Surface-enhanced Laser Desorption/ionization Time-of-flight Mass Spectrometry Research Articles

Saliva analysis by Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (SELDI-TOF-MS) in orthodontic treatment: first pilot study

Objective SELDI-TOF-MS (Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry) allows the generation of an accurate protein profile from minimal amounts of biological samples and may executes proteomic profile of saliva. The aim of this work is to compare the proteomic profile of saliva of patients in orthodontic treatment to the beginning of treatment and after three months by using the surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. Materials and methods Saliva was collected from 14 patients, between the 11 and 17 years, to the beginning of the orthodontic treatment and after three months. Specimens were centrifuged (10 min, 13000 x g); the Q10 ProteinChips were prepared according to the manufacturer's instructions and were loaded with the supernatants. A saturated solution of sinapinic acid was used as energy-absorbing matrix. The analysis was performed in a m/ z range from 2500 to 25000 Da, and the proteomic profiles were compared by a specific data analysis software. Saliva (5 mL) was collected by spitting directly into a clean 15 mL conical tube. The samples were then aliquotted and stored at –80 °C until use. Results Profile of saliva of patients before orthodontic treatment present a number of peaks different respect profile of saliva after three months of treatment. The average intensities of peaks at m/z 3372, 5232, 4045 and 10128 were significantly higher after three months then at beginning of treatment in the same patients and among these one. The Roc Plot has demonstrated high sensitivity and specificity. Conclusions Many differences were noted in salivary proteomic profile obtained using the SELDI-TOF-MS technology in patients in orthodontic treatment to beginning and after three months. These data suggest that the proteomic analysis of saliva is a promising new tool for a non-invasive study of oral mucosa and bone changes.

Identification of β2‐microglobulin as a urinary biomarker for chronic allograft nephropathy using proteomic methods

Chronic allograft nephropathy (CAN) remains the leading cause of renal graft loss after the first year following renal transplantation. This study aimed to identify novel urinary proteomic profiles, which could distinguish and predict CAN in susceptible individuals. The study included 34 renal transplant patients with histologically proven CAN and 36 patients with normal renal transplant function. High-throughput proteomic profiles were generated from urine samples with three different ProteinChip arrays by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Following SELDI, a biomarker pattern software analysis was performed which led to the identification of a novel biomarker pattern that could distinguish patients with CAN from those with normal renal function. An 11.7 kDa protein identified as β2 microglobulin was the primary protein of this biomarker pattern, distinguishing CAN from control patients (receiver operator characteristic [ROC]=0.996). SELDI-TOF-MS comparison of purified β2 microglobulin protein and CAN urine demonstrated identical 11.7 kDa protein peaks. Significantly, higher concentrations of 2 microglobulin were found in the urine of patients with CAN compared with the urine of normal renal function transplant recipients (p<0.001). Although further validation in a larger more diverse patient population is required to determine if this β2 microglobulin protein biomarker will provide a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly shows a capability to stratify control and disease patients.

Proteomic analysis of resectable non-small cell lung cancer: post-resection serum samples may be useful in identifying potential markers

Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) can be used to analyse peptides and proteins in clinical samples. A prospective study was undertaken on patients undergoing curative resection for non-small cell lung cancer (NSCLC): we used SELDI-TOF-MS to compare the proteomic profiles of serum from these patients both before surgical resection and after resection (disease-free) to identify potential biomarkers. Student t-tests were used, and a P-value of <0.01 was considered significant. Twenty-five patients with NSCLC [76% male, mean age 69 (range 53-81) years] were analysed. There were 13 squamous cell carcinomas, 10 adenocarcinomas and 2 large cell carcinomas with a stage distribution of four stage IA, 11 stage IB, five stage IIB, three stage IIIA, one stage IIIB and one stage IV. SELDI spectra generated with immobilised metal affinity chromatography arrays produced 170 peaks. Of these, 35 showed significant differences in their intensities between the preoperative and post-resection states (P<0.01). Postoperative samples in the disease-free state may represent good controls to identify biomarkers in NSCLC, avoiding the difficulties associated with cross-sectional studies. These pilot data need to be validated with larger numbers of patients.

A pilot investigation on serum protein fingerprinting of nasopharyngeal carcinoma

To establish a preliminary foundation for developing a serum proteomics diagnostic model of nasopharyngeal carcinoma (NPC) by comparing the differences in serum protein fingerprints between patients with NPC and healthy subjects and between different types of NPC. The serum samples of 41 patients with different types of NPC and 20 healthy subjects were collected. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) were used to detect the blood samples to obtain serum protein mass spectrum, i.e. serum protein fingerprinting. Biomarker Wizard and Biomarker Patterns system software were used to compare the differences in serum protein mass spectrum between NPC patients and healthy subjects and between different types of NPC, and to screen out the NPC-related serum proteins. Compared with the healthy control, NPC patients emerged 9 very prominent protein peaks (P < 0.001), with the combined differential peaks. No significant difference was found in relative amount of serum proteins with different molecular mass between different types of NPC (P > 0.05). The serum marker proteins and specific protein fingerprints of NPC can be screened out by SELDI-TOF-MS, which could be used to develop a serum proteomics model for clinical screening and early diagnosis of NPC.

Surface-enhanced laser desorption ionization/time-of-flight (SELDI-TOF) mass spectrometry (MS) as a phenotypic method for rapid identification of antibiotic resistance

Based on experiments with 10 defined strains of Escherichia coli, we present a new method for bacterial phenotyping using SELDI-TOF mass spectrometry. Changes in bacterial protein profiles in the context of the time of cultivation and the antibiotic environment were minimal. Proteom subprofiling may further distinguish between strains with specific susceptibility to antimicrobials. Mass spec-based methods may become common in the future of bacterial pathogen identification in clinical microbiology diagnostics.

Transthyretin-down-regulation in sera of cholangiocarcinoma

Objective As SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry) has been broadly used to screen biomarkers for a variety of diseases, the identification and validation of the revealed biomarkers requires more focused attention.Method In this paper, the serum samples from 60 cholangiocarcinoma, 146 lung cancer, 65 LGC and 58 LPC, 49 benign diseases of hepatobiliary and 53 normal individuals were analyzed by SELDI-TOF-MS. Results Among a set of proteins automatically selected as specific biomarkers by Biomarker Wizard software, three protein peaks, with molecular weights of 13. 71 × 103 , 13.83 × 103 and 13. 99 ×103 , were found significantly decreased in cholangiocarcinoma samples. The candidate biomarkers obtained from Tricine-SDS-PAGE gel bands by matching the molecular weight with peaks on CM10 chips were identified by Mass spectrometry as the native transthyretin(native TTR),cysTTR and glutTTR.These preliminary results were further proven by immunoprecipitation using commercial TTR antibodies. This allowed us to re-measure the TTR levels in all the groups more simply by ELISA assay. It showed a firm consistency between ELISA and SELDI analysis. In addition, while TTR levels in cholangiocarcinoma were found to be lower than those in normal healthy controls, TTR levels in benign diseases of the hepatobiliary system were found to be higher than those in healthy controls.Conclusion TTR could be a biomarker that better discriminates cholangiocarcinoma patients from the benign diseases compared to other biomarkers presently available. Key words: Cholangiocarcinoma; Transthyretin(TTR); Serum biomarkers; SELDI-TOF-MS

Application of protein expression profiling to screen chemicals for androgenic activity

Protein expression changes can be used for detection of biomarkers that can be applied diagnostically to screen chemicals for endocrine modifying activity. In this study, surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) coupled with a short term fish assay was used to investigate changes in plasma protein expression as a means to screen chemicals for androgenic activity. Adult gravid female sheepshead minnows ( Cyprinodon variegatus) were placed into separate aquaria for seawater control, ethanol solvent control, and the following androgen agonist treatments at 5.0 μg/L: dihydrotestosterone (DHT), methyldihydrotestosterone (MDHT), testosterone (T), methyltestosterone (MT) and trenbolone (TB). Treatments of 0.6 μg/L endosulfan and 40 μg/L chlorpyrifos (CP) served as non-androgenic negative stressor controls. Test concentrations were maintained using an intermittent flow-through dosing apparatus supplying exposure water at 20 L/h. Fish were sampled at 7 days, the plasma diluted, processed on weak cation exchange CM10 ProteinChip arrays and analyzed. Spectral processing resulted in 249 individual m/ z peak clusters for the androgen exposed fish. Partial least squares-discriminant analysis was used to develop an androgen-responsive model using sample spectra from exposures with DHT and unexposed solvent control fish as the training set. The androgen classification model performed with ≥79% specificity (% true negative) and ≥70% sensitivity (% true positive) for non-aromatizable androgens. The aromatizable androgens T and MT were classified as androgenic with specificities of 42 and 79%, respectively. The reduction in sensitivity observed with T is thought to be caused by its metabolic conversion to an estrogen by aromatase. The results of these studies show diagnostic plasma protein expression models can correctly classify chemicals by their androgenic activity using a combination of high throughput mass spectrometry and multivariate approaches.

Analysis of the mitochondrial proteome in multiple sclerosis cortex

Mitochondrial dysfunction has been proposed to play a role in the neuropathology of multiple sclerosis (MS). Previously, we reported significant alterations in the transcription of nuclear-encoded electron transport chain genes in MS and confirmed translational alterations for components of Complexes I and III that resulted in reductions in their activity. To more thoroughly and efficiently elucidate potential alterations in the expression of mitochondrial and related proteins, we have characterized the mitochondrial proteome in postmortem MS and control cortex using Surface-Enhanced Laser Desorption Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS). Using principal component analysis (PCA) and hierarchical clustering techniques we were able to analyze the differential patterns of SELDI-TOF spectra to reveal clusters of peaks which distinguished MS from control samples. Four proteins in particular were responsible for distinguishing disease from control. Peptide fingerprint mapping unambiguously identified these differentially expressed proteins. Three proteins identified are involved in respiration including cytochrome c oxidase subunit 5b (COX5b), the brain specific isozyme of creatine kinase, and hemoglobin β-chain. The fourth protein identified was myelin basic protein (MBP). We then investigated whether these alterations were consistent in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. We found that MBP was similarly altered in EAE but the respiratory proteins were not. These data indicate that while the EAE mouse model may mimic aspects of MS neuropathology which result from inflammatory demyelinating events, there is another distinct mechanism involved in mitochondrial dysfunction in gray matter in MS which is not modeled in EAE.

Application of serum proteomic patterns for the detection of esophageal carcinoma in Kazakh in Xinjiang

To detect the serum protein profiles of Kazakh's esophageal carcinoma (EC) patients in Xinjiang by SELDI-TOF-MS (surface enhanced laser desorption & ionization time-of-flight mass spectrometry) and build up a diagnostic model of Kazakh's EC in Xinjiang. The serum samples from 41 Kazakh's EC patients and 20 Kazakh's healthy controls were collected and analyzed on weak cation exchange and hydrophobic surface protein chip by SELDI-TOF-MS technology. The differentially expressed markers of esophageal carcinoma were detected. The values of M/Zs were significantly different between Kazakh's EC patients and controls (P < 0.05). Among these, 6 proteins peaks were up-regulated (5495.2265, 15 964.6951, 16 152.0872, 4488.4818, 8164.7652, 4979.4223) and 4 down-regulated (6900.3285, 13 790.9241, 8790.8130, 8714.7915) in the Kazakh's EC group. According to cross validation, the model of Kazakh's EC made up of 7 proteins (M/Z 6900.3285, 13 790.9241, 8790.8130, 15 964.6951, 16 152.0872, 4488.4818, 4979.4223) was established. The sensitivity and specificity of this model were 100% (41/41) and 100% (20/20) respectively. The model with 7 proteins markers has a higher sensitivity and specificity for Kazakh's EC patients in Xinjiang. It may provide a new serum diagnostic tool for Kazakh's EC patients in Xinjiang.

Analysis of urinary proteomic patterns for type 2 diabetic nephropathy by ProteinChip

Objective To detect urinary proteomic profiling of patients with type 2 diabetes by using ProteinChip array technology, for searching new potential biomarkers in early diagnosis of type 2 diabetic nephropathy (T2DN). Methods A total of 95 urine samples from type 2 diabetic patients with normoalbuminuria (DM, n = 30), microalbuminuria (DNl, n = 25) and macroalbuminuria (DN2, n = 20), and healthy controls ( n = 20) were analyzed by SELDI-TOF-MS (the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry) technology combined with bioinformatics tools. Results Over 300 proteins or peptides from 1 to 80 kDa were obtained using ProteinChip. About 40 of them with the m/ z values from 2008.78 to 79176.55 Da were significantly differentiated between type 2 diabetic patients and control subjects. Four proteins of mass 2797.03, 4545.77, 4984.03 and 9083.71 Da were selected as the potential biomarkers for T2DN with sensitivity of 88% and specificity of 96.7%. Conclusion ProteinChip technology can help to discover new biomarkers and provide a novel non-invasive tool to early diagnosis of T2DN.

Identification of proteomic signatures of mantle cell lymphoma, small lymphocytic lymphoma, and marginal zone lymphoma biopsies by surface enhanced laser desorption/ionization-time of flight mass spectrometry

Mantle cell lymphoma (MCL), small lymphocytic lymphoma (SLL), and marginal zone lymphoma (MZL) are small B-cell non-Hodgkin lymphomas (NHLs) that may be difficult to distinguish. In order to identify specific proteomic biomarkers, differential proteomic analysis of these three NHLs was performed using surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). Whole cell lysates obtained from 18 MCL, 20 SLL, and 20 MZL biopsies were applied on two different ProteinChips (cationic and anionic). Hierarchical clustering and discriminating scores combined with an innovative bio-informatics microdissection strategy allowed us to distinguish specific lymphoma proteomic signatures based on the expression of 37 protein peaks. SELDI-assisted protein purification combined with nano-liquid chromatography (LC) quadrupole-time of flight tandem mass spectrometry (Q-TOF MS/MS) was used to identify proteins overexpressed in both MCL and SLL tumors. Among them two histones, H2B and H4, were identified in MCL tumor biopsies and the signal recognition particle 9 kDa protein, SRP9, in SLL tumor biopsies.

Enriched sera protein profiling for detection of non-small cell lung cancer biomarkers

BackgroundNon Small Cell Lung Cancer (NSCLC) is the major cause of cancer related-death. Many patients receive diagnosis at advanced stage leading to a poor prognosis. At present, no satisfactory screening tests are available in clinical practice and the discovery and validation of new biomarkers is mandatory. Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-ToF-MS) is a recent high-throughput technique used to detect new tumour markers. In this study we performed SELDI-ToF-MS analysis on serum samples treated with the ProteoMiner™ kit, a combinatorial library of hexapeptide ligands coupled to beads, to reduce the wide dynamic range of protein concentration in the sample. Serum from 44 NSCLC patients and 19 healthy controls were analyzed with IMAC30-Cu and H50 ProteinChip Arrays.ResultsComparing SELDI-ToF-MS protein profiles of NSCLC patients and healthy controls, 28 protein peaks were found significantly different (p < 0.05), and were used as predictors to build decision classification trees. This statistical analysis selected 10 protein peaks in the low-mass range (2-24 kDa) and 6 in the high-mass range (40-80 kDa). The classification models for the low-mass range had a sensitivity and specificity of 70.45% (31/44) and 68.42% (13/19) for IMAC30-Cu, and 72.73% (32/44) and 73.68% (14/19) for H50 ProteinChip Arrays.ConclusionsThese preliminary results suggest that SELDI-ToF-MS protein profiling of serum samples pretreated with ProteoMiner™ can improve the discovery of protein peaks differentially expressed between NSCLC patients and healthy subjects, useful to build classification algorithms with high sensitivity and specificity. However, identification of the significantly different protein peaks needs further study in order to provide a better understanding of the biological nature of these potential biomarkers and their role in the underlying disease process.

Characterization of discriminatory urinary proteomic biomarkers for severe preeclampsia using SELDI-TOF mass spectrometry

To analyze the proteomic pattern in urine for distinguishing severe preeclampsia from mild preeclampsia and normotensive controls using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Urine samples were collected from women with severe preeclampsia (n=11 [sPE]), mild preeclampsia (n=7 [mPE]), and normotensive controls (n=8) and analyzed by SELDI-TOF-MS to identify discriminatory protein peaks in the sPE cohort. A scoring system was constructed--designated as Preeclampsia Proteomic Score of Urine (PPSU)--to differentiate sPE from mPE and normotensive controls. Four discriminatory protein peaks were identified (m/z ratio: 4155, 6044, 6663, and 7971), all of which were down-regulated in women with sPE. PPSU scores in women with sPE were significantly lower than that in both mPE and controls (sPE 0 [0-4] vs. mPE 3 [0-4] vs. controls 4 [2-4]; median [range]; P<0.05). PPSU<2 had a sensitivity of 90.9% and specificity of 93.3% in discriminating patients with sPE from mPE and controls. Proteomic analysis of urine can accurately distinguish sPE from mPE and normotensive controls.

Identification of Regional Lymph Node Involvement of Colorectal Cancer by Serum SELDI Proteomic Patterns

Background. To explore the application of serum proteomic patterns for the preoperative detection of regional lymph node involvement of colorectal cancer (CRC). Methods. Serum samples were applied to immobilized metal affinity capture ProteinChip to generate mass spectra by Surface-Enhanced Laser Desorption/ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Proteomic spectra of serum samples from 70 node-positive CRC patients and 75 age- and gender-matched node-negative CRC patients were employed as a training set, and a classification tree was generated by using Biomarker Pattern Software package. The validity of the classification tree was then challenged with a blind test set including another 65 CRC patients. Results. The software identified an average of 46 mass peaks/spectrum and 5 of the identified peaks at m/z 3,104, 3,781, 5,867, 7,970, and 9,290 were used to construct the classification tree. The classification tree separated effectively node-positive CRC patients from node-negative CRC patients, achieving a sensitivity of 94.29% and a specificity of 100.00%. The blind test challenged the model independently with a sensitivity of 91.43% a specificity of 96.67%. Conclusions. The results indicate that SELDI-TOF-MS can correctly distinguish node-positive CRC patients from node-negative ones and show great potential for preoperative screening for regional lymph node involvement of CRC.

Self-calibrated warping for mass spectra alignment.

With recent advances in mass spectrometry (MS) technologies, it is now possible to study protein profiles over a wide range of molecular weights in small biological specimens. However, MS spectra are usually not aligned or synchronized between samples. To ensure the consistency of the subsequent analysis, spectrum alignment is necessary to align the spectra such that the same biological entity would show up at the same m/z value for different samples. Although a variety of alignment algorithms have been proposed in the past, most of them are developed based on chromatographic data and do not address some of the unique characteristics of the serum or other body fluid MS data. In this work, we propose a self-calibrated warping (SCW) algorithm to address some of the challenges associated with serum MS data alignment. In addition, we compare the proposed algorithm with five existing representative alignment methods using a clinical surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) data set.

793: Characterization of discriminatory urinary proteomic biomarkers for severe preeclampsia using seldi-TOF mass spectrometry

To identify and characterize novel urinary biomarkers that are differentially expressed in women with severe preeclampsia using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

Mass spectrometry measurement of plasma hepcidin for the prediction of iron overload

Hepcidin has emerged as the primary regulator of iron homeostasis. Previous studies on assessing urinary hepcidin are limited. We developed a method for quantifying hepcidin-25 (Hep-25) in plasma using surface-enhanced laser-desorption-ionization time-of-flight mass spectrometry (SELDI-TOF/MS) and a 25-AA peptide as reference standard. The aims of the study were 1) to assess the performance of this method in different conditions of iron metabolism disorders; 2) to assess the diagnostic validity of non-invasive serum biomarkers in the identification of iron overload. Validation of the method was performed in 10 patients with type I hemochromatosis (HE) and in 177 subjects previously enrolled in a general population epidemiological study. Among the latter group, 17 had non-alcoholic fatty liver disease, 10 had chronic hepatitis C, and 150 subjects had normal ultrasound, normal liver function tests (LFTs), an alcohol intake < 20 g ethanol/day and were negative for the C282Y mutation. The following biomarkers were assayed in each case: plasma Hep-25, C282Y and H63D mutations of the HFE gene; serum iron, ferritin (SF), transferrin saturation, transaminases, γ-glutamyltransferase (GGT), glucose, insulin, total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides. Plasma Hep-25 concentrations were higher in HCV+ patients (26.3 ± 7.2 nmol/L) than in controls, and correlated positively with SF (p < 0.001). H63D heterozygous subjects revealed a pattern of iron overload that was significantly higher than H63D wild type subjects. Analyzing the data with the Biomarker Pattern 5.0.2. software to identify the most significant biomarkers for discriminating between HE cases and controls allowed us to produce an algorithm with four terminal nodes, which included glucose > 4.8 mmol/L and Hep-25/SF ratio ≤ 6.6 as the main splitters. These variables enabled the correct diagnosis of HE with 100% sensitivity, 93% specificity and an area under the receiver operating characteristic (ROC) curve of 0.993. Our plasma Hep-25 mass spectrometry method yields measurements that reflect pathological and genetic influences; simple non-invasive biomarkers (Hep-25/SF ratio and glucose) can predict the presence of HE.

Different protein profile in amniotic fluid with nervous system malformations by surface‐enhanced laser desorption‐ionization/time‐of‐flight mass spectrometry (SELDI‐TOF‐MS) technology

To detect the distinct proteins in amniotic fluid (AF) between nervous system malformations fetuses and normal fetuses. Surface-enhanced laser desorption-ionization/time-of-flight mass spectrometry was used to characterize AF peptides in AF between nervous system malformations fetuses and normal fetuses. WCX2 protein chips were used to characterize AF peptides in AF. Protein chips were examined in a PBSIIC protein reader, the protein profiling was collected by ProteinChip software version 3.1 (Ciphergen Biosystems, Fremont, CA, USA) and analyzed by Biomarker Wizard software (Ciphergen Biosystems). Nine distinct proteins were identified in AF between nervous system malformations fetuses and normal fetuses. Compared with the control group, three proteins with m/z 4967.5 Da, 5258.0 Da, and 11,717.0 Da were down-regulated, and six proteins with m/z 2540.4 Da, 3107.1 Da, 3396.8 Da, 4590.965 Da, 5589.2 Da and 6429.4 Da up-regulated in nervous system malformations fetuses. The results suggest that there are distinct proteins in protein profiling of AF between nervous system malformations fetuses and normal fetuses.

Identification of serum proteins involved in pancreatic cancer cachexia

AimsTreatment of cachexia requires pharmacological intervention which, in turn, requires knowledge of the mediators and processes. Cachexia markers that are specifically expressed in pancreatic cancer and secreted into the blood circulation have yet to be identified. The aim of our study was to investigate the serum protein profiles and protein alterations associated with cachexia and to identify potential disease protein biomarkers indicative for this syndrome. Main methodsSerum samples from cachectic and non-cachectic patients undergoing pancreatic cancer (PaCa) surgery and controls were investigated by Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). The identity of detected discriminatory markers was determined by a combination of protein fractionation, chromatographic purification steps, gel electrophoresis, and mass spectrometry. Key findingsUsing Cu-IMAC array and CM-10 array based SELDI-TOF-MS. we identified eleven up- and four down-regulated proteins associated with cachexia. CiphergenExpress analysis revealed four disease-associated protein features (38559Da, 9138Da, 8925Da and 3358Da) that were elevated by a factor of 2.3, 1.7, 1.4 and 1.4, respectively. Zinc-α2-glycoprotein (ZAG), apolipoproteins apo C-II and apo C-III and glucagon-like peptide-1 (GLP-1) were identified as markers for PaCa-associated cachexia syndrome. ZAG levels were additionally evaluated in serum and tissue samples by ELISA and immunohistochemistry and the obtained data confirmed the SELDI-TOF-MS results. SignificanceThe identified proteins could be routinely and reliably measured in the serum of patients and provide an elegant non-invasive approach for early diagnosis of cachectic pancreatic cancer patients. Controlling ZAG and GLP-1 activity could be beneficial in the management of cancers and cachexia-induced conditions.

Identification of novel biomarker candidates by proteomic analysis of cerebrospinal fluid from patients with moyamoya disease using SELDI-TOF-MS

BackgroundMoyamoya disease (MMD) is an uncommon cerebrovascular condition with unknown etiology characterized by slowly progressive stenosis or occlusion of the bilateral internal carotid arteries associated with an abnormal vascular network. MMD is a major cause of stroke, specifically in the younger population. Diagnosis is based on only radiological features as no other clinical data are available. The purpose of this study was to identify novel biomarker candidate proteins differentially expressed in the cerebrospinal fluid (CSF) of patients with MMD using proteomic analysis.MethodsFor detection of biomarkers, CSF samples were obtained from 20 patients with MMD and 12 control patients. Mass spectral data were generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) with an anion exchange chip in three different buffer conditions. After expression difference mapping was undertaken using the obtained protein profiles, a comparative analysis was performed.ResultsA statistically significant number of proteins (34) were recognized as single biomarker candidate proteins which were differentially detected in the CSF of patients with MMD, compared to the control patients (p < 0.05). All peak intensity profiles of the biomarker candidates underwent classification and regression tree (CART) analysis to produce prediction models. Two important biomarkers could successfully classify the patients with MMD and control patients.ConclusionsIn this study, several novel biomarker candidate proteins differentially expressed in the CSF of patients with MMD were identified by a recently developed proteomic approach. This is a pilot study of CSF proteomics for MMD using SELDI technology. These biomarker candidates have the potential to shed light on the underlying pathogenesis of MMD.