Data analysis of assorted serum peptidome profiles

Important options available--from start to finish--for translating proteomics results to clinical chemistry

In the realm of clinical chemistry, the field of clinical proteomics, that is, the application of proteomic methods for understanding mechanisms and enabling diagnosis, prediction, measurement of activity, and treatment response in disease, is first and foremost a discovery and research tool that feeds assay development downstream. Putative new assay candidates generated by proteomics discovery projects compete with well-established assays with known indications, well-described performance, and of known value in specific clinical settings. Careful attention to the many options available in the design, execution, and interpretation of clinical proteomics studies is thus necessary for translation into clinical practice. We here review and discuss important options associated with clinical proteomics endeavors stretching from the planning phases to the final use in clinical chemistry.

Inhibition of circulating dipeptidyl peptidase 4 activity in patients with metastatic prostate cancer

Cancer is responsible for many deaths and is a major source of healthcare expenditures. The identification of new, non-invasive biomarkers might allow improvement of the direct diagnostic or prognostic ability of already available tools. Here, we took the innovative approach of interrogating the activity of exopeptidases in the serum of cancer patients with the aim of establishing a distinction based on enzymatic function, instead of simple protein levels, as a means to biomarker discovery. We first analyzed two well-characterized mouse models of prostate cancer, each with a distinct genetic lesion, and established that broad exopeptidase and targeted aminopeptidase activity tests reveal proteolytic changes associated with tumor development. We also describe new peptide-based freeze-frame reagents uniquely suited to probe the altered balance of selected aminopeptidases, as opposed to the full array of exopeptidases, and/or their modulators in patient serum or plasma. One particular proteolytic activity was impaired in animals with aggressive disease relative to cancer-free littermates. We identified the protease in question as dipeptidyl peptidase 4 (DPP4) by analyzing selected knockout mice and evaluating the effect of specific inhibitors. DPP4 activity was also reduced in the sera of patients with metastatic prostate cancer relative to patients with localized disease or healthy controls. However, no significant differences in DPP4 serum levels were observed, which established the loss of activity as the result of impaired enzymatic function. Biochemical analysis indicated that reduced activity was the result not of post-translational modifications or allosteric changes, but instead of a low-molecular-weight inhibitor. After we adjusted for age and total prostate-specific antigen, reduced DPP4 activity remained a significant predictor of cancer status. The results of this proof-of-principle study suggest that DPP4 activity might be a potential blood-based indicator of the presence of metastatic cancer of prostatic origin, either by itself or, more likely, as a means to improve the sensitivity and specificity of existing markers.

Detection of cervical cancer biomarker patterns in blood plasma and urine by differential scanning calorimetry and mass spectrometry

Improved methods for the accurate identification of both the presence and severity of cervical intraepithelial neoplasia (CIN) and extent of spread of invasive carcinomas of the cervix (IC) are needed. Differential scanning calorimetry (DSC) has recently been shown to detect specific changes in the thermal behavior of blood plasma proteins in several diseases. This methodology is being explored to provide a complementary approach for screening of cervical disease. The present study evaluated the utility of DSC in differentiating between healthy controls, increasing severity of CIN and early and advanced IC. Significant discrimination was apparent relative to the extent of disease with no clear effect of demographic factors such as age, ethnicity, smoking status and parity. Of most clinical relevance, there was strong differentiation of CIN from healthy controls and IC, and amongst patients with IC between FIGO Stage I and advanced cancer. The observed disease-specific changes in DSC profiles (thermograms) were hypothesized to reflect differential expression of disease biomarkers that subsequently bound to and affected the thermal behavior of the most abundant plasma proteins. The effect of interacting biomarkers can be inferred from the modulation of thermograms but cannot be directly identified by DSC. To investigate the nature of the proposed interactions, mass spectrometry (MS) analyses were employed. Quantitative assessment of the low molecular weight protein fragments of plasma and urine samples revealed a small list of peptides whose abundance was correlated with the extent of cervical disease, with the most striking plasma peptidome data supporting the interactome theory of peptide portioning to abundant plasma proteins. The combined DSC and MS approach in this study was successful in identifying unique biomarker signatures for cervical cancer and demonstrated the utility of DSC plasma profiles as a complementary diagnostic tool to evaluate cervical cancer health.

Peptidome analysis of human skim milk in term and preterm milk

The abundant proteins in human milk have been well characterized and are known to provide nutritional, protective, and developmental advantages to both term and preterm infants. Due to the difficulties associated with detection technology of the peptides, the expression of the peptides present in human milk is not known widely. In recent years, peptidome analysis has received increasing attention. In this report, the analysis of endogenous peptides in human milk was done by mass spectrometry. A method was also developed by our researchers, which can be used in the extraction of peptide from human milk. Analysis of the extracts by LC-MS/MS resulted in the detection of 1000-3000Da peptide-like features. Out of these, 419 peptides were identified by MS/MS. The identified peptides were found to originate from 34 proteins, of which several have been reported. Analysis of the peptides' cleavage sites showed that the peptides are cleaved with regulations. This may reflect the protease activity and distribution in human body, and also represent the biological state of the tissue and provide a fresh source for biomarker discovery. Isotope dimethyl labeling analysis was also used to test the effects of premature delivery on milk protein composition in this study. Differences in peptides expression between breast milk in term milk (38-41weeks gestation) and preterm milk (28-32weeks gestation) were investigated in this study. 41 Peptides in these two groups were found expressed differently. 23 Peptides were present at higher levels in preterm milk, and 18 were present at higher levels in term milk.

Simultaneous extraction and rapid visualization of peptidomic and lipidomic body fluids fingerprints using mesoporous aluminosilicate and MALDI-TOF MS

Herein we report the use of mesoporous aluminosilicate (MPAS) for the simultaneous extraction of peptides and lipids from complex body fluids such as human plasma and synovial fluid. We show that MPAS particles, given their mesostructural features with nanometric pore size and high surface area, are an efficient device for simultaneous extraction of peptidome and lipidome from as little as a few microliters of body fluids. The peptides and the lipids, selected and enriched by MPAS particles and rapidly visualized by MALDI-TOF MS, could form part of a diagnostic profile of the "peptidome" and the "lipidome" of healthy versus diseased subjects in comparative studies. The ability of this approach to rapidly reveal the overall pattern of changes in both lipidome and peptidome signatures of complex biofluids could be of valuable interest for handling large numbers of samples required in -omics studies for the purpose of finding novel biomarkers.

Quantitative statistical analysis of standard and human blood proteins from liquid chromatography, electrospray ionization, and tandem mass spectrometry

It will be important to determine if the parent and fragment ion intensity results of liquid chromatography, electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) experiments have been randomly and independently sampled from a normal population for the purpose of statistical analysis by general linear models and ANOVA. The tryptic parent peptide and fragment ion m/z and intensity data in the mascot generic files from LC-ESI-MS/MS of purified standard proteins, and human blood protein fractionated by partition chromatography, were parsed into a Structured Query Language (SQL) database and were matched with protein and peptide sequences provided by the X!TANDEM algorithm. The many parent and/or fragment ion intensity values were log transformed, tested for normality, and analyzed using the generic Statistical Analysis System (SAS). Transformation of both parent and fragment intensity values by logarithmic functions yielded intensity distributions that closely approximate the log-normal distribution. ANOVA models of the transformed parent and fragment intensity values showed significant effects of treatments, proteins, and peptides, as well as parent versus fragment ion types, with a low probability of false positive results. Transformed parent and fragment intensity values were compared over all sample treatments, proteins or peptides by the Tukey-Kramer Honestly Significant Difference (HSD) test. The approach provided a complete and quantitative statistical analysis of LC-ESI-MS/MS data from human blood.

Exploring serological classification tree model of active pulmonary tuberculosis by magnetic beads pretreatment and MALDI-TOF MS analysis

Pulmonary tuberculosis (TB) is an infectious disease disturbing status of public health, and accurate diagnosis of TB would effectively help control the disturbance. Our study tried to establish a classification tree model that distinguished active TB from non-TB individuals. We used matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) combined with weak cationic exchange (WCX) magnetic beads to analyse 178 serum samples containing 75 patients with active TB and 103 non-TB individuals (43 patients with common pulmonary diseases and 60 healthy controls). Samples were randomly divided into a training set and a test set. Statistical softwares were applied to construct this model. An amount of 48 differential expressed peaks (P < 0.05) were identified by the training set, and our model was set up by three of them, m/z 7626, 8561 and 8608. This model can discriminate patients with active TB from patients with non-TB with a sensitivity of 98.3% and a specificity of 84.4%. The test set was used to verify the performance, which demonstrated good sensitivity and specificity: 85.7% and 83.3%, respectively. Differential expressed peaks between smear-positive and smear-negative active TB also have been analysed. It came out that m/z 8561 and 8608 not only acted as vital factors in the pathogenesis of active TB but also played an important role in regulating different active TB status. In conclusion, MALDI-TOF MS combined with WCX magnetic beads was a powerful technology for constructing classification tree model, and the model we built could serve as a potential diagnostic tool for active TB.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Serum apolipoproteins C-I and C-III are reduced in stomach cancer patients: results from MALDI-based peptidome and immuno-based clinical assays

Finding new peptide biomarkers for stomach cancer in human sera that can be implemented into a clinically practicable prediction method for monitoring of stomach cancer. We studied the serum peptidome from two different biorepositories. We first employed a C8-reverse phase liquid chromatography approach for sample purification, followed by mass-spectrometry analysis. These were applied onto serum samples from cancer-free controls and stomach cancer patients at various clinical stages. We then created a bioinformatics analysis pipeline and identified peptide signature discriminating stomach adenocarcinoma patients from cancer-free controls. Matrix Assisted Laser Desorption/Ionization–Time of Flight (MALDI-TOF) results from 103 samples revealed 9 signature peptides; with prediction accuracy of 89% in the training set and 88% in the validation set. Three of the discriminating peptides discovered were fragments of Apolipoproteins C-I and C-III (apoC-I and C-III); we further quantified their serum levels, as well as CA19-9 and CRP, employing quantitative commercial-clinical assays in 142 samples. ApoC-I and apoC-III quantitative results correlated with the MS results. We then employed apoB-100-normalized apoC-I and apoC-III, CA19-9 and CRP levels to generate rules set for stomach cancer prediction. For training, we used sera from one repository, and for validation, we used sera from the second repository. Prediction accuracies of 88.4% and 74.4% were obtained in the training and validation sets, respectively. Serum levels of apoC-I and apoC-III combined with other clinical parameters can serve as a basis for the formulation of a diagnostic score for stomach cancer patients.

MALDI-TOF serum profiling using semiautomated serum peptide capture with magnetic reversed phase (C18) beads

Mass spectrometry can be used to generate diagnostic peptide peak profiles "signatures" of serum samples. Peak profiles can be used to compare different sera and correlate samples (i.e., patient groups) with clinical data to assist in diagnosis, monitoring, and/or prediction. We describe the semiautomated capture of serum peptides/small proteins with magnetic beads that harbor C18 alkyl chains, the deposition of captured material on a target plate for MALDI-TOF mass spectrometry, as well as, general guidelines for data acquisition. We also include, in a separate note, a short manual version of the capture procedure. Overall, the serum sample processing protocol, reported here, is reproducible and robust. In conjunction with MALDI-TOF mass spectrometry, this protocol allows for the profiling of several hundreds of serum peptides.

Detection of oesophageal cancer biomarkers by plasma proteomic profiling of human cell line xenografts in response to chemotherapy

Background:

The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy may improve survival, but targeting treatment to patients who respond to chemotherapy could be improved by the availability of markers of response. This study sought proteomic markers of therapeutic response using an adenocarcinoma xenograft model.

Methods:

Epirubicin, cisplatin or 5-fluorouracil was administered to severe combined immune-deficient mice bearing OE19 oesophageal adenocarcinoma xenografts. Murine plasma samples from treated and untreated xenografts were analysed by surface-enhanced laser desorption/ionisation time-of-flight mass spectroscopy, and panels of peaks were found using class prediction models that distinguished treatment groups. Proteins in these peaks were identified by mass spectroscopy in tryptic digests of purified fractions. Five paired samples from oesophageal cancer patients before and after chemotherapy were analysed using the same methodology.

Results:

Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the treated xenograft and control groups. Marker panels predicted treated vs untreated xenografts with sensitivities of 100%, specificities of 86–100% and test efficiencies of 89–100%. Three of the proteins identified in these panels, apolipoprotein A-I, serum amyloid A and transthyretin were confirmed in the clinical samples.

Conclusion:

Plasma protein markers can be detected in response to chemotherapy in oesophageal adenocarcinoma xenografts and in clinical samples, and have the potential to monitor response and guide chemotherapy in oesophageal adenocarcinoma.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Strategy for degradomic-peptidomic analysis of human blood plasma

Herein we describe a strategy for degradomic-peptidomic analyses. The human blood peptidome was isolated through application of AC/SEC, which enriched its components by >300-fold. The isolated peptidome components were separated by long column HRLC providing a peak capacity of approximately 300 for species having MWs of up to 20 kDa. The separated species were identified by the FT MS/MS-UStags sequencing method. We identified >200 peptidome components that originated from 29 protein substrates from the blood plasma of a single healthy person. The peptidome peptides identified had MWs range of 0.5-14 kDa and identifications were achieved with extremely low (near zero) false discovery rates through searching the IPI human protein database (approximately 70,000 entries). Some of the peptidome peptides identified have mutations and modifications such as acetylation, acetylhexosamine, amidation, cysteinylation, didehydro, oxidation, and pyro-glu. The capabilities described enable the global analysis of the peptidome peptides to identify degradome targets such as degradome proteases, proteases inhibitors, and other relevant substrates, the cleavage specificities for the degradation of individual substrates, as well as a potential basis for using the various extents of substrate degradation for diagnostic purposes.

The endogenous peptides of normal human serum extracted from the acetonitrile-insoluble precipitate using modified aqueous buffer with analysis by LC-ESI-Paul ion trap and Qq-TOF

Many peptides of biological or medicinal importance may be derived from proteolytic actions and are found at low concentrations in human blood fluids. Endogenous polypeptides from human serum were precipitated in acetonitrile and the precipitate was then selectively extracted with water modified by organic solvents and collected over C18 resin. Extraction of serum with C18 alone, and the acetonitrile supernatant or ultrafiltration collected over C18, served as controls. The samples were analyzed by SDS-PAGE, or C18 high pressure liquid chromatography with electrospray ionization using a Paul ion trap and Qq-TOF. Spectra were correlated without specifying an enzyme using the X!TANDEM or the Paragon algorithms. Multiple endogenous peptides from plasminogen, coagulation factors, collagens, serum amyloid, receptors, zinc finger/bromo peptide proteins, ryanodine receptor, calmodulin binding activator, erythroid differentiation factor, testes cancer antigen, extracellular matrix protein, myeloid/lymphoid leukemia 2 and many low abundance proteins were correlated by X!TANDEM with protein expect values of approximately E-16 or less. Proteins with binding sites for nucleic acids, phosphoinositides, and other cellular locations were also observed using the Qq-TOF and Paragon algorithm. Proteins with low expectation scores and overlapping peptides sequences were observed. The existence of these proteins in serum has been confirmed by tryptic digestion and LC-ESI-MS/MS. The presence of plasminogen, serum amyloid and zinc finger RNA binding proteins were confirmed by Western blot. There was agreement on the detection of endogenous peptides from low abundance proteins associated with the biology of cancer from the examination of the blood peptides by ion trap and Qq-TOF, tryptic digests of blood proteins, and Western blot.

Precipitation and selective extraction of human serum endogenous peptides with analysis by quadrupole time-of-flight mass spectrometry reveals posttranslational modifications and low-abundance peptides

The endogenous peptides of human serum may have regulatory functions, have been associated with physiological states, and their modifications may reveal some mechanisms of disease. In order to correlate levels of specific peptides with disease alongside internal standards, the polypeptides must first be reliably extracted and identified. Endogenous blood peptides can be effectively enriched by precipitation of the serum with organic solvents followed by selective extraction of peptides using aqueous solutions modified with organic solvents. Polypeptides on filter paper were assayed with Coomasie brilliant blue binding. The polypeptides were resolved by detergent tricine polyacrylamide electrophoresis and visualized by diamine silver staining. Peptides in the extracts were collected by C18 and analyzed by matrix-assisted laser desorption/ionization and liquid chromatography-electrospray ionization-tandem mass spectrometry (MS/MS) quadrupole time-of-flight MS/MS. Peptides were resolved as multiple isotopic peaks in MS mode with mass deviation of 0.1 Da or less and similar accuracy for fragments. The sensitivity of MS and MS/MS analysis was estimated to be in the picomolar range or less. The peptide composition of the extracts was dependent on solvent formulation. Multiple peptides from apolipoproteins, complement proteins, coagulation factors, and many others were identified by X!Tandem with high mass accuracy of peptide ions and fragments from collision-induced dissociation. Many previously unreported posttranslational modifications of peptides including phosphorylations, oxidations, glycosylations, and others were detected with high mass accuracy and may be of clinical importance. About 4,630 redundant peptides were identified with 99% confidence separately, and together some 1,251 distinct proteins were identified with 99% confidence or greater using the Paragon algorithm.

Cancer-specific MALDI-TOF profiles of blood serum and plasma: biological meaning and perspectives

MALDI-TOF mass-spectrometry has become a popular tool of cancer research during the last decade. High throughput and relative simplicity of this technology have made it attractive for biomarker discovery and validation across various platforms in blood serum/plasma. Many technical approaches have been developed for plasma/serum profiling including protein-chip based SELDI-TOF mass-spectrometry, purification of serum on magnetic beads, analysis of carrier-associated fraction and mass-spectrometric immunoassays. Extensive data about the identity of differential features detected on mass-spectra up to now makes it possible to draw conclusions about potency and perspectives of MALDI-TOF mass-spectrometry in this field. A great majority of identified differentially expressed proteins are either house-keeping or inflammatory proteins as well as their modifications or fragments. Discriminating ability of mass-spectra is likely to be based on differential modification and fragmentation patterns of abundant serum proteins reflecting activity of enzymes including proteases and their inhibitors.

Prediction of outcome of non-small cell lung cancer patients treated with chemotherapy and bortezomib by time-course MALDI-TOF-MS serum peptide profiling

BACKGROUND

Only a minority of patients with advanced non-small cell lung cancer (NSCLC) benefit from chemotherapy. Serum peptide profiling of NSCLC patients was performed to investigate patterns associated with treatment outcome.Using magnetic bead-assisted serum peptide capture coupled to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), serum peptide mass profiles of 27 NSCLC patients treated with cisplatin-gemcitabine chemotherapy and bortezomib were obtained. Support vector machine-based algorithms to predict clinical outcome were established based on differential pre-treatment peptide profiles and dynamic changes in peptide abundance during treatment.

RESULTS

A 6-peptide ion signature distinguished with 82% accuracy, sensitivity and specificity patients with a relatively short vs. long progression-free survival (PFS) upon treatment. Prediction of long PFS was associated with longer overall survival. Inclusion of 7 peptide ions showing differential changes in abundance during treatment led to a 13-peptide ion signature with 86% accuracy at 100% sensitivity and 73% specificity. A 5-peptide ion signature could separate patients with a partial response vs. non-responders with 89% accuracy at 100% sensitivity and 83% specificity. Differential peptide profiles were also found when comparing the NSCLC serum profiles to those from cancer-free control subjects.

CONCLUSION

This study shows that serum peptidome profiling using MALDI-TOF-MS coupled to pattern diagnostics may aid in prediction of treatment outcome of advanced NSCLC patients treated with chemotherapy.

Monitoring peptidase activities in complex proteomes by MALDI-TOF mass spectrometry

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semiquantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide substrates using robotic extraction and a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometric readout. Relative quantitation of the peptide metabolites is carried out by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be used for diagnostic or predictive purposes and it enables profiling of 96 samples in 30 h. It could be tailored to many diagnostic and pharmaco-dynamic purposes as a readout of catalytic and metabolic activities in body fluids or tissues.

Serum proteomics using mass spectrometry

The identification and eventual application of tumor markers in cancer screening, early detection, diagnosis, and prognosis is a continuing focus of significant translational cancer research. While many new candidate markers have been discovered and at least partly characterized, very few have found widespread clinical application limited presently to the use of CA-125 in ovarian cancer, CEA, primarily in colon cancer, and PSA in prostate cancer screening and patient monitoring. The rapidly emerging field of cancer genomics and proteomics, and their clinical translation as "molecular diagnosis" and "molecular medicine" are already beginning to transform the field, and the accelerating growth of information and technology in this research area will undoubtedly transform the field of tumor markers and their application in the near future leading to improved molecular tools for cancer diagnosis, prognosis, and treatment and ultimately, to the emergence of novel and more effective cancer therapies, including improved approaches for immunotherapy and cancer prevention strategies. Toward this goal, herein are described detailed methods and workflows for mass spectrometry-based biomarker discovery in serum/plasma utilizing two complementary approaches - matrix-assisted laser desorption ionization time of flight (MALDI-TOF) and nanoflow reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS). These discovery workflows incorporate both abundant protein depletion and sample fractionation upstream of analytical mass spectrometry to optimize the identification and quantitation of lower abundant species.

Screening serum biomarkers of fatty liver disease using proteomic technology

AIM: To analyze the serum proteomic pattern of the fatty liver disease (FLD) patients, to build a diagnostic model and to evaluate its clinic significance using magnetic bead and MALDI-TOF-MS.

METHODS: WCX magnetic bead and MALDI-TOF-MS were used to detect the serum proteomic patterns of 95 modest FLD patients, 76 mild FLD patients and 99 healthy persons (HP). Biomarker Wizard software was used to analyze protein peaks for significant difference. The model was then built by Biomarker Patterns Software and was further evaluated in blind test for reliability.

RESULTS: A diagnostic pattern for modest FLD from HP using m/z 7626.2, 24147.7, 6118.2 was established with 90.2% sensitivity and 93.9% specificity. A sensitivity of 90.9% and a specificity of 92.0% in blind test were obtained. One diagnostic pattern using m/z 7626.2, 3286.0, 2760.7, 2543.1, 2746.1 was established to differentiate mild from modest FLD; the other diagnostic pattern using m/z 7626.2, 11721.0, 24141.7, 8529.1, 9042.7 was established to differentiate mild FLD from HP.

CONCLUSION: Proteomic technology can significantly identify novel significant biomarkers in the serum. The diagnostic pattern consisting of three differential protein peaks can discriminate the modest FLD from HP. The diagnostic pattern consisting of five specific differential protein peaks can differentiate mild from modest FLD as well as mild FLD from HP.

Precision enhancement of MALDI-TOF MS using high resolution peak detection and label-free alignment

We have developed an automated procedure for aligning peaks in multiple TOF spectra that eliminates common timing errors and small variations in spectrometer output. Our method incorporates high-resolution peak detection, re-binning, and robust linear data fitting in the time domain. This procedure aligns label-free (uncalibrated) peaks to minimize the variation in each peak's location from one spectrum to the next, while maintaining a high number of degrees of freedom. We apply our method to replicate pooled-serum spectra from multiple laboratories and increase peak precision (t/sigma(t)) to values limited only by small random errors (with sigma(t) less than one time count in 89 out of 91 instances, 13 peaks in seven datasets). The resulting high precision allowed for an order of magnitude improvement in peak m/z reproducibility. We show that the CV for m/z is 0.01% (100 ppm) for 12 out of the 13 peaks that were observed in all datasets between 2995 and 9297 Da.