Ciphergen Biosystems Research Articles

Changes in the Matrix Markedly Enhance the Resolution and Accurate Identification of Human Pathogens by MALDI-TOF MS

The mass spectral profiles of three major/emerging Gram positive pathogens belonging to the genera Clostridium, Listeria and Propionibacterium were investigated using four MALDI-TOF (Matrix-Assisted Laser Desorption/ Ionization- Time of Flight) Mass Spectrometers from Waters, Shimadzu, Bruker and Ciphergen Biosystems. These instruments have been extensively used for developing a diagnostic platform for high throughput, low cost, near sample-free preparation for microbial identification. The results demonstrate the marked effect of spectral quality obtained by altering the matrix and the added value of simple preparative extraction procedures. While microbial spectral data are generally collected in the mass range 2 to 20 kDa for diagnostic signatures, most of the significant mass ions are <10 kDa. The change from the traditional use of CMBT (5-chloro-2-mercaptobenzothiazole) to DHB (2-(2, 5-DiHydroxyBenzoic acid) enabled successful identification of C. difficile whereas the substitution of CHCA (alpha-cyano-4-hydroxycinnamic acid) for DHB (2,5-dihydroxybenzoic acid) improved the identification of Listeria species. By contrast, the use of SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization- Time of Flight- Mass Spectrometry), which employs affinity pre-capture of specific classes of molecules and analysed using sinapinic acid, showed a fivefold extension of the mass range of analytes, extending the potential for biomarker discovery and higher resolution strain typing of P. acnes.

Urine screening by Seldi-Tof, followed by biomarker identification, in a Brazilian cohort of patients with Renal Cell Carcinoma (RCC)

To screen proteins/peptides in urine of Renal Cell Carcinoma (RCC) patients by SELDI-TOF (Surface Enhanced Laser Desorption Ionization - Time of Flight) in search of possible biomarkers. Sixty-one urines samples from Clear Cell RCC and Papillary RCC were compared to 29 samples of control urine on CM10 chip. Mass analysis was performed in a ProteinChip Reader PCS 4,000 (Ciphergen Biosystems, Fremont, CA) with the software Ciphergen Express 3.0. All chips were read at low and at high laser energy. For statistical analysis the urine samples were clustered according to the histological classification (Clear Cell and Papillary Carcinoma). For identification urine was loaded on a SDS PAGE gel and bands of most interest were excised, trypsinized and identified by MS/MS. Databank searches were performed in Swiss-Prot database using the MASCOT search algorithm and in Profound. Proteins that were identified from urine of controls included immunoglobulin light chains, albumin, secreted and transmembrane 1 precursor (protein K12), mannan-binding lectin-associated serine protease-2 (MASP-2) and vitelline membrane outer layer 1 isoform 1. Identification of immunoglobulins and isoforms of albumin are quite common by proteomics and therefore cannot be considered as possible molecular markers. K12 and MASP-2 play important physiological roles, while vitellite membrane outer layer 1 role is unknown since it was never purified in humans. The down expression of Protein K-12 and MASP-2 make them good candidates for RCC urine marker and should be validated in a bigger cohort including the other less common histological RCC subtypes.

Potential proteomic biomarkers in assessing liver fibrosis using SELDI-TOF MS

The accurate assessment of the severity of liver fibrosis is of paramount importance in determining treatment strategies, response to treatment and prognosis in patients with chronic liver disease. The aim of this study was to investigate potential proteomic biomarkers for assessing stages of hepatic fibrosis. Serum samples of 83 patients with chronic liver disease (using METAVIR index, 17 F0, 30 F1, 6 F2, 9 F3, and 21 F4 patients) and 29 healthy controls were analyzed using surface-enhanced laser desorption/ionization time-of- flight mass spectrometry on IMAC30 ProteinChip arrays. Discriminatory peaks between groups were identified using Mann-Whitney U non-parametric test. Comparison of mild (F0, F1) and severe fibrosis (F2, F3, F4) was performed using tree classification (cross-validation) with the Biomarker Patterns Software, version 5.0 (Ciphergen Biosystems, US). No statistically significant discriminatory peak was evident between F0, F1 and F2 fibrosis. More than 30 peaks were found to be discriminatory between patients with cirrhosis (F4) and all other stages of liver fibrosis, including F2 and F3. Six surface-enhanced laser desorption/ionization proteomic features were found to be discriminative for mild (F0, F1) vs. advanced (F2, F3, F4) fibrosis (AUROC ≥0.8, p<0.05, Mann-Whitney test). The decision tree (m/z 4280, 10453 and 6376) yielded a sensitivity of 83.3% (30/36), a specificity of 85.1% (40/47), a positive predictive value of 81.1%, and a negative predictive value of 86.9%, with an AUROC of 0.94. The results of this study revealed discriminatory peaks between the protein profiles of patients with cirrhosis and other stages of liver fibrosis. Potential proteomic biomarkers can be notably determined for discriminating mild and advanced fibrosis using surface-enhanced laser desorption/ionization time-of- flight mass spectrometry.

Effect of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on identifying biomarkers of laryngeal carcinoma.

The aim is to study the serum protein fingerprint of patients with laryngeal carcinoma (LC) and to screen for protein molecules closely related to LC during the onset and progression of the disease with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Serum samples from 68 patients with LC and 117 non-cancer control samples (75 healthy volunteers and 42 Vocal fold polyps). Q10 protein chips and PBSII-C protein chips reader (Ciphergen Biosystems Inc.) were used. The protein fingerprint expression of all the Serum samples and the resulting profiles between cancer and non-cancer groups were analyzed with Biomarker Wizard system. A group of proteomic peaks were detected. Three differently expressed potential biomarkers were identified with the relative molecular weights of 5,915, 6,440 and 9,190Da. Among the three peaks, the one with m/z 6,440 was down-regulated, and the other two peaks with m/z 5,915 and 9,190 were up-regulated in LC. This diagnostic model could distinguish LC patients from controls with a sensitivity of 92.1% and a specificity of 91.9%. Moreover, blind test data showed a sensitivity of 86.7% and a specificity of 89.1%. The data suggested that SELDI technology could be used to screen proteins with altered expression levels in the serum of LC patients. These protein peaks were considered as specific serum biomarkers of LC and have the potential value for further investigation.

MALDI-TOF MS Combined With Magnetic Beads for Detecting Serum Protein Biomarkers and Establishment of Boosting Decision Tree Model for Diagnosis of Colorectal Cancer

The aim of present study is to study the serum protein fingerprint of patients with colorectal cancer (CRC) and to screen protein molecules that are closely related to colorectal cancer during the onset and progression of the disease with Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Serum samples from 144 patients with CRC and 120 healthy volunteers were adopted in present study. Weak cation exchange (WCX) magnetic beads and PBSII-C protein chips reader (Ciphergen Biosystems Ins.) were used. The protein fingerprint expression of all the Serum samples and the resulted profiles between cancer and normal groups were analyzed with Biomarker Wizard system. Several proteomic peaks were detected and four potential biomarkers with different expression profiles were identified with their relative molecular weights of 2870.7 Da, 3084 Da, 9180.5 Da, and 13748.8 Da, respectively. Among the four proteins, two proteins with m/z 2870.7 and 3084 were down-regulated, and the other two with m/z 9180.5 and 13748.8 were up-regulated in serum samples from CRC patients. The present diagnostic model could distinguish CRC from healthy controls with the sensitivity of 92.85% and the specificity of 91.25%. Blind test data indicated a sensitivity of 86.95% and a specificity of 85%. The result suggested that MALDI technology could be used to screen critical proteins with differential expression in the serum of CRC patients. These differentially regulated proteins were considered as potential biomarkers for the patients with CRC in the serum and of the potential value for further investigation.

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.

Discrimination analysis of mass spectrometry proteomics for cervical cancer detection.

To study the serum protein fingerprint of patients with cervical cancer and to screen for protein molecules closely related to cervical cancer during the onset and progression of the disease using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Serum samples from 85 patients with cervical cancer and 80 healthy volunteers. Weak cation exchange (WCX) magnetic beads and PBSII-C protein chips reader (Ciphergen Biosystems Ins.) were used.The protein fingerprint expression of all the serum samples and the resulting profiles between cancer and normal were analyzed with Biomarker Wizard system. A group of proteomic peaks were detected. Three differently expressed potential biomarkers were identified with the relative molecular weights of 3974Da, 4175Da, 5906Da. This diagnostic model can distinguish cervical cancer from healthy controls with a sensitivity of 93.3% and a specificity of 95%. Blind test data indicated a sensitivity of 87.5% and a specificity of 90%. MALDI technology can be used to screen significant proteins of differential expression in the serum of cervical cancer patients. These different proteins could be specific biomarkers of the patients with cervical cancer in the serum and have the potential value of further investigation.

Comparison of algorithms for pre-processing of SELDI-TOF mass spectrometry data

Surface-enhanced laser desorption and ionization (SELDI) time of flight (TOF) is a mass spectrometry technology. The key features in a mass spectrum are its peaks. In order to locate the peaks and quantify their intensities, several pre-processing steps are required. Though different approaches to perform pre-processing have been proposed, there is no systematic study that compares their performance. In this article, we present the results of a systematic comparison of various popular packages for pre-processing of SELDI-TOF data. We evaluate their performance in terms of two of their primary functions: peak detection and peak quantification. Regarding peak quantification, the performance of the algorithms is measured in terms of reproducibility. For peak detection, the comparison is based on sensitivity and false discovery rate. Our results show that for spectra generated with low laser intensity, the software developed by Ciphergen Biosystems (ProteinChip Software 3.1 with the additional tool Biomarker Wizard) produces relatively good results for both peak quantification and detection. On the other hand, for the data produced with either medium or high laser intensity, none of the methods show uniformly better performances under both criteria. Our analysis suggests that an advantageous combination is the use of the packages MassSpecWavelet and PROcess, the former for peak detection and the latter for peak quantification.

Potential Biomarkers of Acute Cerebral Infarction Detected by SELDI-TOF-MS

No single biologic marker is used in the routine diagnosis of acute cerebral infarction. We screened for potential biomarkers in 92 plasma samples, including samples from 32 patients with acute cerebral infarction and 60 hospital control subjects. Pretreated plasma samples were analyzed using SELDI-TOF-MS (Ciphergen Biosystems, Fremont, CA). Proteomic spectra of mass to charge ratio (m/z) were generated by the application of plasma to weak cation exchange (CM10 ProteinChip, Ciphergen Biosystems) arrays. A differential pattern consisting of 13 biomarkers was selected based on their collective contribution to the optimal separation between patients with acute cerebral infarction and control subjects with a sensitivity of 84.4% and specificity of 95.0%, respectively. Plasma proteomic profiling with SELDI-TOF-MS and ProteinChip technologies shows potential in discriminating patients with acute cerebral infarction and control subjects. Diagnosis of acute cerebral infarction should probably depend on the use of a panel of biomarkers.

Protein Profiling of Human Breast Tumor Cells Identifies Novel Biomarkers Associated with Molecular Subtypes

Molecular subtypes of breast cancer with relevant biological and clinical features have been defined recently, notably ERBB2-overexpressing, basal-like, and luminal-like subtypes. To investigate the ability of mass spectrometry-based proteomics technologies to analyze the molecular complexity of human breast cancer, we performed a SELDI-TOF MS-based protein profiling of human breast cell lines (BCLs). Triton-soluble proteins from 27 BCLs were incubated with ProteinChip arrays and subjected to SELDI analysis. Unsupervised global hierarchical clustering spontaneously discriminated two groups of BCLs corresponding to "luminal-like" cell lines and to "basal-like" cell lines, respectively. These groups of BCLs were also different in terms of estrogen receptor status as well as expression of epidermal growth factor receptor and other basal markers. Supervised analysis revealed various protein biomarkers with differential expression in basal-like versus luminal-like cell lines. We identified two of them as a carboxyl terminus-truncated form of ubiquitin and S100A9. In a small series of frozen human breast tumors, we confirmed that carboxyl terminus-truncated ubiquitin is observed in primary breast samples, and our results suggest its higher expression in luminal-like tumors. S100A9 up-regulation was found as part of the transcriptionally defined basal-like cluster in DNA microarrays analysis of human tumors. S100A9 association with basal subtypes as well as its poor prognosis value was demonstrated on a series of 547 tumor samples from early breast cancer deposited in a tissue microarray. Our study shows the potential of integrated genomics and proteomics profiling to improve molecular knowledge of complex tumor phenotypes and identify biomarkers with valuable diagnostic or prognostic values.

The potential biomarkers for thromboembolism detected by SELDI-TOF-MS

The potential biomarkers for thromboembolism detected by SELDI-TOF-MS

A serum Biomarker model to diagnose pancreatic cancer using proteomic fingerprint technology

OBJECTIVE To establish a serum protein pattern model for screening pancreatic cancer. METHODS Twenty-nine serum samples from patients with pancreatic cancer were collected before surgery, and an additional 57 serum samples from age and sex-matched individuals without cancer were used as controls. WCX magnetic beans and a PBS II-C protein chip reader (Ciphergen Biosystems Inc) were employed to detect the protein fingerprint expression of all serum samples. The resulting pro fi les comparing serum from cancer and normal patients were analyzed with the Biomarker Wizard system, to establish a model using the Biomarker Pattern system software. A double-blind test was used to determine the sensitivity and specificity of the model. RESULTS A group of 4 biomarkers (relative molecular weights were 5,705 Da, 4,935 Da, 5,318 Da, 3,243 Da) were selected to set up a decision tree to produce the classification model to effectively screen pancreatic cancer patients. The results yielded a sensitivity of 100% (20/20), specificity of 97.4% (37/38). The ROC curve was 99.7%. A double-blind test used to challenge the model resulted in a sensitivity of 88.9% and a specificity of 89.5%. CONCLUSION New serum biomarkers of pancreatic cancer have been identified. The pattern of combined markers provides a powerful and reliable diagnostic method for pancreatic cancer with high sensitivity and specificity.

Recombinant Mouse Sperm ZP3-binding Protein (ZP3R/sp56) Forms a High Order Oligomer That Binds Eggs and Inhibits Mouse Fertilization in Vitro

Many candidates have been proposed as zona pellucida-binding proteins. Without precluding a role for any of those candidates, we focused on mouse sperm protein ZP3R/sp56, which is localized in the acrosomal matrix. The objective of this study was to analyze the role of ZP3R/sp56 in mouse fertilization. We expressed recombinant ZP3R/sp56 as a secreted protein in HEK293 cells and purified it from serum-free, conditioned medium. In the presence of reducing agents, the recombinant ZP3R/sp56 exhibited a molecular weight similar to that observed for the native ZP3R/sp56. Reminiscent of the native protein, recombinant ZP3R/sp56 formed a high molecular weight, disulfide cross-linked oligomer consisting of six or more monomers under non-reducing conditions. Recombinant ZP3R/sp56 bound to the zona pellucida of unfertilized eggs but not to 2-cell embryos, indicating that the changes that take place in the zona pellucida at fertilization affected the interaction of this protein with the zona pellucida. The extent of in vitro fertilization was reduced in a dose-dependent manner when unfertilized eggs were preincubated with recombinant ZP3R/sp56 (74% drop at the maximum concentrations assayed). Eggs incubated with the recombinant protein showed an absence of or very few sperm in the perivitelline space, suggesting that the reduction in the fertilization rate is caused by the inhibition of sperm binding and/or penetration through the zona pellucida. These results indicate that sperm ZP3R/sp56 is important for sperm-zona interactions during fertilization and support the concept that the acrosomal matrix plays an essential role in mediating the binding of sperm to the zona pellucida.

Laboratory methods to improve SELDI peak detection and quantitation

BackgroundProtein profiling with surface-enhanced laser desorption-ionisation time-of-flight mass spectrometry (SELDI-TOF MS) is a promising approach for biomarker discovery. Some candidate biomarkers have been identified using SELDI-TOF, but validation of these can be challenging because of technical parameters that effect reproducibility. Here we describe steps to improve the reproducibility of peak detection.MethodsSELDI-TOF mass spectrometry was performed using a system manufactured by Ciphergen Biosystems along with their ProteinChip System. Serum from 10 donors was pooled and used for all experiments. Serum was fractionated with Expression Difference Mapping kit-Serum Fractionation from the same company and applied to three different ProteinChips. The fractionations were run over a one month period to examine the contribution of sample batch and time to peak detection variability. Spectra were processed and peaks detected using the Ciphergen Express software and variance measured.ResultsExperimental parameters specific to the serum fraction and ProteinChip, including spot protocols (laser intensity and detector sensitivity) were optimized to decrease peak detection variance. Optimal instrument settings, regular calibration along with controlled sample handling and processing nearly doubled the number of peaks detected and decreased intensity variance.ConclusionThis report assesses the variation across fractionated sera processed over a one-month period. The optimizations reported decreased the variance and increased the number of peaks detected.

Artificial neural networks combined with surface-enhanced laser desorption/ionization mass spectra distinguish endometriosis from healthy population

Artificial neural networks combined with surface-enhanced laser desorption/ionization mass spectra distinguish endometriosis from healthy population

Detection of endometriosis with the use of plasma protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Detection of endometriosis with the use of plasma protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Serum pharmacoproteomics of erlotinib-treated advanced prostate cancer patients: A SELDI-TOF mass spectrometry analysis

14603 Background: EGFR (Epidermal Growth Factor Receptor) is a promising target in various epithelial cancers. Erlotinib is an orally active small molecule tyrosine kinase inhibitor (TKI) targeting EGFR, under evaluation in prostate cancer. To identify protein biomarkers associated with EGFR TKI treatment we performed serum protein profiling in advanced prostate cancer patients receiving erlotinib, using Surface Enhanced Laser Desorption/Ionization-Time of Flight Mass Spectrometry (SELDI-TOF MS). Method: Serums from 23 advanced or metastatic prostate cancer patients enrolled in a phase II study of erlotinib as single agent were collected before treatment, on D28 and D56 and kept frozen in liquid nitrogen until analysis. Serum samples from each patients and each time points were first urea treated and then incubated with 3 different ProteinChip arrays (Ciphergen Biosystems): IMAC-Cu, CM10 and H50 using a fully automated platform (Tecan). After adding SPA matrix, arrays were analysed using a PBSIIc ProteinChip reader (Ciphergen Biosystems). After noise reduction, baseline substraction, and data normalisation, protein peaks were detected using the Biomarker Wizard tool integrated to the ProteinChip Software 3.1. Numeric data were then exported to excel files that were used for further biostatistic processing. Results: Combining protein profiles resolved from each experimental condition, several hundreds of protein peaks were obtained. Protein profiles from untreated and D28 and D56-treated patients were compared using non-parametric statistical methods and several protein peaks appeared differentially expressed between pre and post-treatment samples. Supervised methods identified protein peaks correlating with specific erlotinib toxicity on day 28. Since only minimal activity was noted in this trial, no protein profile correlating with anti-tumor effect was identified. Purification and identification of proteins modulated by treatment and associated with toxicity are ongoing. Conclusion: Serum protein profiling using SELDI-TOF MS is a promising method to characterize pharmacoproteomics of innovative compounds under development and to identify protein biomarkers potentially associated with drug effects. No significant financial relationships to disclose.

Preliminary analysis of biomarkers in plasma by SELDI to predict the response to EGFR tyrosine kinase inhibitors (TKIs) in NSCLC patients

7189 Background: The identification of NSCLC patients who are most likely to respond to EGFR tyrosine kinase inhibitors (TKIs) have been investigated intensively. Although screenings for EGFR mutation and gene copy number are promising, these tests are not yet widely available. New predictor markers are urgently needed. The objective of this study was to identify proteomic markers in plasma to predict benefits for patients treated with EGFR TKIs. Methods: Proteomic spectra derived from plasma samples from EGFR TKIs-responsive patients and non-responsive patients were generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). These proteomic spectra (WCX2 chips, Ciphergen Biosystems, Inc.) were then analyzed by comparing protein profiles in different response groups (PR Vs PD, training set). Another group of patients treaded with EGFR TKIs will be serving as testing set to validate the result of training set. Results: Totally, fifty-four advanced NSCLC patients were included in this study. All patients were treated with single agent of gefitinib or erlotinib. Twenty-nine patients were included in training set of this study. All were suitable for response evaluation. Ten patients (34.5%) were PR, 8 (27.6%) were SD, and 11 (37.9%) were progressive disease (PD). Total six significant protein peaks were significant (m/z 4288, 4595, 9191, 9349, 9397, and 9563) between PR group and PD group (table). Another twenty-five patients were included for testing set. Analyzing of testing set is still going on. Table shows PR and PD patients’ plasma comparison on WCX2 chips. Conclusions: This preliminary “training” set of spectra that uses SELDI-TOF MS technology found that six protein peaks seemed to be very important biomarkers to predict the response to gefitinib. Prospective tests to confirm these proteins and peptides will be present at this meeting. These results are promising for identifying new biomarkers of EGFR TKIs with SELDI. [Table: see text] No significant financial relationships to disclose.

ProteinChip technology is a useful method in the pathogenesis and diagnosis of endometriosis: a preliminary study

ProteinChip technology is a useful method in the pathogenesis and diagnosis of endometriosis: a preliminary study

1141644472 Surface Enhanced Laser Desorption and Ionization (SELDI) mass spectrometry for investigation of human embryo conditioned IVF culture medium

Introduction: The human pre‐implantation embryo metabolism is still widely unknown. Mass spectrometry is a very sensitive proteomic method to detect the entire spectrum of molecules in samples below 1 μL. Surface Enhanced Laser Desorption Ionisation – Time Of Flight (SELDI – TOF) mass spectrometry is a further advanced method to reduce overlapping signals from different substances.Material and Methods: A total of 22 different pre‐implantation embryo supernatants (10 μL each) from 16 different single‐cultured embryos were analyzed. From 6 embryos, supernatants were obtained both at day 3 and 5. Embryo stage was defined by microscopy. Different stages including arrested embryos, 4‐ or 8‐cell stage, early and expanded blastocysts were investigated. SELDI combines a chip‐based separation technology with mass spectrometry. All samples were fractioned by applying six different pH milieus and then exposed to chips with six differently coated surfaces. All fractions were analyzed on a mass spectrometer type ProteinChip System, Series 4000 (Ciphergen Biosystems, Inc.).Results: By comparing the protein profiles of the analyzed embryos the implemented bioinformatic software was able to classify blinded samples correctly into groups of embryos as defined by microscopy. The use of IMAC‐chips (copper‐coated) and CM10‐chips (cation‐exchange) led to highest resolution of peaks. Although the masses of numerous molecules in culture media are assessed by this method, the exact definition of substances needs application of further techniques.Conclusions: These first SELDI mass spectrometric analyses of embryo culture media demonstrate the capability of discriminating different stages of human pre‐implantation embryos by their protein expression profiles.