoma of the lung (SCC) are limited in chemotherapy. However, not all patients could benefit form standard platinum regimen. Considering the dismal prognosis of patients with advanced SCC, a greater focus on selecting sensitive chemotherapy regimens remains of upmost importance to improve outcomes in this disease. In this study, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to detect pre-chemotherapy serum peptides in advanced lung squamous cell carcinoma patients accepting paclitaxel combined with platinum chemotherapy and to analyze the correlation between serum peptides and chemotherapy efficacy.

METHODS

Patients with advanced lung squamous cell carcinoma received paclitaxel combining with platinum chemotherapy and evaluated the efficacy every two cycles. Evaluation of complete response (CR) or partial response (PR) patients defined as sensitive group, progressive disease (PD) patients defined as resistant group. Serum samples were collected from patients with lung squamous cell carcinoma. Eighty-one patients were randomly divided into training group (sensitive group I and resistant group I) and validation group (sensitive group II and resistant group II) according to the ratio of 3:1. Serum samples were pretreated and Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was used to detect serum peptide fingerprints. ClinProTools software was used to analyze the differences between the sensitive group I and the resistant group I. Three kinds of biological algorithms (SNN, GA, QC) built in CPT software were used to establish the curative effect prediction model respectively and the optimal algorithm was selected. The validation group was used for blind verification.

RESULTS

Thirty sensitive patients and 31 resistant patients were enrolled in the training group. Ten sensitive patients and 10 resistant patients were included in the validation group. The training group had 96 differentially expressed peptides in the sensitive and resistant patients, with 16 statistically significant peptides (P<0.001). The predictive model was established by 5 polypeptides (1,897.75 Da, 2,023.93 Da, 3,683.36 Da, 4,269.56 Da, 5,341.29 Da). The recognition rate of this model was 89.18% and the cross validation rate was 95.11%. The accuracy of the model was 85%, the sensitivity was 90.0% and the specificity was 80.0%. The median PFS in the sensitive group was better than patients in the resistant group (7.2 months 95%CI: 4.4-14.5 vs 1.8 months 95%CI: 0.7-3.5). The results showed that the differential peptides 4,232.04 Da and 4,269.56 Da were correlated with PFS in patients with lung squamous cell carcinoma (P<0.001).

CONCLUSIONS

MALDI-TOF-MS was used to detect the difference of serum peptides between sensitive and resistant groups. The preliminary curative effect prediction model was used to predict the efficacy of paclitaxel combined with platinum regimen. However, this model need further investigations to verify the accuracy and the sensitivity.

Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway

Coronary artery disease (CAD) is one of the largest causes of death worldwide yet the traditional risk factors, although useful in identifying people at high risk, lack the desired predictive accuracy. Techniques like quantitative plasma proteomics holds immense potential to identify newer markers and this study (conducted in three phases) was aimed to identify differentially expressed proteins in stable CAD patients. In the first (discovery) phase, plasma from CAD cases (angiographically proven) and controls were subjected to iTRAQ based proteomic analysis. Proteins found to be differentially expressed were then validated in the second and third (verification and validation) phases in larger number of (n = 546) samples. After multivariate logistic regression adjusting for confounding factors (age, diet, etc.), four proteins involved in the reverse cholesterol pathway (Apo A1, ApoA4, Apo C1 and albumin) along with diabetes and hypertension were found to be significantly associated with CAD and could account for approximately 88% of the cases as revealed by ROC analysis. The maximum odds ratio was found to be 6.70 for albumin (p < 0.0001), followed by Apo AI (5.07, p < 0.0001), Apo CI (4.03, p = 0.001), and Apo AIV (2.63, p = 0.003). Down-regulation of apolipoproteins and albumin implicates the impairment of reverse cholesterol pathway in CAD.

Potential Serum Markers for Monitoring the Progression of Hepatitis B Virus-Associated Chronic Hepatic Lesions to Liver Cirrhosis

BACKGROUND/AIMS

To screen for serum protein/peptide biomarkers of hepatitis B virus (HBV)-associated chronic hepatic lesions in an attempt to profile the progression of HBV-associated chronic hepatic lesions using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) techniques.

METHODS

Using SELDI-TOF MS, serum protein/peptide profiles on the CM10 ProteinChip arrays were obtained from a training group including 26 HBV-associated hepatocellular carcinoma patients with liver cirrhosis (LC), 30 HBV-associated LC patients, 85 patients at different stages of liver fibrosis, and 30 asymptomatic HBV carriers. The most valuable SELDI peak for predicting the progression to LC in HBV-infected patients was identified.

RESULTS

A SELDI peak of M/Z 5805 with value for predicting LC in HBV-infected patients was found and was identified as a peptide of the C-terminal fraction of the fibrinogen a-chain precursor, isoform 1.

CONCLUSIONS

The peptide of the C-terminal fraction of the fibrinogen α-chain precursor, isoform 1 with M/Z 5805, may be a serological biomarker for progression to LC in HBV-infected patients.

A SELDI-TOF approach to ecotoxicology: comparative profiling of low molecular weight proteins from a marine diatom exposed to CdSe/ZnS quantum dots

Quantum dots (QDs), namely semiconductor nanocrystals, due to their particular optical and electronic properties, have growing applications in device technology, biotechnology and biomedical fields. Nevertheless, the possible threat to human health and the environment have attracted increasing attention as the production and applications of QDs increases rapidly while standard evaluation of safety lags. In the present study we performed proteomic analyses, by means of 2D gel electrophoresis and Surface Enhanced Laser Desorption Ionization-Time of Flight-Mass Spectrometry (SELDI-TOF-MS). We aimed to identify potential biomarkers of exposure to CdSe/ZnS quantum dots. The marine diatom Phaeodactylum tricornutum exposed to 2.5nM QDs was used as a model system. Both 2DE and SELDI showed the presence of differentially expressed proteins. By Principal Component Analysis (PCA) we were able to show that the differentially expressed proteins can discriminate between exposed and not exposed cells. Furthermore, a protein profile specific for exposed cells was obtained by SELDI analysis. To our knowledge, this is the first example of the application of SELDI technology to the analysis of microorganisms used as biological sentinel model of marine environmental pollution.

Molecularly imprinted polymers coupled to matrix assisted laser desorption ionization mass spectrometry for femtomoles detection of cardiac troponin I peptides

Molecularly imprinted polymers (MIPs) were combined to MALDI-TOF-MS to evaluate a selective enrichment (SE) method for the determination of clinically relevant biomarkers from complex biological samples. The concept was proven with the myocardial injury marker Troponin I (cTnI). In a first part, MIP materials entailed for the recognition of cTnI epitopes (three peptides selected) were prepared and characterized in dimensions (0.7-2μm), dissociation constants (58-817 nM), kinetics of binding (5-60 min), binding capacity (ca. 1.5 µg/mg polymer), imprinting factors (3 > IF > 5) and selectivity for the peptide epitope. Then, the MIPs, incubated with cTnI peptides and spotted on the target with the DHB matrix, were assayed for the desorption of the peptides in MALDI-TOF-MS. The measured detection limit was ca. 300 femtomols. Finally, the MIP-SE MALDI-TOF-MS was tested for its ability to enrich in the cTnI peptides from a complex sample, mimic of serum (i.e. 81 peptides of digested albumin). The MIP-SE MALDI-TOF-MS successfully enriched in cTnI peptides from the complex sample proving the technique could offer a flexible platform to prepare entailed materials suitable for diagnostic purposes.

Candidate proteomic biomarkers for three genogroups of the swine pathogen Streptococcus suis serotype 2

BACKGROUND

Streptococcus suis, more specifically serotype 2, is a major swine pathogen and an emerging zoonotic agent that causes severe infections such as meningitis, endocarditis, and septicemia. In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) was used to investigate the protein expression profiles of 45 strains of S. suis serotype 2 that had previously been clustered by multilocus sequence typing (MLST) into three sequence types (ST1, ST25, and ST28) (n = 15 for each ST).

RESULTS

The SELDI data were analyzed using the univariate Mann-Whitney and Kruskal-Wallis tests and multivariate statistical methods (heatmap/hierarchical clustering). The heatmap identified 136 cell proteins, and hierarchical clustering provided a 100% correct classification of all fifteen ST1 and ST25 strains and thirteen of the fifteen ST28 strains (87% correct). The univariate statistical analyses of the SELDI protein expression profiles identified nine significant proteins that discriminated the strains of the three STs of S. suis. Of these proteins, two were overexpressed in ST1 (5958 Da and 10249 Da), four in ST25 (5989 Da, 6646 Da, 7421 Da, and 9825 Da), and three in ST28 (4516 Da, 7833 Da, and 9342 Da). Two of the proteins associated with the ST28 strains (p4516 and p9342) were purified and were identified as a putative ABC transporter and a nucleoid-DNA-binding protein, respectively.

CONCLUSIONS

SELDI analysis of 45 strains of S. suis allowed to identify nine statistically significant proteins that can be specifically correlated with either ST1, ST25 or ST28. The possible involvement of the overexpressed proteins in the pathology of S. suis infections will require further investigation.

Biomarker Characterization by MALDI-TOF/MS

Mass spectrometric techniques frequently used in clinical diagnosis, such as gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, ambient ionization mass spectrometry, and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF/MS), are discussed. Due to its ability to rapidly detect large biomolecules in trace amounts, MALDI-TOF/MS is an ideal tool for characterizing disease biomarkers in biologic samples. Clinical applications of MS for the identification and characterization of microorganisms, DNA fragments, tissues, and biofluids are introduced. Approaches for using MALDI-TOF/MS to detect various disease biomarkers including peptides, proteins, and lipids in biological fluids are further discussed. Finally, various sample pretreatment methods which improve the detection efficiency of disease biomarkers are introduced.

Apolipoprotein C1 (APOC1) as a novel diagnostic and prognostic biomarker for lung cancer: A marker phase I trial

BACKGROUND

Tumor cells continuously evolve over time in response to host pressures. However, explanations as to how tumor cells are influenced by the inflammatory tumor microenvironment over time are, to date, poorly defined. We hypothesized that prognostic biomarkers could be obtained by exploring the expression of inflammation-associated genes between early and late stage lung cancer tumor samples.

METHODS

Candidate inflammation-associated genes, apolipoprotein C-1 (APOC1), MMP1, KMO)1, CXCL5, CXCL)7, IL-1α, IL-1β, TNF-α and IL-6 were verified by real-time quantitative polymerase chain reaction. Gene expression profiles and immunofluorescence staining of 30 lung cancer tissues were compared.

RESULTS

Expressions of APOC1 and IL-6 mRNA on tumor tissues in late stage disease were significantly higher than in early stage lung cancer samples. Immunofluorescence staining of tumor samples showed that the expression of APOC1 gradually increased from early to late stage in lung cancer patients. The expression levels of IL-6 and APOC1 in tumor samples were positively correlated; however, no prognostic value of APOC1 can be identified in serum samples.

CONCLUSIONS

We found that the level of tumor APOC1 was highly expressed in late stage lung cancer. Further research is warranted to determine the molecular mechanisms underlying the cross talk of APOC1 and IL-6 in tumor progression. An expanded sample size marker phase II study may lead to the discovery of new lung cancer therapeutics targeting APOC1.

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Discovery and identification of serum potential biomarkers for pulmonary tuberculosis using iTRAQ-coupled two-dimensional LC-MS/MS

Pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis is a chronic disease. Currently, there are no sufficiently validated biomarkers for early diagnosis of TB infection. In this study, a panel of potential serum biomarkers was identified between patients with pulmonary TB and healthy controls by using iTRAQ-coupled 2D LC-MS/MS technique. Among 100 differentially expressed proteins screened, 45 proteins were upregulated (>1.25-fold at p < 0.05) and 55 proteins were downregulated (<0.8-fold at p < 0.05) in the TB serum. Bioinformatics analysis revealed that the differentially expressed proteins were related to the response to stimulus, the metabolic and immune system processes. The significantly differential expression of apolipoprotein CII (APOCII), CD5 antigen-like (CD5L), hyaluronan-binding protein 2 (HABP2), and retinol-binding protein 4 (RBP4) was further confirmed using immunoblotting and ELISA analysis. By forward stepwise multivariate regression analysis, a panel of serum biomarkers including APOCII, CD5L, and RBP4 was obtained to form the disease diagnostic model. The receiver operation characteristic curve of the diagnostic model was 0.98 (sensitivity = 93.42%, specificity = 92.86%). In conclusion, APOCII, CD5L, HABP2, and RBP4 may be potential protein biomarkers of pulmonary TB. Our research provides useful data for early diagnosis of TB.

Investigation of serum protein profiles in scrapie infected sheep by means of SELDI-TOF-MS and multivariate data analysis

Background

Classical scrapie in sheep is a fatal neurodegenerative disease associated with the conversion PrP^C to PrP^Sc. Much is known about genetic susceptibility, uptake and dissemination of PrP^Sc in the body, but many aspects of prion diseases are still unknown. Different proteomic techniques have been used during the last decade to investigate differences in protein profiles between affected animals and healthy controls. We have investigated the protein profiles in serum of sheep with scrapie and healthy controls by SELDI-TOF-MS and LC-MS/MS. Latent Variable methods such as Principal Component Analysis, Partial Least Squares-Discriminant Analysis and Target Projection methods were used to describe the MS data.

Results

The serum proteomic profiles showed variable differences between the groups both throughout the incubation period and at the clinical end stage of scrapie. At the end stage, the target projection model separated the two groups with a sensitivity of 97.8%, and serum amyloid A was identified as one of the protein peaks that differed significantly between the groups.

Conclusions

At the clinical end stage of classical scrapie, ten SELDI peaks significantly discriminated the scrapie group from the healthy controls. During the non-clinical incubation period, individual SELDI peaks were differently expressed between the groups at different time points. Investigations of differences in -omic profiles can contribute to new insights into the underlying disease processes and pathways, and advance our understanding of prion diseases, but comparison and validation across laboratories is difficult and challenging.

A SELDI mass spectrometry study of experimental autoimmune encephalomyelitis: sample preparation, reproducibility, and differential protein expression patterns

Background

Experimental autoimmune encephalomyelitis (EAE) is an autoimmune, inflammatory disease of the central nervous system that is widely used as a model of multiple sclerosis (MS). Mitochondrial dysfunction appears to play a role in the development of neuropathology in MS and may also play a role in disease pathology in EAE. Here, surface enhanced laser desorption ionization mass spectrometry (SELDI-MS) has been employed to obtain protein expression profiles from mitochondrially enriched fractions derived from EAE and control mouse brain. To gain insight into experimental variation, the reproducibility of sub-cellular fractionation, anion exchange fractionation as well as spot-to-spot and chip-to-chip variation using pooled samples from brain tissue was examined.

Results

Variability of SELDI mass spectral peak intensities indicates a coefficient of variation (CV) of 15.6% and 17.6% between spots on a given chip and between different chips, respectively. Thinly slicing tissue prior to homogenization with a rotor homogenizer showed better reproducibility (CV = 17.0%) than homogenization of blocks of brain tissue with a Teflon® pestle (CV = 27.0%). Fractionation of proteins with anion exchange beads prior to SELDI-MS analysis gave overall CV values from 16.1% to 18.6%. SELDI mass spectra of mitochondrial fractions obtained from brain tissue from EAE mice and controls displayed 39 differentially expressed proteins (p≤ 0.05) out of a total of 241 protein peaks observed in anion exchange fractions. Hierarchical clustering analysis showed that protein fractions from EAE animals with severe disability clearly segregated from controls. Several components of electron transport chain complexes (cytochrome c oxidase subunit 6b1, subunit 6C, and subunit 4; NADH dehydrogenase flavoprotein 3, alpha subcomplex subunit 2, Fe-S protein 4, and Fe-S protein 6; and ATP synthase subunit e) were identified as possible differentially expressed proteins. Myelin Basic Protein isoform 8 (MBP8) (14.2 kDa) levels were lower in EAE samples with advanced disease relative to controls, while an MBP fragment (12. 4kDa), likely due to calpain digestion, was increased in EAE relative to controls. The appearance of MBP in mitochondrially enriched fractions is due to tissue freezing and storage, as MBP was not found associated with mitochondria obtained from fresh tissue.

Conclusions

SELDI mass spectrometry can be employed to explore the proteome of a complex tissue (brain) and obtain protein profiles of differentially expressed proteins from protein fractions. Appropriate homogenization protocols and protein fractionation using anion exchange beads can be employed to reduce sample complexity without introducing significant additional variation into the SELDI mass spectra beyond that inherent in the SELDI- MS method itself. SELDI-MS coupled with principal component analysis and hierarchical cluster analysis provides protein patterns that can clearly distinguish the disease state from controls. However, identification of individual differentially expressed proteins requires a separate purification of the proteins of interest by polyacrylamide electrophoresis prior to trypsin digestion and peptide mass fingerprint analysis, and unambiguous identification of differentially expressed proteins can be difficult if protein bands consist of several proteins with similar molecular weights.

Advances in MALDI mass spectrometry in clinical diagnostic applications

The concept of matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) was first reported in 1985. Since then, MALDI MS technologies have been evolving, and successfully used in genome, proteome, metabolome, and clinical diagnostic research. These technologies are high-throughput and sensitive. Emerging evidence has shown that they are not only useful in qualitative and quantitative analyses of proteins, but also of other types of biomolecules, such as DNA, glycans, and metabolites. Recently, parallel fragmentation monitoring (PFM), which is a method comparable to selected reaction monitoring, has been reported. This highlights the potentials of MALDI-TOF/TOF tandem MS in quantification of metabolites. Here we critically review the applications of the major MALDI MS technologies, including MALDI-TOF MS, MALDI-TOF/TOF MS, SALDI-TOF MS, MALDI-QqQ MS, and SELDI-TOF MS, to the discovery and quantification of disease biomarkers in biological specimens, especially those in plasma/serum specimens. Using SELDI-TOF MS as an example, the presence of systemic bias in biomarker discovery studies employing MALDI-TOF MS and its possible solutions are also discussed in this chapter. The concepts of MALDI, SALDI, SELDI, and PFM are complementary to each other. Theoretically, all these technologies can be combined, leading to the next generation of the MALDI MS technologies. Real applications of MALDI MS technologies in clinical diagnostics should be forthcoming.

Detection of serum protein biomarkers by surface enhanced laser desorption/ionization in patients with adenocarcinoma of the lung

AIM

Early diagnosis of lung cancer is important for successful treatment and improving the outcome of patients. We explored novel tools for screening serum biomarkers to distinguish adenocarcinoma of the lung from healthy controls by serum protein profiles.

METHODS

Serum samples were taken from 31 patients with adenocarcinoma of the lung and 31 healthy controls, matched for age, sex and smoking status. Serum samples were applied to strong anion 2(SAX-2) protein chips to generate mass spectra by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Protein peak identification and clustering were performed using Biomarker Wizard, compared by MATLAB 7.5 and a classification tree was constructed using R weka software. The validity of the classification tree was then challenged with a blind test.

RESULTS

The software identified 102 peaks and m/z 14022.9 and m/z 3735.99 was used to construct a classification tree. The classification tree effectively separated adenocarcinoma of lung patients from healthy controls, achieving a validity of 100%. The blind test challenged the model with a sensitivity of 100% and a specificity of 100%.

CONCLUSION

The results suggested that the SELDI-TOF-MS technique can correctly distinguish adenocarcinoma of lung patients from healthy controls and showed great potential for development as a screening test for the detection of lung cancer.

Proteomic biomarkers associated with Streptococcus agalactiae invasive genogroups

Group B streptococcus (GBS, Streptococcus agalactiae) is a leading cause of meningitis and sepsis in newborns and an etiological agent of meningitis, endocarditis, osteoarticular and soft tissue infections in adults. GBS isolates are routinely clustered in serotypes and in genotypes. At present one GBS sequence type (i.e. ST17) is considered to be closely associated with bacterial invasiveness and novel proteomic biomarkers could make a valuable contribution to currently available GBS typing data. For that purpose we analyzed the protein profiles of 170 genotyped GBS isolates by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI). Univariate statistical analysis of the SELDI profiles identified four protein biomarkers significantly discriminating ST17 isolates from those of the other sequence types. Two of these biomarkers (MW of 7878 Da and 12200 Da) were overexpressed and the other two (MW of 6258 Da and 10463 Da) were underexpressed in ST17. The four proteins were isolated by mass spectrometry-assisted purification and their tryptic peptides analyzed by LC-MS/MS. They were thereby identified as the small subunit of exodeoxyribonuclease VII, the 50S ribosomal protein L7/L12, a CsbD-like protein and thioredoxin, respectively. In conclusion, we identified four candidate biomarkers of ST17 by SELDI for high-throughput screening. These markers may serve as a basis for further studies on the pathophysiology of GBS infection, and for the development of novel vaccines.

New approaches to sepsis: molecular diagnostics and biomarkers

Sepsis is among the most common causes of death in hospitals. It arises from the host response to infection. Currently, diagnosis relies on nonspecific physiological criteria and culture-based pathogen detection. This results in diagnostic uncertainty, therapeutic delays, the mis- and overuse of antibiotics, and the failure to identify patients who might benefit from immunomodulatory therapies. There is a need for new sepsis biomarkers that can aid in therapeutic decision making and add information about screening, diagnosis, risk stratification, and monitoring of the response to therapy. The host response involves hundreds of mediators and single molecules, many of which have been proposed as biomarkers. It is, however, unlikely that one single biomarker is able to satisfy all the needs and expectations for sepsis research and management. Among biomarkers that are measurable by assays approved for clinical use, procalcitonin (PCT) has shown some usefulness as an infection marker and for antibiotic stewardship. Other possible new approaches consist of molecular strategies to improve pathogen detection and molecular diagnostics and prognostics based on transcriptomic, proteomic, or metabolic profiling. Novel approaches to sepsis promise to transform sepsis from a physiologic syndrome into a group of distinct biochemical disorders and help in the development of better diagnostic tools and effective adjunctive sepsis therapies.

Protein biomarkers of alcohol abuse

Alcohol abuse can lead to a number of health and social issues. Our current inability to accurately assess long-term drinking behaviors is an important obstacle to its diagnosis and treatment. Biomarkers for chronic alcohol consumption have made a number of important advances but have yet to become highly accurate and as accepted as objective tests for other diseases. Thus, there is a crucial need for the development of more sensitive and specific markers of alcohol abuse. Recent advancements in proteomic technologies have greatly increased the potential for alcohol abuse biomarker discovery. Here, the authors review established and novel protein biomarkers for long-term alcohol consumption and the proteomic technologies that have been used in their study.

Proteomic analysis reveals platelet factor 4 and beta-thromboglobulin as prognostic markers in severe acute respiratory syndrome

Previously, we reported that proteomic fingerprints were present in sera of patients with severe acute respiratory syndrome (SARS), and could separate patients into subgroups with different prognoses. In the present study, we examined the prognostic values of the SARS‐associated proteomic features by biostatistical analysis, and deciphered the identities of those with prognostic values. Data of 20 SARS‐associated serum proteomic features and ten serological variables from 38 SARS adult patients before treatment were subjected to multivariate logistic regression. Proteomic features of m/z 6634, m/z 7769, m/z 8635, and m/z 8865 were identified as independent prognostic markers. After purification by cation‐exchange chromatography and gel electrophoresis, proteomic features of m/z 7769 and m/z 8865 were found to be platelet factor 4 (PF4) and beta‐thromboglobulin (beta‐TG) by tandem mass spectrometry, respectively. The associations of decreased serum PF4 and increased serum beta‐TG levels with poor prognosis were confirmed by Western blot. Previous studies suggest that PF4 and beta‐TG are involved in the pathogenesis of acute respiratory distress syndrome (ARDS) in a negative and positive way, respectively. Our results suggest that PF4 and beta‐TG may also play similar roles in the development of ARDS in SARS patients.

SELDI-TOF-MS Serum Profiling Reveals Predictors of Cardiac MRI Changes in Marathon Runners

Purpose. To utilize proteomics to discover proteins associated with significant cardiac magnetic resonance imaging (MRI) changes in marathon runners. Methods. Serum from 25 runners was analyzed by surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Proteomic profiles were compared in serum samples obtained prior to the race, at the finish line and within 7 hours after race to identify dynamic proteins correlated with cardiac MRI changes. Results. 693 protein/peptide clusters were identified using two ProteinChip surface chemistries and, of these, 116 were significantly different between the three time points. We identified 7 different patterns of protein expression change within the runners and 5 prerace protein peaks, 16 finish-line protein levels, and 15 postrace proteins which were correlated with significant postrace cardiac MRI changes. Conclusions. This study has identified baseline levels of proteins which may be predictive of risk of significant cardiac damage following a marathon race. Preliminary identification of the significant proteins suggested the involvement of cytokines and other proteins involved in stress and inflammatory response.

Diagnosis of colorectal cancer by MALDI-TOF-MS combined with WCX magnetic beads

AIM: To explore the difference in serum proteomic spectra between patients with colorectal cancer and healthy individuals, and to identify the specific protein biomarkers.

METHODS: Serum samples collected from 67 colorectal cancer patients and 66 healthy individuals were randomized into model construction group and validation group. Magnetic beads-based weak cation exchange (MB-WCX) kit and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) were used to profile serum proteome. Flex analysis software was used to analyze protein peaks for significant difference. A diagnostic model was then built using ClinproTools2.2software and evaluated blindly for reliability.

RESULTS: Thirty-three differentially expressed proteins in serum were screened between colorectal cancer patients and healthy individuals, including 25 up-regulated proteins and 8 down-regulated ones. Five proteins (759, 3316, 4645, 4248, and 2645 Dr) were used for building a ClinProt model which was able to classify colorectal cancer patients and healthy individuals with a sensitivity of 94.12% (32/34) and a specificity of 96.97% (32/33). A double blind validation test showed that the ClinProt model yielded a sensitivity of 93.94 (31/33) and a specificity of 96.97% (32/33).

CONCLUSION: Combination of MALDI-TOF-MS with WCX kit allows to directly screen proteins differentially expressed in the serum of patients with colorectal cancer, and these proteins can be used to diagnose early-stage colorectal cancer.

Proteomics analysis of plasma for early diagnosis of endometriosis

OBJECTIVE

To test the hypothesis that differential surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein or peptide expression in plasma can be used in infertile women with or without pelvic pain to predict the presence of laparoscopically and histologically confirmed endometriosis, especially in the subpopulation with a normal preoperative gynecologic ultrasound examination.

METHODS

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis was performed on 254 plasma samples obtained from 89 women without endometriosis and 165 women with endometriosis (histologically confirmed) undergoing laparoscopies for infertility with or without pelvic pain. Data were analyzed using least squares support vector machines and were divided randomly (100 times) into a training data set (70%) and a test data set (30%).

RESULTS

Minimal-to-mild endometriosis was best predicted (sensitivity 75%, 95% confidence interval [CI] 63-89; specificity 86%, 95% CI 71-94; positive predictive value 83.6%, negative predictive value 78.3%) using a model based on five peptide and protein peaks (range 4.898-14.698 m/z) in menstrual phase samples. Moderate-to-severe endometriosis was best predicted (sensitivity 98%, 95% CI 84-100; specificity 81%, 95% CI 67-92; positive predictive value 74.4%, negative predictive value 98.6%) using a model based on five other peptide and protein peaks (range 2.189-7.457 m/z) in luteal phase samples. The peak with the highest intensity (2.189 m/z) was identified as a fibrinogen β-chain peptide. Ultrasonography-negative endometriosis was best predicted (sensitivity 88%, 95% CI 73-100; specificity 84%, 95% CI 71-96) using a model based on five peptide peaks (range 2.058-42.065 m/z) in menstrual phase samples.

CONCLUSION

A noninvasive test using proteomic analysis of plasma samples obtained during the menstrual phase enabled the diagnosis of endometriosis undetectable by ultrasonography with high sensitivity and specificity.

LEVEL OF EVIDENCE

II.

Screening and identification of serum proteomic biomarkers for gastric adenocarcinoma

The aim of the present study was to screen for possible serum biomarkers for gastric adenocarcinoma. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) was used to screen serum samples from 109 cases of gastric adenocarcinoma and 106 control subjects (60 healthy subjects, 30 patients with chronic superficial gastritis and 16 cases of chronic atrophic gastritis). The differentially expressed protein peaks were selected and isolated using high performance liquid chromatography (HPLC) and processed with enzyme prior to liquid chromatography-mass spectrometry tandem mass spectrometry (LC-MS/MS) analysis and data mining with software XCalibur program components BioWorks 3.2. Among the gastric cancer cases, three differentially expressed protein peaks were selected as potential serum biomarkers: the m/z peaks at 5,906.5 showed increased expression (8.53±4.33 in the cancer group, and 0.88±0.31 in the control group); the m/z peaks at 6,635.7 and 8,716.3 showed decreased expression (6.54±2.44 and 0.93±0.29, respectively, in the cancer group and 17.56±4.43 and 2.16±0.98, respectively, in the control group) (P<0.01). The m/z peaks at 5,906.5, 6,635.7 and 8,716.3, were identified as fibrinogen α-chain, apolipo-protein A-II and apolipoprotein C-I. The combined use of the three biomarkers distinguished the cancer group patients from the control group samples at a sensitivity of 93.85% (61/65) and a specificity of 94.34% (50/53). In conclusion, fibrinogen α-chain, apolipoprotein A-II and apolipoprotein C-I were identified as potential markers for gastric cancer and appear to have diagnostic value for clinical applications.

Combined mRNA microarray and proteomic analysis of eutopic endometrium of women with and without endometriosis

BACKGROUND

An early semi-invasive diagnosis of endometriosis has the potential to allow early treatment and minimize disease progression but no such test is available at present. Our aim was to perform a combined mRNA microarray and proteomic analysis on the same eutopic endometrium sample obtained from patients with and without endometriosis.

METHODS

mRNA and protein fractions were extracted from 49 endometrial biopsies obtained from women with laparoscopically proven presence (n= 31) or absence (n= 18) of endometriosis during the early luteal (n= 27) or menstrual phase (n= 22) and analyzed using microarray and proteomic surface enhanced laser desorption ionization-time of flight mass spectrometry, respectively. Proteomic data were analyzed using a least squares-support vector machines (LS-SVM) model built on 70% (training set) and 30% of the samples (test set).

RESULTS

mRNA analysis of eutopic endometrium did not show any differentially expressed genes in women with endometriosis when compared with controls, regardless of endometriosis stage or cycle phase. mRNA was differentially expressed (P< 0.05) in women with (925 genes) and without endometriosis (1087 genes) during the menstrual phase when compared with the early luteal phase. Proteomic analysis based on five peptide peaks [2072 mass/charge (m/z); 2973 m/z; 3623 m/z; 3680 m/z and 21133 m/z] using an LS-SVM model applied on the luteal phase endometrium training set allowed the diagnosis of endometriosis (sensitivity, 91; 95% confidence interval (CI): 74-98; specificity, 80; 95% CI: 66-97 and positive predictive value, 87.9%; negative predictive value, 84.8%) in the test set.

CONCLUSION

mRNA expression of eutopic endometrium was comparable in women with and without endometriosis but different in menstrual endometrium when compared with luteal endometrium in women with endometriosis. Proteomic analysis of luteal phase endometrium allowed the diagnosis of endometriosis with high sensitivity and specificity in training and test sets. A potential limitation of our study is the fact that our control group included women with a normal pelvis as well as women with concurrent pelvic disease (e.g. fibroids, benign ovarian cysts, hydrosalpinges), which may have contributed to the comparable mRNA expression profile in the eutopic endometrium of women with endometriosis and controls.

Identification of CXCL5/ENA-78 as a factor involved in the interaction between cholangiocarcinoma cells and cancer-associated fibroblasts

Knowledge of tumor-stromal interactions is essential for understanding tumor development. We focused on the interaction between cholangiocarcinoma and cancer-associated fibroblasts (CAFs) in intrahepatic cholangiocarcinoma and reported their positive interaction in vitro and in vivo. The aim of this study is to identify the key protein involved in the interaction between cholangiocarcinoma cells and CAFs and its role on cholangiocarcinoma progression. Using the conditioning medium from cholangiocarcinoma cells, hepatic stellate cells and coculture of them, Protein-Chip analysis with SELDI-TOF-MS showed that the peak of an 8,360-Da protein remarkably increased in the coculture medium. This protein was identified as CXCL5/ENA78, epithelial cell-derived neutrophil-activating peptide-78, by q-TOF/MS/MS analysis. Two cholangiocarcinoma cell lines, HuCCT1 and RBE, produced CXCL5 that promoted their invasion and migration in an autocrine fashion. These effects of CXCL5 significantly decreased by inhibition of CXC-receptor 2, which is the receptor for CXCL5. In addition, IL-1β produced by hepatic stellate cells induced the expression of CXCL5 in cholangiocarcinoma cells. In human tissue samples, a significant correlation was observed between CAFs and CXCL5 produced by cholangiocarcinoma cells in intrahepatic cholangiocarcinoma (p = 0.0044). Furthermore, the high-CXCL5-expression group exhibited poor overall survival after curative hepatic resection (p = 0.027). The presence of tumor-infiltrating neutrophils expressing CD66b was associated with CXCL5 expression in tumor cells (p < 0.0001). These data suggest that CXCL5 is important for the interaction between cholangiocarcinoma and CAFs, and inhibition of tumor-stromal interactions may be a useful therapeutic approach for cholangiocarcinoma.

Reproducibility and concordance of differential DNA methylation and gene expression in cancer

Background

Hundreds of genes with differential DNA methylation of promoters have been identified for various cancers. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed.

Methodology/Principal Findings

Using array data for seven types of cancers, we first evaluated the effects of experimental batches on differential DNA methylation detection. Second, we compared the directions of DNA methylation changes detected from different datasets for the same cancer. Third, we evaluated the concordance between methylation and gene expression changes. Finally, we compared DNA methylation changes in different cancers. For a given cancer, the directions of methylation and expression changes detected from different datasets, excluding potential batch effects, were highly consistent. In different cancers, DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression, whereas hypomethylation was only weakly correlated with the up-regulation of genes. Finally, we found that genes commonly hypomethylated in different cancers primarily performed functions associated with chronic inflammation, such as ‘keratinization’, ‘chemotaxis’ and ‘immune response’.

Conclusions

Batch effects could greatly affect the discovery of DNA methylation biomarkers. For a particular cancer, both differential DNA methylation and gene expression can be reproducibly detected from different studies with no batch effects. While DNA hypermethylation is significantly linked to gene down-regulation, hypomethylation is only weakly correlated with gene up-regulation and is likely to be linked to chronic inflammation.

An estrogen-responsive plasma protein expression signature in Atlantic cod (Gadus morhua) revealed by SELDI-TOF MS

Compound-specific protein expression signatures (PESs) can be revealed by proteomic techniques. The SELDI-TOF MS approach is advantageous due to its simplicity and high-throughput capacity, however, there are concerns regarding the reproducibility of this method. The aim of this study was to define an estrogen-responsive PES in plasma of Atlantic cod (Gadus morhua) using the SELDI-TOF MS technique. Protein expression analysis of male cod exposed to 17β-estradiol (E₂) showed that 27 plasma peaks were differentially expressed following exposure. The reproducibility of this result was evaluated by reanalyzing the samples six months later, and a significant change in expression was confirmed for 13 of the 27 peaks detected in the first analysis. The performance of the reproducible E₂-responsive PES, constituting these 13 peaks, was then tested on samples from juvenile cod exposed to 4-nonylphenol, North Sea oil, or North Sea oil spiked with alkylphenols. Principal component analysis revealed that nonylphenol-exposed cod could be separated from unexposed cod based on the E₂-responsive PES, indicating that the PES can be used to assess estrogenic exposure of both juvenile and adult specimens of cod. A targeted antibody-assisted SELDI-TOF MS approach was carried out in an attempt to identify the E₂-responsive peaks. Results indicated that 2 peaks were fragments of the well-known biomarkers VTG and/or ZRP. In this study, the SELDI-TOF MS technology has shown its potential for defining compound-specific PESs in fish. Nevertheless, thorough validation of reproducibility, specificity and sensitivity of a PES is required before it can be applied in environmental monitoring.

Urinary exosomes and proteomics

A number of highly abundant proteins in urine have been identified through proteomics approaches, and some have been considered as disease-biomarker candidates. These molecules might be clinically useful in diagnosis of various diseases. However, none has proven to be specifically indicative of perturbations of cellular processes in cells associated with urogenital diseases. Exosomes could be released into urine which flows through the kidney, ureter, bladder and urethra, with a process of filtration and reabsorption. Urinary exosomes have been recently suggested as alternative materials that offer new opportunities to identify useful biomarkers, because these exosomes secreted from epithelial cells lining the urinary track might reflect the cellular processes associated with the pathogenesis of diseases in their donor cells. Proteomic analysis of such urinary exosomes assists the search of urinary biomarkers reflecting pathogenesis of various diseases and also helps understanding the function of urinary exosomes in urinary systems. Thus, it has been recently suggested that urinary exosomes are one of the most valuable targets for biomarker development and to understand pathophysiology of relevant diseases.