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1.  Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation 
PLoS Computational Biology  2013;9(4):e1002963.
Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.
Author Summary
Novel proteomic technology has led to the generation of vast amounts of biological data and the identification of numerous potential biomarkers. However, computational approaches to translate this information into knowledge capable of impacting clinical care have been lagging. We propose a computational proteomic pipeline for biomarker studies that is founded on the combination of advanced statistical methodologies. We demonstrate our approach through the analysis of data obtained from heart transplant patients. Heart transplantation is the gold standard treatment for patients with end-stage heart failure, but is complicated by episodes of immune rejection that can adversely impact patient outcomes. Current rejection monitoring approaches are highly invasive, requiring a biopsy of the heart. This work aims to reduce the need for biopsies, and demonstrate the power and utility of computational approaches in proteomic biomarker discovery. Our work utilizes novel high-throughput proteomic technology combined with advanced statistical techniques to identify blood markers that guide the decision as to whether a biopsy is warranted, reduce the number of unnecessary biopsies, and ultimately diagnose the presence of rejection in heart transplant patients. Additionally, the proposed computational methodologies can be applied to a range of proteomic biomarker studies of various diseases and conditions.
doi:10.1371/journal.pcbi.1002963
PMCID: PMC3617196  PMID: 23592955
2.  A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice 
Proteomics has opened a new horizon in biological sciences. Global proteomic analysis is a promising technology for the discovery of thousands of proteins, post-translational modifications, polymorphisms, and molecular interactions in a variety of biological systems. The activities and roles of the identified proteins must also be elucidated, but this is complicated by the inability of conventional proteomic methods to yield quantitative information for protein expression. Thus, a variety of biological systems remain “black boxes”. Quantitative targeted absolute proteomics (QTAP) enables the determination of absolute expression levels (mol) of any target protein, including low-abundance functional proteins, such as transporters and receptors. Therefore, QTAP will be useful for understanding the activities and roles of individual proteins and their differences, including normal/disease, human/animal, or in vitro/in vivo. Here, we describe the study protocols and precautions for QTAP experiments including in silico target peptide selection, determination of peptide concentration by amino acid analysis, setup of selected/multiple reaction monitoring (SRM/MRM) analysis in liquid chromatography–tandem mass spectrometry, preparation of protein samples (brain capillaries and plasma membrane fractions) followed by the preparation of peptide samples, simultaneous absolute quantification of target proteins by SRM/MRM analysis, data analysis, and troubleshooting. An application of QTAP in biological sciences was introduced that utilizes data from inter-strain differences in the protein expression levels of transporters, receptors, tight junction proteins and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice. Among 18 molecules, 13 (abcb1a/mdr1a/P-gp, abcc4/mrp4, abcg2/bcrp, slc2a1/glut1, slc7a5/lat1, slc16a1/mct1, slc22a8/oat3, insr, lrp1, tfr1, claudin-5, Na+/K+-ATPase, and γ-gtp) were detected in the isolated brain capillaries, and their protein expression levels were within a range of 0.637-101 fmol/μg protein. The largest difference in the levels between the three strains was 2.2-fold for 13 molecules, although bcrp and mct1 displayed statistically significant differences between C57BL/6J and the other strain(s). Highly sensitive simultaneous absolute quantification achieved by QTAP will increase the usefulness of proteomics in biological sciences and is expected to advance the new research field of pharmacoproteomics (PPx).
doi:10.1186/2045-8118-10-21
PMCID: PMC3691662  PMID: 23758935
Quantitative targeted absolute proteomics (QTAP); Pharmacoproteomics (PPx); Absolute expression level; In silico peptide selection criteria; LC-MS/MS; Blood–brain barrier; Strain difference; Transporter; Receptor; Tight junction protein
3.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
doi:10.1038/msb.2011.37
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
4.  Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling 
Journal of Proteome Research  2010;9(8):4295-4305.
Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.
Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes but incomplete sampling poses challenges in comparing protein inventories by spectral counting approaches. We developed a statistical method based on quasi-likelihood modeling and demonstrate that it compares favorably to other statistical tests. Statistically significant spectral count differences were confirmed by MRM demonstrating that the observed protein level differences reflect the underlying biology of the samples.
doi:10.1021/pr100527g
PMCID: PMC2920032  PMID: 20586475
LC−MS/MS; shotgun proteomics; multiple reaction monitoring (MRM); head and neck carcinoma; Generalized Linear Model; spectral counting
5.  Development of Biomarkers for Screening Hepatocellular Carcinoma Using Global Data Mining and Multiple Reaction Monitoring 
PLoS ONE  2013;8(5):e63468.
Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.
doi:10.1371/journal.pone.0063468
PMCID: PMC3661589  PMID: 23717429
6.  Implementation of a Data Repository-Driven Approach for Targeted Proteomics Experiments by Multiple Reaction Monitoring 
Journal of proteomics  2008;72(5):838-852.
Multiple Reaction Monitoring (MRM), commonly employed for the mass spectrometric detection of small molecules, is rapidly gaining ground in proteomics. Its high sensitivity and specificity makes this targeted approach particularly useful when sample throughput or proteome coverage limits global studies. Existing tools to design MRM assays rely exclusively on theoretical predictions, or combine them with previous observations on the same type of sample. The additional mass spectrometric experimentation this requires can pose significant demands on time and material. To overcome these challenges, a new MRM worksheet was introduced into The Global Proteome Machine database (GPMDB) that provided all of the information needed to design MRM transitions based solely on archived observations made by other researchers in previous experiments. This required replacing the precursor ion intensity by the number of peptide observations, which proved to be an adequate substitute if peptides did not occur in multiple forms. While the absence of collision energy information proved largely inconsequential, successful prediction of unique transitions depended on the type of fragment ion involved. The design of MRM assays for iTRAQ-labeled tryptic peptides obtained from human platelet proteins demonstrated the usefulness of the MRM worksheet also for quantitative applications. This workflow, which relies exclusively on experimental observations stored in data repositories, therefore represents an attractive alternative for the prediction of MRM transitions prior to experimental validation and optimization.
doi:10.1016/j.jprot.2008.11.015
PMCID: PMC2706936  PMID: 19121650
Tandem Mass Spectrometry; Multiple Reaction Monitoring; Targeted Proteomics; Data Repository; Platelets
7.  Dose-Dependent Proteomic Analysis of Glioblastoma Cancer Stem Cells upon Treatment with Gamma-Secretase Inhibitor 
Proteomics  2011;11(23):4529-4540.
Notch Signaling has been demonstrated to have a central role in Glioblastoma (GBM) Cancer Stem Cells (CSCs) and we have demonstrated recently that Notch pathway blockade by γ-secretase inhibitor (GSI) depletes GBM CSCs and prevents tumor propagation both in vitro and in vivo. In order to understand the proteome alterations involved in this transformation, a dose-dependent quantitative mass spectrometry (MS) based proteomic study has been performed based on global proteome profiling and a target verification phase where both Immunoassay and a Multiple Reaction Monitoring (MRM) assay are employed. The selection of putative protein candidates for confirmation poses a challenge due to the large number of identifications from the discovery phase. A multilevel filtering strategy together with literature mining is adopted to transmit the most confident candidates along the pipeline. Our results indicate that treating GBM CSCs with GSI induces a phenotype transformation towards non-tumorigenic cells with decreased proliferation and increased differentiation, as well as elevated apoptosis. Suppressed glucose metabolism and attenuated NFR2-mediated oxidative stress response are also suggested from our data, possibly due to their crosstalk with Notch Signaling. Overall, this quantitative proteomic based dose-dependent work complements our current understanding of the altered signaling events occurring upon the treatment of GSI in GBM CSCs.
doi:10.1002/pmic.201000730
PMCID: PMC3517080  PMID: 21932445
Glioblastoma; Cancer Stem Cells; Label-free; Multiple Reaction Monitoring; Pathway Analysis
8.  A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins 
Journal of proteome research  2012;11(4):2127-2139.
Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers.
doi:10.1021/pr2007957
PMCID: PMC3703649  PMID: 22256890
Sweat; Proteome; Schizophrenia; Biomarkers; LC-MS/MS; MRM
9.  High Throughput Protein Quantitation using MRM Viewer Software and Dynamic MRM on a Triple Quadruple Mass Spectrometer 
RP-122
Peptide quantitation using Multiple Reaction Monitoring (MRM) has been established as an important methodology for biomarker verification andvalidation.This requires high throughput combined with high sensitivity to analyze potentially thousands of target peptides in each sample.Dynamic MRM allows the system to only acquire the required MRMs of the peptide during a retention window corresponding to when each peptide is eluting. This reduces the number of concurrent MRM and therefore improves quantitation and sensitivity. MRM Selector allows the user to generate an MRM transition list with retention time information from discovery data obtained on a QTOF MS system.This list can be directly imported into the triple quadrupole acquisition software.However, situations can exist where a) the list of MRMs contain an excess of MRM transitions allowable under the ideal acquisition conditions chosen ( allowing for cycle time and chromatography conditions), or b) too many transitions in a certain retention time region which would result in an unacceptably low dwell time and cycle time.A new tool - MRM viewer has been developed to help users automatically generate multiple dynamic MRM methods from a single MRM list.In this study, a list of 3293 MRM transitions from a human plasma sample was compiled.A single dynamic MRM method with 3293 transitions results in a minimum dwell time of 2.18ms.Using MRM viewer we can generate three dynamic MRM methods with a minimum dwell time of 20ms which can give a better quality MRM quantitation.This tool facilitates both high throughput and high sensitivity for MRM quantitation.
PMCID: PMC2918046
10.  GeLC-MRM quantitation of mutant KRAS oncoprotein in complex biological samples 
Journal of Proteome Research  2012;11(7):3908-3913.
Tumor-derived mutant KRAS (v-Ki-ras-2 Kirsten rat sarcoma viral oncogene) oncoprotein is a critical driver of cancer phenotypes and a potential biomarker for many epithelial cancers. Targeted mass spectrometry analysis by multiple reaction monitoring (MRM) enables selective detection and quantitation of wild-type and mutant KRAS proteins in complex biological samples. A recently described immunoprecipitation approach (Proc. Nat. Acad. Sci. 2011, 108, 2444–2449) can be used to enrich KRAS for MRM analysis, but requires large protein inputs (2–4 mg). Here we describe sodium dodecyl sulfate-polyacrylamide gel electrophoresis-based enrichment of KRAS in a low molecular weight (20 –25 kDa) protein fraction prior to MRM analysis (GeLC-MRM). This approach reduces background proteome complexity, thus allowing mutant KRAS to be reliably quantified in low protein inputs (5–50 μg). GeLC-MRM detected KRAS mutant variants (G12D, G13D, G12V, G12S) in a panel of cancer cell lines. GeLC-MRM-analysis of wild-type and mutant was linear with respect to protein input and showed low variability across process replicates (CV = 14%). Concomitant analysis of a peptide from the highly similar HRAS and NRAS proteins enabled correction of KRAS-targeted measurements for contributions from these other proteins. KRAS peptides were also quantified in fluid from benign pancreatic cysts and pancreatic cancers at concentrations from 0.08 – 1.1 fmol/μg protein. GeLC-MRM provides a robust, sensitive approach to quantitation of mutant proteins in complex biological samples.
doi:10.1021/pr300161j
PMCID: PMC3400422  PMID: 22671702
KRAS; GeLC-MRM; targeted proteomics; colorectal cancer; pancreatic cyst fluid
11.  Precision of Multiple Reaction Monitoring Mass Spectrometry Analysis of Formalin-Fixed, Paraffin-Embedded Tissue 
Journal of Proteome Research  2012;11(6):3498-3505.
We compared the reproducibility of multiple reaction monitoring (MRM) mass spectrometry-based peptide quantitation in tryptic digests from formalin-fixed, paraffin-embedded (FFPE) and frozen clear cell renal cell carcinoma tissues. The analyses targeted a candidate set of 114 peptides previously identified in shotgun proteomic analyses, of which 104 were detectable in FFPE and frozen tissue. Although signal intensities for MRM of peptides from FFPE tissue were on average 66% of those in frozen tissue, median coefficients of variation (CV) for measurements in FFPE and frozen tissues were nearly identical (18–20%). Measurements of lysine C-terminal peptides and arginine C-terminal peptides from FFPE tissue were similarly reproducible (19.5% and 18.3% median CV, respectively). We further evaluated the precision of MRM-based quantitation by analysis of peptides from the Her2 receptor in FFPE and frozen tissues from a Her2 overexpressing mouse xenograft model of breast cancer and in human FFPE breast cancer specimens. We obtained equivalent MRM measurements of HER2 receptor levels in FFPE and frozen mouse xenografts derived from HER2-overexpressing BT474 cells and HER2-negative Sum159 cells. MRM analyses of 5 HER2-positive and 5 HER-negative human FFPE breast tumors confirmed the results of immunohistochemical analyses, thus demonstrating the feasibility of HER2 protein quantification in FFPE tissue specimens. The data demonstrate that MRM analyses can be performed with equal precision on FFPE and frozen tissues and that lysine-containing peptides can be selected for quantitative comparisons, despite the greater impact of formalin fixation on lysine residues. The data further illustrate the feasibility of applying MRM to quantify clinically important tissue biomarkers in FFPE specimens.
doi:10.1021/pr300130t
PMCID: PMC3368395  PMID: 22530795
formalin-fixed; paraffin-embedded tissue; multiple reaction monitoring; breast cancer; biomarkers; HER2
12.  MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides 
BMC Cancer  2009;9:96.
Background
The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented.
Methods
MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide.
Results
In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000.
Conclusion
Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter ions, MRM conditions can be selected to enable the detection of target peptides and proteins.
doi:10.1186/1471-2407-9-96
PMCID: PMC2670839  PMID: 19327145
13.  Addressing the needs of traumatic brain injury with clinical proteomics 
Clinical proteomics  2014;11(1):11.
Background
Neurotrauma or injuries to the central nervous system (CNS) are a serious public health problem worldwide. Approximately 75% of all traumatic brain injuries (TBIs) are concussions or other mild TBI (mTBI) forms. Evaluation of concussion injury today is limited to an assessment of behavioral symptoms, often with delay and subject to motivation. Hence, there is an urgent need for an accurate chemical measure in biofluids to serve as a diagnostic tool for invisible brain wounds, to monitor severe patient trajectories, and to predict survival chances. Although a number of neurotrauma marker candidates have been reported, the broad spectrum of TBI limits the significance of small cohort studies. Specificity and sensitivity issues compound the development of a conclusive diagnostic assay, especially for concussion patients. Thus, the neurotrauma field currently has no diagnostic biofluid test in clinical use.
Content
We discuss the challenges of discovering new and validating identified neurotrauma marker candidates using proteomics-based strategies, including targeting, selection strategies and the application of mass spectrometry (MS) technologies and their potential impact to the neurotrauma field.
Summary
Many studies use TBI marker candidates based on literature reports, yet progress in genomics and proteomics have started to provide neurotrauma protein profiles. Choosing meaningful marker candidates from such ‘long lists’ is still pending, as only few can be taken through the process of preclinical verification and large scale translational validation. Quantitative mass spectrometry targeting specific molecules rather than random sampling of the whole proteome, e.g., multiple reaction monitoring (MRM), offers an efficient and effective means to multiplex the measurement of several candidates in patient samples, thereby omitting the need for antibodies prior to clinical assay design. Sample preparation challenges specific to TBI are addressed. A tailored selection strategy combined with a multiplex screening approach is helping to arrive at diagnostically suitable candidates for clinical assay development. A surrogate marker test will be instrumental for critical decisions of TBI patient care and protection of concussion victims from repeated exposures that could result in lasting neurological deficits.
doi:10.1186/1559-0275-11-11
PMCID: PMC3976360  PMID: 24678615
Traumatic brain injury; Biomarker; Clinical proteomics; Mass spectrometry; Multiple reaction monitoring
14.  Analysis of host-cell proteins in biotherapeutic proteins by comprehensive online two-dimensional liquid chromatography/mass spectrometry 
mAbs  2012;4(1):24-44.
Assays for identification and quantification of host-cell proteins (HCPs) in biotherapeutic proteins over 5 orders of magnitude in concentration are presented. The HCP assays consist of two types: HCP identification using comprehensive online two-dimensional liquid chromatography coupled with high resolution mass spectrometry (2D-LC/MS), followed by high-throughput HCP quantification by liquid chromatography, multiple reaction monitoring (LC-MRM). The former is described as a “discovery” assay, the latter as a “monitoring” assay. Purified biotherapeutic proteins (e.g., monoclonal antibodies) were digested with trypsin after reduction and alkylation, and the digests were fractionated using reversed-phase (RP) chromatography at high pH (pH 10) by a step gradient in the first dimension, followed by a high-resolution separation at low pH (pH 2.5) in the second dimension. As peptides eluted from the second dimension, a quadrupole time-of-flight mass spectrometer was used to detect the peptides and their fragments simultaneously by alternating the collision cell energy between a low and an elevated energy (MSE methodology). The MSE data was used to identify and quantify the proteins in the mixture using a proven label-free quantification technique (“Hi3” method). The same data set was mined to subsequently develop target peptides and transitions for monitoring the concentration of selected HCPs on a triple quadrupole mass spectrometer in a high-throughput manner (20 min LC-MRM analysis). This analytical methodology was applied to the identification and quantification of low-abundance HCPs in six samples of PTG1, a recombinant chimeric anti-phosphotyrosine monoclonal antibody (mAb). Thirty three HCPs were identified in total from the PTG1 samples among which 21 HCP isoforms were selected for MRM monitoring. The absolute quantification of three selected HCPs was undertaken on two different LC-MRM platforms after spiking isotopically labeled peptides in the samples. Finally, the MRM quantitation results were compared with TOF-based quantification based on the Hi3 peptides, and the TOF and MRM data sets correlated reasonably well. The results show that the assays provide detailed valuable information to understand the relative contributions of purification schemes to the nature and concentrations of HCP impurities in biopharmaceutical samples, and the assays can be used as generic methods for HCP analysis in the biopharmaceutical industry.
doi:10.4161/mabs.4.1.18748
PMCID: PMC3338939  PMID: 22327428
host cell proteins; protein quantification; biotherapeutic proteins; mAbs; HCP
15.  A Database of Reaction Monitoring Mass Spectrometry Assays for Elucidating Therapeutic Response in Cancer 
Proteomics. Clinical applications  2011;5(7-8):383-396.
Purpose
The Quantitative Assay Database (QuAD), http://proteome.moffitt.org/QUAD/, facilitates widespread implementation of quantitative mass spectrometry in cancer biology and clinical research through sharing of methods and reagents for monitoring protein expression and modification.
Experimental Design
Liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM) assays are developed using SDS-PAGE fractionated lysates from cancer cell lines. Pathway maps created using GeneGO Metacore provide the biological relationships between proteins and illustrate concepts for multiplexed analysis; each protein can be selected to examine assay development at the protein and peptide level.
Results
The coupling of SDS-PAGE and LC-MRM screening has been used to detect 876 peptides from 218 cancer-related proteins in model systems including colon, lung, melanoma, leukemias, and myeloma, which has led to the development of 95 quantitative assays including stable-isotope labeled peptide standards. Methods are published online and peptide standards are made available to the research community. Protein expression measurements for heat shock proteins, including a comparison with ELISA and monitoring response to the HSP90 inhibitor, 17-DMAG, are used to illustrate the components of the QuAD and its potential utility.
Conclusions and Clinical Relevance
This resource enables quantitative assessment of protein components of signaling pathways and biological processes and holds promise for systematic investigation of treatment responses in cancer.
doi:10.1002/prca.201000115
PMCID: PMC3530891  PMID: 21656910
Cancer Biology; LC-MRM; Pathways; Quantification; Signaling
16.  Absolute Quantification of Phosphorylation on the Kinase Activation Loop of Cellular Focal Adhesion Kinase by Stable Isotope Dilution Liquid Chromatography/Mass Spectrometry 
Analytical chemistry  2009;81(9):3304-3313.
A vital point of convergence for many signaling pathways at cellular focal adhesions is the interaction of two non-receptor tyrosine kinases, focal adhesion kinase (FAK) and Src. The binding of Src to FAK leads to the phosphorylation of Y576 and Y577, located within the activation loop domain of FAK. However, it has not been possible previously to determine the absolute quantitative relationship between phosphorylated and non-phosphorylated forms of this activation loop domain in cells undergoing normal metabolism. We have developed a stable isotope dilution liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) technique that allows such determinations to be made. Isotopically labeled and phosphorylated FAK protein standards were synthesized and used to control for loss during immunoprecipitation of FAK. A control tryptic peptide, representing an unmodified region of FAK, was employed to monitor the mass balance of post-translational modifications (PTMs) on the activation loop domain. Absolute quantification was conducted using stable isotope labeled peptide standards with four endogenous amino acid overhangs at the trypsin digestion sites of both the amino and carboxy terminus. The LC-MRM/MS method was rigorously validated using in vitro kinase assays and employed to conduct absolute quantification of FAK phosphorylation in normal mouse embryo fibroblasts (MEFs). This methodology will have particular utility for biomarker studies of kinase-inhibiting anti-cancer drugs and for quantitative proteomic investigations that examine kinase- and phosphatase-mediated cellular signal transduction pathways.
doi:10.1021/ac900204f
PMCID: PMC2706532  PMID: 19354260
17.  Development of a High-Sensitivity Targeted MRM Assay for Peptide and Protein Quantification 
Discovery phase proteomics has generated numerous candidate protein markers for a wide variety of biological processes and disease types. To assess the viability of these protein expression changes requires the analysis of a larger number of samples, preferably in a targeted fashion, and hence the use of MRM has become routine. Specific peptides from the proteins of interest are targeted as surrogate markers for that protein, in a screening assay using a triple quadrupole mass spectrometer operating in the multiple reaction monitoring (MRM) mode. The MRM method which is used to detect specific ions from target molecules has the capability to simultaneously quantify large numbers of proteins with good limits of quantification (LOQ) and linear dynamic range. In this mode of analysis the sensitivity and dynamic range are improved and providing sufficient data points across a chromatographic peak are recorded then quantitation is accurate (CV 5-10%). This high sensitivity coupled with the specificity/selectivity afforded by MRM transitions allows extensive panels of peptide biomarkers to be monitored in a single experiment from complex mixtures. We will describe the development and implementation of novel high-sensitivity MRM assays for large scale peptide quantification.
PMCID: PMC3186638
18.  Yale Protein Expression Database 2.0 
The Yale Protein Expression Database (YPED) (Shifman et. al. 2007) was developed as open source web-accessible software system for discovery and protein profiling data management. We have since expanded the software by adding a suite of tools for new protein profiling technologies, post-translational modifications, targeted proteomics, and data dissemination. The first set of tools enables us to integrate SILAC and label-free quantitation data into YPED. The second set of tools aid in the identification and site-localization of phosphopeptides. The third set were developed as a complete targeted proteomics workflow which utilizes a custom peptide spectral library database to facilitate peptide and MRM transition selection for global targeted proteomic analysis, tools for MRM method export, and an interface for collation of quantitation data results and review. Our final efforts have added a public data repository to YPED which enables the release of curated proteomic datasets for public download as either open source raw data files or Excel spreadsheets.
PMCID: PMC3630593
19.  Restructuring proteomics through verification 
Biomarkers in medicine  2010;4(6):799-803.
Proteomics technologies have revolutionized cell biology and biochemistry by providing powerful new tools to characterize complex proteomes, multiprotein complexes and post-translational modifications. Although proteomics technologies could address important problems in clinical and translational cancer research, attempts to use proteomics approaches to discover cancer biomarkers in biofluids and tissues have been largely unsuccessful and have given rise to considerable skepticism. The National Cancer Institute has taken a leading role in facilitating the translation of proteomics from research to clinical application, through its Clinical Proteomic Technologies for Cancer. This article highlights the building of a more reliable and efficient protein biomarker development pipeline that incorporates three steps: discovery, verification and qualification. In addition, we discuss the merits of multiple reaction monitoring mass spectrometry, a multiplex targeted proteomics platform, which has emerged as a potentially promising, high-throughput protein biomarker measurements technology for preclinical ‘verification’.
doi:10.2217/bmm.10.92
PMCID: PMC3041639  PMID: 21133699
biomarker; multiple reaction monitoring mass spectrometry; proteomics; verification
20.  P202-S Expanding the Capabilities of Peptide MRM-Based Assays in Plasma Using a Hybrid Triple-Quadrupole Linear Ion-Trap Mass Spectrometer 
As the study of protein biomarkers increases in importance, technical limitations to the detection of low-abundance proteins and high-throughput, high-precision quantitation remain to be overcome. The complexity and dynamic range of the plasma proteome makes the task of specific, quantitative detection even more challenging. Multiple reaction monitoring (MRM) capabilities of triple quadrupole MS systems have been explored as solutions to this challenge due to their well-known sensitivity and selectivity for components in complex matrices such as plasma. Recently, a suite of >100 MRMs representing ~50 plasma protein markers were monitored quantitatively in a single assay using the MRM-based technique showing detection of proteins down to the level of L-selectin (~1μg/mL) with minimal sample preparation and no peptide or protein standards for most of the plasma protein markers.1
As more extensive candidate biomarker panels are being identified, MRM assays will need to be more rapidly developed to verify the expression changes of these proteins across larger clinical sample sets. To do this, the unique combination of triple-quadrupole and ion-trapping capabilities of the hybrid triple quadrupole–linear ion trap mass spectrometer have been utilized. A strategy for rapid MRM assay development for larger-scale profiling and qualification of biomarker candidates without having to first prepare synthetic peptide standards is currently being investigated and involves a chemical labeling strategy to create global reference standards to enable quantitative comparisons between clinical samples. Single assays consisting of ~500s of MRM transitions have been developed for this rapid qualification phase, facilitated by intelligent use of retention time windows during an LC analysis, while maintaining an optimum number of data points for improved precision of peak area and quantitative profiling. This presentation will demonstrate the details of this workflow with human plasma examples.
PMCID: PMC2291921
21.  Probing Advantages of Different Selectivity Strategies for Targeted Quantitative Proteomics 
INTRODUCTION: There has been an exponential increase in the number of ‘potential’ protein biomarkers discovered; thus requiring the need for better quantification strategies to confirm or refute their ultimate utility. Also required is increased throughput which means reduced sample preparation and/or accelerated chromatography which increases the chance of interferences that could confound robust quantification. The purpose of this study is to explore a range of new MS analysis methodologies that enable higher selectivity quantification. The different techniques rely on different properties of the molecule for specificity so their utility will depend to a large degree on the target molecules. But an exploration to determine some general guidelines will be helpful when choosing the best strategy. In this study, we compare the quantification of tryptic peptides in complex biological matrices using various strategies including combinations of sample preparation and mass spectrometric methodologies on different mass spectrometric platforms. EXPERIMENTAL METHODS: The intact or digested BNP was spiked into the crashed plasma to create calibration curves. An AB SCIEX QTRAP® 5500 system equipped with Turbo V™ source was used. Multiple reaction monitoring (MRM) transitions and MRM3 experiments for intact and digested BNP were developed and used to measure the calibration curves. For the differential mobility separations, a QTRAP 5500 system equipped with SelexION™ Technology was used. RESULTS: Three quantitative methodologies were used with the QTRAP® 5500 System: MRM provides selectivity based on the fragmentation of the peptide and monitoring of a specific product ion. When matrix interference is a problem with MRM, further selectivity can be performed using MRM3, which provides a second level of selectivity based on monitoring a secondary product ion. Alternatively, the differential mobility separation (DMS) system which provides selectivity based on the mobility of the various chemicals in the sample can also be used. Intact BNP provided good fragmentation for MS/MS and MS3, thus best sensitivity was obtained using MRM3 or MRM. However, for large peptides which do not fragment well, SIM (single ion monitoring) using DMS may be an alternative methodology for quantification.
PMCID: PMC3630610
22.  Review of Software Tools for Design and Analysis of Large scale MRM Proteomic Datasets 
Methods (San Diego, Calif.)  2013;61(3):287-298.
Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow.
doi:10.1016/j.ymeth.2013.05.004
PMCID: PMC3775261  PMID: 23702368
Targeted proteomics; multiple reaction monitoring; database; bioinformatics; mass spectrometry
23.  Mass spectrometry quantification of clusterin in the human brain 
Background
The multifunctional glycoprotein clusterin has been associated with late-onset Alzheimer’s disease (AD). Further investigation to define the role of clusterin in AD phenotypes would be aided by the development of techniques to quantify level, potential post-translational modifications, and isoforms of clusterin. We have developed a quantitative technique based on multiple reaction monitoring (MRM) mass spectrometry to measure clusterin in human postmortem brain tissues.
Results
A stable isotope-labeled concatenated peptide (QconCAT) bearing selected peptides from clusterin was expressed with an in vitro translation system and purified. This clusterin QconCAT was validated for use as an internal standard for clusterin quantification using MRM mass spectrometry. Measurements were performed on the human postmortem frontal and temporal cortex from control and severe AD cases. During brain tissues processing, 1% SDS was used in the homogenization buffer to preserve potential post-translational modifications of clusterin. However, MRM quantifications in the brain did not suggest phosphorylation of Thr393, Ser394, and Ser396 residues reported for clusterin in serum. MRM quantifications in the frontal cortex demonstrated significantly higher (P < 0.01) level of clusterin in severe AD group (39.1 ± 9.1 pmol/mg tissue protein) in comparison to control group (25.4 ± 4.4 pmol/mg tissue protein). In the temporal cortex, the clusterin levels were not significantly different, 29.0 ± 7.9 pmol/mg tissue protein and 28.0 ± 8.4 pmol/mg tissue protein in control and severe AD groups, respectively.
Conclusions
The proposed protocol is a universal quantitative technique to assess expression level of clusterin. It is expected that application of this protocol to quantification of various clusterin isoforms and potential post-translational modifications will be helpful in addressing the role of clusterin in AD.
doi:10.1186/1750-1326-7-41
PMCID: PMC3470951  PMID: 22906254
Clusterin; QconCAT; Multiple reaction monitoring; Human brain; Alzheimer’s disease
24.  Mass Spectrometric Immunoassay and Multiple Reaction Monitoring as Targeted MS-based Quantitative Approaches in Biomarker Development: Potential Applications to Cardiovascular Disease and Diabetes 
Type 2 diabetes (T2DM) is an important risk factor for cardiovascular disease (CVD)—the leading cause of death in the US. Yet not all subjects with T2DM are at equal risk for CVD complications; the challenge lies in identifying those at greatest risk. Therapies directed towards treating conventional risk factors have failed to significantly reduce this residual risk in T2DM patients. Thus newer targets and markers are needed for the development and testing of novel therapies. Herein we review two complementary mass spectrometry-based approaches—Mass Spectrometric Immunoassay (MSIA) and tandem mass spectrometry as multiple reaction monitoring (MRM)—for the analysis of plasma proteins and post translational modifications (PTMs) of relevance to T2DM and CVD. Together, these complementary approaches allow for high-throughput monitoring of many PTMs and the absolute quantification of proteins near the low picomolar range. In this review article, we discuss the clinical relevance of the HDL proteome and Apolipoprotein A-I PTMs to T2DM and CVD as well as provide illustrative MSIA and MRM data on high density lipoprotein (HDL) proteins from T2DM patients to provide examples of how these mass spectrometry approaches can be applied to gain new insight regarding cardiovascular risk factors. Also discussed are the reproducibility, interpretation and limitations of each technique with an emphasis on their capacities to facilitate the translation of new biomarkers into clinical practice.
doi:10.1002/prca.201200028
PMCID: PMC4029342  PMID: 23696124
Proteomics; HDL; Apolipoprotein A-I; Diabetes; Cardiovascular Disease
25.  Correlation between y-Type Ions Observed in Ion Trap and Triple Quadrupole Mass Spectrometers 
Journal of proteome research  2009;8(9):4243-4251.
Multiple reaction monitoring mass spectrometry (MRM-MS) is a technique for high-sensitivity targeted analysis. In proteomics, MRM-MS can be used to monitor and quantify a peptide based on the production of expected fragment peaks from the selected peptide precursor ion. The choice of which fragment ions to monitor in order to achieve maximum sensitivity in MRM-MS can potentially be guided by existing MS/MS spectra. However, because the majority of discovery experiments are performed on ion trap platforms, there is concern in the field regarding the generalizability of these spectra to MRM-MS on a triple quadrupole instrument. In light of this concern, many operators perform an optimization step to determine the most intense fragments for a target peptide on a triple quadrupole mass spectrometer. We have addressed this issue by targeting, on a triple quadrupole, the top six y-ion peaks from ion trap-derived consensus library spectra for 258 doubly charged peptides from three different sample sets and quantifying the observed elution curves. This analysis revealed a strong correlation between the y-ion peak rank order and relative intensity across platforms. This suggests that y-type ions obtained from ion trap-based library spectra are well-suited for generating MRM-MS assays for triple quadrupoles and that optimization is not required for each target peptide.
doi:10.1021/pr900298b
PMCID: PMC2802215  PMID: 19603825
multiple reaction monitoring (MRM); selective reaction monitoring (SRM); triple quadrupole; ion trap; mass spectrometer; y-ions; spectral library; spectral correlation

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