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.
Glioblastoma; Cancer Stem Cells; Label-free; Multiple Reaction Monitoring; Pathway Analysis
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.
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’.
biomarker; multiple reaction monitoring mass spectrometry; proteomics; verification
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.
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.
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.
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.
Cancer Biology; LC-MRM; Pathways; Quantification; Signaling
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.
multiple reaction monitoring (MRM); selective reaction monitoring (SRM); triple quadrupole; ion trap; mass spectrometer; y-ions; spectral library; spectral correlation
Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.
Multiple reaction monitoring mass spectrometry (MRM-MS); stable isotope dilution (SID); quantification; interference detection; limits of detection and quantification; intra- and interlaboratory precision
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.
Tandem Mass Spectrometry; Multiple Reaction Monitoring; Targeted Proteomics; Data Repository; Platelets
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.
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.
Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low µg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.
Protein quantification with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has emerged as a powerful platform for assessing panels of biomarkers. In this study, direct infusion, using automated, chip-based nanoelectrospray ionization, coupled with MRM (DI-MRM) is used for protein quantification. Removal of the LC separation step increases the importance of evaluating the ratios between the transitions. Therefore, the effects of solvent composition, analyte concentration, spray voltage, and quadrupole resolution settings on fragmentation patterns have been studied using peptide and protein standards. After DI-MRM quantification was evaluated for standards, quantitative assays for the expression of heat shock proteins (HSPs) were translated from LC-MRM to DI-MRM for implementation in cell line models of multiple myeloma. Requirements for DI-MRM assay development are described. Then, the two methods are compared; criteria for effective DI-MRM analysis are reported based on the analysis of HSP expression in digests of whole cell lysates. The increased throughput of DI-MRM analysis is useful for rapid analysis of large batches of similar samples, such as time course measurements of cellular responses to therapy.
Quantitative Mass Spectrometry; Direct Infusion; Multiple Reaction Monitoring Mass Spectrometry; Heat Shock Proteins; Multiple Myeloma
The utility of mass spectrometry (MS)-based proteomic analyses and their clinical applications have been increasingly recognized over the past decade due to their high sensitivity, specificity and throughput. MS-based proteomic measurements have been used in a wide range of biological and biomedical investigations, including analysis of cellular responses and disease-specific post-translational modifications. These studies greatly enhance our understanding of the complex and dynamic nature of the proteome in biology and disease. Some MS techniques, such as those for targeted analysis, are being successfully applied for biomarker verification, whereas others, including global quantitative analysis (for example, for biomarker discovery), are more challenging and require further development. However, recent technological improvements in sample processing, instrumental platforms, data acquisition approaches and informatics capabilities continue to advance MS-based applications. Improving the detection of significant changes in proteins through these advances shows great promise for the discovery of improved biomarker candidates that can be verified pre-clinically using targeted measurements, and ultimately used in clinical studies - for example, for early disease diagnosis or as targets for drug development and therapeutic intervention. Here, we review the current state of MS-based proteomics with regard to its advantages and current limitations, and we highlight its translational applications in studies of protein biomarkers.
biomarker; clinical proteomics; ion mobility separations; mass spectrometry; multiple reaction monitoring; selected reaction monitoring; shotgun proteomics; targeted proteomics; translational proteomics
Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.
multiple reaction monitoring (MRM); selective reaction monitoring (SRM); MRM transition; transition list; spectral library; mass spectrometry; targeted proteomics
Reaction monitoring mass spectrometry has emerged as a powerful tool for targeted detection and quantification of proteins in clinical samples. Here, we report the use of gel electrophoresis for protein fractionation and liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM) screening for quantitative analysis of components from the Wnt/β-catenin signaling pathway, which contributes to colon tumor formation and progression. In silico tools are used to design LC-MRM screens for each target protein. Following successful peptide detection, stable isotope labeled peptides are synthesized and developed as internal standards. Then, the assays are implemented in colon cancer cell lines to achieve detection in minimal amounts of cells, compatible with direct translation to clinical specimens. Selected assays are compared with qualitative results from immunoblotting (Westerns) and translated to individual frozen colon tissue sections and laser capture microdissected tumor cells. This LC-MRM platform has been translated from in vitro models to clinical specimens, forming the basis for future experiments in patient assessment.
Wnt/β-catenin signaling; colon cancer; frozen tissue; laser capture microdissection; liquid chromatography coupled to multiple reaction monitoring; biomarker assessment
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.
KRAS; GeLC-MRM; targeted proteomics; colorectal cancer; pancreatic cyst fluid
Selected reaction monitoring (SRM), sometimes called multiple reaction monitoring (MRM), is becoming the tool of choice for targeted quantitative proteomics in the plant science community. Key to a successful SRM experiment is prior identification of the distinct peptides for the proteins of interest and the determination of the so-called transitions that can be programmed into an LC-MS/MS to monitor those peptides. The transition for a given peptide comprises the intact peptide m/z and a high intensity product ion that can be monitored at a characteristic retention time (RT). To aid the design of SRM experiments, several online tools and databases have been produced to help researchers select transitions for their proteins of interest, but many of these tools are limited to the most popular model organisms such as human, yeast, and mouse or require the experimental acquisition of local spectral libraries. In this paper we present MRMaid1, a web-based SRM assay design tool whose transitions are generated by mining the millions of identified peptide spectra held in the EBI’s PRIDE database. By using data from this large public repository, MRMaid is able to cover a wide range of species that can increase as the coverage of PRIDE grows. In this paper MRMaid transitions for 25 Arabidopsis thaliana proteins are evaluated experimentally, and found capable of quantifying 23 of these proteins. This performance was found to be comparable with the more time consuming approach of designing transitions using locally acquired orbitrap data, indicating that MRMaid is a valuable tool for targeted Arabidopsis proteomics.
selected reaction monitoring; multiple reaction monitoring; proteomics; transition; database; Arabidopsis; experimental design
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.
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.
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.
Clusterin; QconCAT; Multiple reaction monitoring; Human brain; Alzheimer’s disease
Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.
measurement of proteins is one of the most fundamental analytical
tasks in a biochemistry laboratory, but widely used immunochemical
methods often have limited specificity and high measurement variation.
In this review, we discuss applications of multiple-reaction monitoring
(MRM) mass spectrometry, which allows sensitive, precise quantitative
analyses of peptides and the proteins from which they are derived.
Systematic development of MRM assays is permitted by databases of
peptide mass spectra and sequences, software tools for analysis design
and data analysis, and rapid evolution of tandem mass spectrometer
technology. Key advantages of MRM assays are the ability to target
specific peptide sequences, including variants and modified forms,
and the capacity for multiplexing that allows analysis of dozens to
hundreds of peptides. Different quantitative standardization methods
provide options that balance precision, sensitivity, and assay cost.
Targeted protein quantitation by MRM and related mass spectrometry
methods can advance biochemistry by transforming approaches to protein
HDL carries a rich protein cargo and examining HDL protein composition promises to improve our understanding of its functions. Conventional mass spectrometry methods can be lengthy and difficult to extend to large populations. In addition, without prior enrichment of the sample, the ability of these methods to detect low abundance proteins is limited. Our objective was to develop a high-throughput approach to examine HDL protein composition applicable to diabetes and cardiovascular disease (CVD).
We optimized two multiplexed assays to examine HDL proteins using a quantitative immunoassay (Multi-Analyte Profiling- MAP) and mass spectrometric-based quantitative proteomics (Multiple Reaction Monitoring-MRM). We screened HDL proteins using human xMAP (90 protein panel) and MRM (56 protein panel). We extended the application of these two methods to HDL isolated from a group of participants with diabetes and prior cardiovascular events and a group of non-diabetic controls.
We were able to quantitate 69 HDL proteins using MAP and 32 proteins using MRM. For several common proteins, the use of MRM and MAP was highly correlated (p < 0.01). Using MAP, several low abundance proteins implicated in atherosclerosis and inflammation were found on HDL. On the other hand, MRM allowed the examination of several HDL proteins not available by MAP.
MAP and MRM offer a sensitive and high-throughput approach to examine changes in HDL proteins in diabetes and CVD. This approach can be used to measure the presented HDL proteins in large clinical studies.
High density lipoprotein; Proteomics; Multiple reaction monitoring; Multi-analyte panel; Diabetes; Cardiovascular disease
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.
Sweat; Proteome; Schizophrenia; Biomarkers; LC-MS/MS; MRM
We compared the reproducibility of multiple reaction
(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.
formalin-fixed; paraffin-embedded tissue; multiple
reaction monitoring; breast cancer; biomarkers; HER2
Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this “fit-for-purpose” approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations.
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.