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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.

Introduction: Cancer vaccine therapies rely on accurate personalized selection of immunizing peptides in order to potentiate tumor-specific immune responses against neoepitopes derived from somatic mutations. Given the unique accumulation of mutations in each tumor as well as the patient’s particular complement of HLA class I alleles, the ability to accurately predict which epitopes will be presented by tumor cells is a fundamental prerequisite for successful vaccine design. By utilizing a mono-allelic mass spectrometry (MS) strategy for profiling the endogenous HLA class I peptidome, we recently showed that prediction of endogenous presentation can be drastically improved when model training integrates peptide sequence along with intracellular signals such as likelihood of proteasomal processing and peptide abundance. Yet the limited set of mono-allelic data did not allow for deep comparative analysis across HLA- A, B, and C alleles, which can better inform pan-allele predictor design. Moreover, the significant variability in per-allele model performance remains unexplained. Methods: We recently developed a scalable mono-allelic MS technique to profile naturally presented peptides on HLA molecules, whereby the HLA class I deficient B721.221 cell line is transfected with HLA expression vectors coding for a single allele of interest and eluted HLA peptides are analyzed by LC-MS/MS. In addition, endogenously presented antigens on primary tumor-derived cell lines from 4 melanoma patients were also identified via MS. To extract knowledge from this unique dataset, we implemented computational tools to summarize, visualize, and compare the characteristics of HLA- A, B, C, and G alleles and developed a novel approach to define allele similarity that takes into account the collection of sub-motifs per allele. We trained neural network prediction models, validated their performance on internal and external datasets, and analyzed the variability in performance across alleles. Results: To date, we have generated binding data for 92 HLA- A, B, C and G alleles, identifying more than 190,000 peptides and covering the most frequent alleles in the population. Extensive mono-allelic profiling revealed that some alleles present non-9-mer peptides with high frequency. The availability of large number of non-9-mer peptides allowed us to build length-specific models that often performed better than the corresponding non-length-specific models currently used. We observe that HLA- A and B alleles present more peptides of length 10 and 11 than C alleles, while C alleles have a higher propensity for 8-mers. Correlation-based analysis of binding motifs revealed that HLA-A and B motifs are more specific whereas C motifs are less stringent and thus share more overlapping binders. Since binding data are available only for a fraction of all known alleles, pan-allele models implicitly embed allele similarity to predict for uncharacterized alleles based on the sequence of the binding pocket. By clustering allele-specific peptides into sub-motifs, we propose a novel explicit approach to delineate allele similarity at finer granularity that can improve pan-allele model design. We show that our allele-specific models are better at discriminating tumor-presented epitopes than state of the art predictors and investigate the relationship between false discovery rate and natural abundance of anchor residues to better understand differences in model accuracy amongst alleles. Finally, deconvolution of tumor-presented peptides demonstrated that ~10% of peptides are presented on HLA-C, which has been historically understudied. Conclusions: We have vastly expanded the collection of endogenous HLA-specific peptides deriving biologic insights into the principles of epitope presentations and valuable considerations for prediction model design and epitope selection for tumor vaccines. Citation Format: Siranush Sarkizova, Susan Klaeger, Derin B. Keskin, Karl Clauser, Hasmik Keshishian, Christina R. Hartigan, Nir Hacohen, Steven A. Carr, Catherine J. Wu. Broad analysis and more accurate predictions of HLA class I epitope binding in 92 common HLA alleles profiled by mono-allelic mass spectrometry [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B042.

Pharmacologic agents that induce protein degradation represent an emerging and important class of therapeutic agents. Thalidomide and thalidomide derivatives (TDs) function by bringing target proteins and the E3 ubiquitin ligase substrate adaptor CRBN into proximity leading to ubiquitination and proteasomal degradation of critical oncoproteins. While highly effective, most patients eventually develop resistance to these agents, though the mechanisms by which this occurs and why some patients respond to different drugs within the class remains largely unknown. One major impediment to monitoring these drugs' activity is the need to quantitatively measure multiple protein targets simultaneously. To overcome this issue, we have developed a novel targeted mass spectrometry (MS) assay to measure the levels of CRBN, 8 substrate proteins that are degraded in the presence of TDs (IKZF1, IKZF3, CK1α, ZFP91, RNF166, ZNF692, GSPT1 and GSPT2), and 2 housekeeping control proteins (β-actin and GAPDH). This assay exhibits several advantages over currently used methodologies in that it is quantitatively precise and multiplexed for high throughput, allowing for sensitive detection of a panel of proteins from a single sample. The precision of quantitation of our MS assay enabled us to investigate the relationship between substrate level and drug-mediated degradation by measuring all known substrates in dense time course experiments following treatment of MM1S cells with lenalidomide. These experiments revealed that substrates are degraded in an ordered fashion with IKZF1 and IKZF3 being degraded before CK1α and ZFP91, suggesting that substrates may compete for access to CRBN. To test this directly we overexpressed either RNF166 or ZNF692, two recently identified substrates, in MM1S cells, which led to lenalidomide resistance. This resistance was not mediated by any direct cellular dependence on these proteins but instead was due to their competition for binding to CRBN leading to diminished degradation of other essential lenalidomide targets, IKZF1, IKZF3, and CK1α. Thus, increased expression of proteins capable of interacting with CRBN represents a novel potential mechanism of resistance to this class of drugs. CRBN is essential for lenalidomide-mediated degradation of substrates and sensitivity to drug. Quantitative detection of CRBN in our MS assay enabled us to study the effect of changes in CRBN levels on the activity of TDs. Loss of CRBN led to decreased degradation of all substrates and resistance, whereas overexpression of CRBN augmented degradation of all substrates leading to increased sensitivity to lenalidomide in MM1S cells. In a panel of ten MM cell lines CRBN level correlated with increased substrate degradation and was a significant determinant of differential sensitivity to lenalidomide. These findings demonstrate that CRBN is a limiting factor for both degradation of substrates and sensitivity to TDs. Finally, we took advantage of the high throughput nature of our MS assay and generated dense dose response and kinetic curves for 3 additional TDs (pomalidomide, avadomide and CC-885) in MM1S cells. By combining this with in vivo binding data we have created a detailed map of substrate binding, degradation and order of interaction for each TD. Among other findings, these data demonstrate that lenalidomide differs from pomalidomide and avadomide in that it is a superior degrader of CK1α but inferior at degrading IKZF3 and ZFP91, features that likely underlie some of the differential clinical activity and disease specificity of these agents. In sum, we have developed a highly sensitive, multiplexed quantitative MS assay allowing us to characterize the biochemical activity of TDs in unprecedented detail. Using this assay we show that substrates compete for access to a limiting pool of CRBN and identify a novel mechanism of resistance. The modularity of our assay allows for the detection of new substrates as they are discovered or reconfiguration of the assay to study other degraders. Future translation of this assay to clinical samples will facilitate accurate monitoring of pharmacodynamic activity and elucidation of mechanisms of resistance in vivo. Disclosures Munshi: OncoPep: Other: Board of director.

Recent advances in mass spectrometry have led to in-depth characterization of both tissue and cellular acetylation profiles (or “acetylomes”). These studies reveal the abundance and importance of this post-translational modification not only in transcriptional control, but also in many signaling and metabolic pathways. In the heart, acetylation has been found to play a role in cardiac proliferation, differentiation, and hypertrophy in both developmental and pathological settings. To examine the role of acetylation in exercise-induced cardiac hypertrophy, we studied the expression of enzymes regulating these processes and then undertook a comprehensive proteomic analysis of cardiac proteome and acetylome in hearts from sedentary and exercised mice. We first characterized the expression profiles of 8 acetylases (MYST1-4, GCN5, PCAF, EP300, CREBBP) and 18 deacetylases (HDAC1-11 and SIRT1-7) in four different exercise protocols, including swimming, voluntary wheel run, acute treadmill run, and long-term treadmill run in aged mice. Then, using a proteomics workflow with greater sensitivity and higher coverage recently developed at the Broad Institute, we determined the acetylome of the swim exercised mouse heart (n=5) in comparison to sedentary animals (n=4). We concurrently assessed proteome and phospho-proteome profiles in the same set of samples. Confirmation of the presence of physiological hypertrophy and increased cardiac function with exercise was determined with echocardiography and morphometric analysis. With this method, we identified 4159 acetylation sites and 19,402 phosphorylation sites on 6615 proteins. Acetylated proteins were found to be involved in a diverse array of processes, but most prominently in metabolism and muscle contraction. Phospho-proteome analysis has highlighted the interplay and crosstalk between acetylation and phosphorylation. In summary, the cardiac acetylome is dynamically regulated by exercise and demonstrates major alterations in metabolic pathways. Understanding how physiological hypertrophy affects acetylation and the activity of downstream factors may provide novel insights into the cardioprotective role of exercise.

Accurate predictive algorithms have required elucidation of HLA-peptide binding motifs from extensive HLA binding peptide ligand databases. Historically, however, little attention has been paid to HLA-C because of its perceived lower surface expression, even as newer studies have identified important HLA-C restricted viral epitopes. Robust predictive algorithms for HLA-C are thus lacking and yet, if improved, could markedly expand the spectrum of immune targets contributing to protective immune responses. We generated 21 distinct single HLA-C allele-expressing cell lines and subjected them to immunoaffinity purification and MS-based sequencing. From 33851 peptides identified from the 21 HLA-C expressing cell lines, we discovered novel anchor motifs. These data were used to train machine-learning algorithms to generate an accurate and novel HLA-C epitope prediction tool. Finally, we used our novel algorithm to predict HLA-C restricted neo-epitopes out of tumor biopsies.

Background: Multiple reaction monitoring mass spectrometry (MRM-MS) of peptides with stable isotope–labeled internal standards (SISs) is increasingly being used to develop quantitative assays for proteins in complex biological matrices. These assays can be highly precise and quantitative, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. Methods: The algorithm objectively evaluates MRM-MS data with 2 orthogonal approaches. First, it compares the relative product ion intensities of the analyte peptide to those of the SIS peptide and uses a t-test to determine if they are significantly different. A CV is then calculated from the ratio of the analyte peak area to the SIS peak area from the sample replicates. Results: The algorithm identified problematic transitions and achieved accuracies of 94%–100%, with a sensitivity and specificity of 83%–100% for correct identification of errant transitions. The algorithm was robust when challenged with multiple types of interferences and problematic transitions. Conclusions: This algorithm for automated detection of inaccurate and imprecise transitions (AuDIT) in MRM-MS data reduces the time required for manual and subjective inspection of data, improves the overall accuracy of data analysis, and is easily implemented into the standard data-analysis work flow. AuDIT currently works with results exported from MRM-MS data-processing software packages and may be implemented as an analysis tool within such software.

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 mug/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.

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.

Biomarker discovery produces lists of candidate markers whose presence and level must be subsequently verified in serum or plasma. Verification represents a paradigm shift from unbiased discovery approaches to targeted, hypothesis-driven methods and relies upon specific, quantitative assays optimized for the selective detection of target proteins. Many protein biomarkers of clinical currency are present at or below the nanogram/milliliter range in plasma and have been inaccessible to date by MS-based methods. Using multiple reaction monitoring coupled with stable isotope dilution mass spectrometry, we describe here the development of quantitative, multiplexed assays for six proteins in plasma that achieve limits of quantitation in the 1–10 ng/ml range with percent coefficients of variation from 3 to 15% without immunoaffinity enrichment of either proteins or peptides. Sample processing methods with sufficient throughput, recovery, and reproducibility to enable robust detection and quantitation of candidate biomarker proteins were developed and optimized by addition of exogenous proteins to immunoaffinity depleted plasma from a healthy donor. Quantitative multiple reaction monitoring assays were designed and optimized for signature peptides derived from the test proteins. Based upon calibration curves using known concentrations of spiked protein in plasma, we determined that each target protein had at least one signature peptide with a limit of quantitation in the 1–10 ng/ml range and linearity typically over 2 orders of magnitude in the measurement range of interest. Limits of detection were frequently in the high picogram/milliliter range. These levels of assay performance represent up to a 1000-fold improvement compared with direct analysis of proteins in plasma by MS and were achieved by simple, robust sample processing involving abundant protein depletion and minimal fractionation by strong cation exchange chromatography at the peptide level prior to LC-multiple reaction monitoring/MS. The methods presented here provide a solid basis for developing quantitative MS-based assays of low level proteins in blood.

Interleukin-1 stimulation leads to the recruitment of MyD88, interleukin-1 receptor-associated kinase 1 (IRAK-1) and interleukin-1 receptor-associated kinase 4 (IRAK-4) to the IL-1 receptor. The formation of the IL-1 receptor complex triggers a series of IRAK-1 autophosphorylations, which result in activation. IRAK-4 is upstream of IRAK-1 and may act as IRAK-1 kinase to transmit the signal. To date, there is no upstream kinase reported for IRAK-4; the activation mechanism of IRAK-4 remains poorly understood. Here, for the first time, we report three autophosphorylation sites that are responsible for IRAK-4 kinase activity. LC–MS/MS analysis has identified phosphorylations at T342, T345, and S346, which reside within the activation loop. Site-directed mutants at these positions exhibit significant reductions in the catalytic activity of IRAK-4 (T342A: 57%; T345A: 66%; S346A: 50%). The absence of phosphorylation in kinase-dead IRAK-4 indicates that phosphorylations in the activation loop result from autophosphorylation rather than from phosphorylation by an upstream kinase. Finally, we demonstrate that autophosphorylation is an intramolecular event as wild-type IRAK-4 failed to transphosphorylate kinase-inactive IRAK-4. The present data indicate that the kinase activity of IRAK-4 is dependent on the autophosphorylations at T342, T345, and S346 in the activation loop.

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was

Background: We recently applied a liquid chromatography tandem mass spectrometry (LC-MS/MS) based proteomics platform to plasma samples from individuals undergoing a “planned” myocardial infarction (PMI; alcohol ablation for hypertrophic cardiomyopathy) and identified acyl-CoA binding protein (ACBP) as a potential circulating biomarker of myocardial injury. ACBP is a 10 kDa intracellular protein that is highly expressed in cells with a high turn-over of fatty acids such as cardiomyocytes. We sought to determine the site of ACBP release and whether ischemia alone is sufficient to trigger an increment in plasma levels in humans. Methods: Coronary sinus (CS) and peripheral venous samples were obtained simultaneously from PMI patients; peripheral venous samples were obtained from derivation/validation cohorts of subjects undergoing cardiac stress testing. Plasma ACBP levels were measured by immunoassay. Results: In PMI patients (n=11), pre-injury levels of ACBP were comparable in the CS and peripheral samples. As early as 10 min after PMI, ACBP levels were 27% higher in the CS than in the periphery (P = 0.01), and remained 30% higher at 60 minutes (P = 0.02). Next, we studied 105 patients undergoing cardiac stress testing, 52 of whom demonstrated inducible ischemia (cases) and 53 of whom did not (controls). Baseline ACBP levels were comparable in cases and controls. Changes in median ACBP levels after the exercise stress challenge were significantly greater in the ischemic patients (cases) than in the controls (22% increase in cases; 1% decrease in controls; P = 0.0001), findings which were validated in a second cohort of 101 patients subjects (P = 0.002). These findings remained significant in a multivariable model adjusting for age, male sex, diabetes, BMI, smoking, creatinine, hypercholesterolemia, and total minutes of exercise. By contrast, the effects of exercise on established biomarkers (cTnI, NT-proBNP and FABP) did not differ betwen cases and controls. Conclusions: We provide initial verification that ACBP is rapidly released from the injured heart and increases in response not only to infarction but also ischemia. These findings motivate additional clinical studies of this novel biomarker in heterogeneous patient cohorts.

Liquid chromatography–multiple reaction monitoring mass spectrometry (LC-MRM-MS) of plasma that has been depleted of abundant proteins and fractionated at the peptide level into six to eight fractions is a proven method for quantifying proteins present at low nanogram-per-milliliter levels. A drawback of fraction-MRM is the increased analysis time due to the generation of multiple fractions per biological sample. We now report that the use of heated, long, fused silica columns (>30 cm) packed with 1.9 μm of packing material can reduce or eliminate the need for fractionation prior to LC-MRM-MS without a significant loss of sensitivity or precision relative to fraction-MRM. We empirically determined the optimal column length, temperature, gradient duration, and sample load for such assays and used these conditions to study detection sensitivity and assay precision. In addition to increased peak capacity, longer columns packed with smaller beads tolerated a 4- to 6-fold increase in analyte load without a loss of robustness or reproducibility. The longer columns also provided a 4-fold improvement in median limit-of-quantitation values with increased assay precision relative to the standard 12 cm columns packed with 3 μm material. Overall, the optimized chromatography provided an approximately 3-fold increase in analysis throughput with excellent robustness and less than a 2-fold reduction in quantitative sensitivity relative to fraction-MRM. The value of the system for increased multiplexing was demonstrated by the ability to configure an 800-plex MRM-MS assay, run in a single analysis, comprising 2400 transitions with retention time scheduling to monitor 400 unlabeled and heavy labeled peptide pairs.

Novel analytical techniques are demanded in parallel in the automated combinatorial library syntheses for accelerating the process of drug discovery. In this study, the integration of matrix-assist...

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.

available in PMC 2012 January 1., In animal cells, growth factors coordinate cell proliferation and survival by regulating the phosphoinositide 3-kinase/Akt signaling pathway. Deregulation of this signaling pathway is common in a variety of human cancers. The PI3K-dependent signaling kinase complex defined as mammalian target of rapamycin complex 2 (mTORC2) functions as a regulatory Ser-473 kinase of Akt. We find that activation of mTORC2 by growth factor signaling is linked to the specific phosphorylation of its component rictor on Thr-1135. The phosphorylation of this site is induced by the growth factor stimulation and expression of the oncogenic forms of ras or PI3K. Rictor phosphorylation is sensitive to the inhibition of PI3K, mTOR, or expression of integrin-linked kinase. The substitution of wild-type rictor with its specific phospho-mutants in rictor null mouse embryonic fibroblasts did not alter the growth factor–dependent phosphorylation of Akt, indicating that the rictor Thr-1135 phosphorylation is not critical in the regulation of the mTORC2 kinase activity. We found that this rictor phosphorylation takes place in the mTORC2-deficient cells, suggesting that this modification might play a role in the regulation of not only mTORC2 but also the mTORC2-independent function of rictor. Mol Cancer Res; 8(6); 896–906., University of Texas M.D. Anderson Cancer Center (Fellow Trust fund), American Cancer Society (M.D. Anderson Cancer Center Breast Specialized Programs of Research Excellence (RSG-09-026-01CCG01)), National Institutes of Health (U.S.) (NIH grant CA133522), National Institutes of Health (U.S.) (NIH grant AI104389)

Verification of candidate biomarkers requires specific assays to selectively detect and quantify target proteins in accessible biofluids. The primary objective of verification is to screen potential biomarkers to ensure that only the highest quality candidates from the discovery phase are taken forward into preclinical validation. Because antibody reagents for a clinical grade immunoassay often exist for a small number of candidates, alternative methodologies are required to credential new and unproven candidates in a statistically viable number of serum or plasma samples. Using multiple reaction monitoring coupled with stable isotope dilution MS, we developed quantitative, multiplexed assays in plasma for six proteins of clinical relevance to cardiac injury. The process described does not require antibodies for immunoaffinity enrichment of either proteins or peptides. Limits of detection and quantitation for each signature peptide used as surrogates for the target proteins were determined by the method of standard addition using synthetic peptides and plasma from a healthy donor. Limits of quantitation ranged from 2 to 15 ng/ml for most of the target proteins. Quantitative measurements were obtained for one to two signature peptides derived from each target protein, including low abundance protein markers of cardiac injury in the nanogram/milliliter range such as the cardiac troponins. Intra- and interassay coefficients of variation were predominantly

Background: Protein biomarker candidates from discovery proteomics must be quantitatively verified in patient samples before they can progress to clinical validation. Here we demonstrate that peptide immunoaffinity enrichment coupled with stable isotope dilution mass spectrometry (SISCAPA-MRM) can be used to configure assays with performance suitable for candidate biomarker verification. As proof of principle, we configured SISCAPA assays for troponin I (cTnI), an established biomarker of cardiac injury, and interleukin 33 (IL-33), an emerging immunological and cardiovascular marker for which robust immunoassays are currently not available. Methods: We configured individual and multiplexed assays in which peptides were enriched from digested human plasma using antipeptide antibodies. Assay performance was established using response curves for peptides and proteins spiked into normal plasma. We quantified proteins using labeled peptides as internal standards, and we measured levels of cTnI in patients who underwent a planned myocardial infarction for hypertrophic obstructive cardiomyopathy. Results: Measurement of cTnI and IL-33 proteins from trypsin-digested plasma was linear from 1.5 to 5000 μg/L, with imprecision Conclusions: We used an established biomarker of cardiac injury and an emerging biomarker to demonstrate how SISCAPA can detect and quantify changes in concentration of proteins present at 1–10 μg/L in plasma. Our results demonstrate that these assays can be multiplexed and retain the necessary precision, reproducibility, and sensitivity to be applied to new and uncharacterized candidate biomarkers for verification of low-abundance proteins in blood. .

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.

Emerging metabolomic tools have created the opportunity to establish metabolic signatures of myocardial injury. We applied a mass spectrometry–based metabolite profiling platform to 36 patients undergoing alco-hol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of planned myo-cardial infarction (PMI). Serial blood samples were obtained before and at various intervals after PMI, with patients undergoing elective diagnostic coronary angiography and patients with spontaneous myocardial infarction (SMI) serving as negative and positive controls, respectively. We identified changes in circulating levels of metabolites participating in pyrimidine metabolism, the tricarboxylic acid cycle and its upstream con-tributors, and the pentose phosphate pathway. Alterations in levels of multiple metabolites were detected as early as 10 minutes after PMI in an initial derivation group and were validated in a second, independent group of PMI patients. A PMI-derived metabolic signature consisting of aconitic acid, hypoxanthine, trimethylamine N-oxide, and threonine differentiated patients with SMI from those undergoing diagnostic coronary angiogra-phy with high accuracy, and coronary sinus sampling distinguished cardiac-derived from peripheral metabolic changes. Our results identify a role for metabolic profiling in the early detection of myocardial injury and sug-gest that similar approaches may be used for detection or prediction of other disease states.