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Prostate cancer (PCa) is the second leading cause of male cancer-related deaths in the United States. The pre-mature forms of prostate-specific antigen (PSA), proPSA, were shown to be associated with PCa. However, there is a technical challenge in the development of antibody-based immunoassays for specific recognition of each individual proPSA isoform. Herein, we report the development of highly specific, antibody-free, targeted mass spectrometry assays for simultaneous quantification of [-2], [-4], [-5], and [-7] proPSA isoforms in voided urine. The newly developed proPSA assays capitalize on Lys-C digestion to generate surrogate peptides with appropriate length (9-16 amino acids) along with long-gradient liquid chromatography separation. The assay utility of these isoform markers was evaluated in a cohort of 30 well-established clinical urine samples for distinguishing PCa patients from healthy controls. Under the 95% confidence interval, the combination of [-2] and [-4] proPSA isoforms yields the area under curve (AUC) of 0.86, and the AUC value for the combined all four isoforms was calculated to be 0.85. We have further verified [-2]proPSA, the dominant isoform, in an independent cohort of 34 clinical urine samples. Validation of proPSA isoforms in large-scale cohorts is needed to demonstrate their potential clinical utility.

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While the routine mitochondrial extraction and isolation protocols have not fundamentally changed since the introduction of density gradients, the approaches we use to examine the proteome have. The initial characterisation of mitochondrial proteomes was carried out using two-dimensional gel electrophoresis in 2001 and gel spot mass spectrometry have now largely been superseded as the throughput and sensitivity of commercial mass spectrometers increases. Whist many of these early studies established the components of the mitochondrial proteome, as gels were replaced by gel free approaches the numbers of confirmed components rapidly increased. In this chapter we present gel-based approaches for the separation and concentration of mitochondrial proteins for their characterization by mass spectrometry. We also describe two gel-free approaches which can be used to quantity the degree of contamination arising during the isolation of mitochondria. These approaches are equally suitable for studies comparing one treatment to another.

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Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I-II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes.

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Metallothioneins (MTs) are crucial for metal ion homeostasis in mammalian cells. Specialized mass spectrometry methods have been developed to detect MTs in tissue extracts, though facile methods with scalable throughput are lacking. To improve analytical throughput and repeatability, we developed a standardised liquid chromatography tandem mass spectrometry (LC-MS/MS) method for robust determination of metallothionein-3 (MT3) that is amenable to microplate processing. This method uses standard protein digestion conditions with commercially available reagents and commonly practiced reversed-phase chromatography, detecting MT3 at low ng/mL levels in human brain tissue extracts. We found that trypsin digestion largely underestimated MT3 levels, whereas endopeptidase Lys-C yielded vastly higher signals with low replicate variance. The choice of target peptide was critical for accurate MT3 detection - a peptide in the α-domain yielded the most robust signals. We demonstrate the utility of this method by comparing the expression of MT3 in post-mortem brain tissues of a cohort of Alzheimer's disease (AD) individuals and age-matched controls.

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Food allergies are a global food challenge. For correct food labelling, the detection and quantification of allergens are necessary. However, novel product formulations and industrial processes produce new scenarios, which require much more technological developments. For this purpose, OMICS technologies, especially proteomics, seemed to be relevant in this context. This review summarises the current knowledge and studies that used proteomics to study food allergens. In the case of the allergenic proteins, a wide variety of isoforms, post-translational modifications and other structural changes during food processing can increase or decrease the allergenicity. Most of the plant-based food allergens are proteins with biological functions involved in storage, structure, and plant defence. The allergenicity of these proteins could be increased by the presence of heavy metals, air pollution, and pesticides. Targeted proteomics like selected/multiple reaction monitoring (SRM/MRM) have been very useful, especially in the case of gluten from wheat, rye and barley, and allergens from lentil, soy, and fruit. Conventional 1D and 2-DE immunoblotting have been further widely used. For animal-based food allergens, the widely used technologies are 1D and 2-DE immunoblotting followed by MALDI-TOF/TOF, and more recently LC-MS/MS, which is becoming useful to assess egg, fish, or milk allergens. The detection and quantification of allergenic proteins using mass spectrometry-based proteomics are promising and would contribute to greater accuracy, therefore improving consumer information.

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Introduction: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.Areas covered: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.Expert opinion: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

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Cancerous inhibitor of protein phosphatase 2A (CIP2A) is involved in immune response, cancer progression, and Alzheimer's disease. However, an understanding of the mechanistic basis of its function in this wide spectrum of physiological and pathological processes is limited due to its poorly characterized interaction networks. Here we present the first systematic characterization of the CIP2A interactome by affinity-purification mass spectrometry combined with validation by selected reaction monitoring targeted mass spectrometry (SRM-MS) analysis in T helper (Th) 17 (Th17) cells. In addition to the known regulatory subunits of protein phosphatase 2A (PP2A), the catalytic subunits of protein PP2A were found to be interacting with CIP2A. Furthermore, the regulatory (PPP1R18, and PPP1R12A) and catalytic (PPP1CA) subunits of phosphatase PP1 were identified among the top novel CIP2A interactors. Evaluation of the ontologies associated with the proteins in this interactome revealed that they were linked with RNA metabolic processing and splicing, protein traffic, cytoskeleton regulation and ubiquitin-mediated protein degradation processes. Taken together, this network of protein-protein interactions will be important for understanding and further exploring the biological processes and mechanisms regulated by CIP2A both in physiological and pathological conditions.

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HL-60 promyelocytic cells are a widely used as a model for studying induced granulocytic differentiation. Investigation of proteins of the nuclear fraction, particularly transcription factors, is necessary for a better understanding of molecular mechanisms of cell maturation. Mass spectrometry is a powerful tool for analyzing a proteome due to its high sensitivity, specificity and performance. In this paper, using the selected reaction monitoring (SRM) method, we have assessed the levels of RBPJ, STAT1, CEBPB, CASP3, VAV1, PRKDC, PARP1 and UBC9 nuclear proteins isolated using hypertonic buffer, detergents (sodium dodecyl sulfate (SDS), sodium deoxycholate (DOC) and fissionable detergent ProteaseMAX™) and using centrifugation in a sucrose density gradient. The minimum and maximum protein content was 1.13±0.28 and 14.34±1.63 fmol/mkg of total protein for the transcription factor RBPJ and ubiquitin-protein ligase type I UBC9, respectively. According to the results of shotgun mass spectrometric analysis of nuclear fractions, 2356 proteins were identified, of which 106 proteins were annotated as transcription factors. 37 transcription factors were uniquely identified in the fraction obtained by centrifugation in a sucrose density gradient, while only 9 and 8 transcription factors were uniquely identified in the nuclear fractions obtained using hypertonic buffer and detergents, respectively. The transcription factors identified in the HL-60 cell line represent regulatory molecules; their directed profiling under the influence of differentiation inducers, will shed light on the mechanism of granulocyte maturation.

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This work continues the series of the quantitative measurements of the proteins encoded by different chromosomes in the blood plasma of a healthy person. Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards (SRM SIS) and a gene-centric approach, which is the basis for the implementation of the international Chromosome-centric Human Proteome Project (C-HPP), were applied for the quantitative measurement of proteins in human blood plasma. Analyses were carried out in the frame of C-HPP for each protein-coding gene of the four human chromosomes: 18, 13, Y, and mitochondrial. Concentrations of proteins encoded by 667 genes were measured in 54 blood plasma samples of the volunteers, whose health conditions were consistent with requirements for astronauts. The gene list included 276, 329, 47, and 15 genes of chromosomes 18, 13, Y, and the mitochondrial chromosome, respectively. This paper does not make claims about the detection of missing proteins. Only 205 proteins (30.7%) were detected in the samples. Of them, 84, 106, 10, and 5 belonged to chromosomes 18, 13, and Y and the mitochondrial chromosome, respectively. Each detected protein was found in at least one of the samples analyzed. The SRM SIS raw data are available in the ProteomeXchange repository (PXD004374, PASS01192).

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BACKGROUND: Although total plasma lipoproteome consists of proteins that have shown promises as biomarkers that can identify Alzheimer's disease (AD), effect sizes are modest. The objective of this study is to provide initial proof-of-concept that the plasma lipoproteome more likely differ between AD cases and controls when measured in individual plasma lipoprotein fractions than when measured as total in immunodepleted plasma. METHODS: We first developed a targeted proteomics method based on selected reaction monitoring (SRM) and liquid chromatography and tandem mass spectrometry for measurement of 120 tryptic peptides from 79 proteins that are commonly present in plasma lipoproteins. Then in a proof-of concept case-control study of 5 AD cases and 5 sex- and age-matched controls, we applied the targeted proteomic method and performed relatively quantification of 120 tryptic peptides in plasma lipoprotein fractions (fractionated by sequential gradient ultracentrifugation) and in immunodepleted plasma (of albumin and IgG). Unadjusted p values from two-sample t-tests and overall fold change was used to evaluate a peptide relative difference between AD cases and controls, with lower p values (< 0.05) or greater fold differences (> 1.05 or < 0.95) suggestive of greater peptide/protein differences. RESULTS: Within-day and between-days technical precisions (mean %CV [SD] of all SRM transitions) of the targeted proteomic method were 3.95% (2.65) and 9.31% (5.59), respectively. Between-days technical precisions (mean % CV [SD]) of the entire plasma lipoproteomic workflow including plasma lipoprotein fractionation was 27.90% (14.61). Ten tryptic peptides that belonged to 5 proteins in plasma lipoproteins had unadjusted p values < 0.05, compared to no peptides in immunodepleted plasma. Furthermore, 27, 32, 17, and 20 tryptic peptides in VLDL, IDL, LDL and HDL, demonstrated overall peptide fold differences > 1.05 or < 0.95, compared to only 6 tryptic peptides in immunodepleted plasma. The overall comparisons, therefore, suggested greater peptide/protein differences in plasma lipoproteome when measured in individual plasma lipoproteins than as total in immunodepleted plasma. Specifically, protein complement C3's peptide IHWESASLLR, had unadjusted p values of 0.00007, 0.00012, and 0.0006 and overall 1.25, 1.17, 1.14-fold changes in VLDL, IDL, and LDL, respectively. After positive False Discovery Rate (pFDR) adjustment, the complement C3 peptide IHWESASLLR in VLDL remained statistically different (adjusted p value < 0.05). DISCUSSION: The findings may warrant future studies to investigate plasma lipoproteome when measured in individual plasma lipoprotein fractions for AD diagnosis.

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Selected reaction monitoring (SRM) has become one of the main methods for low-mass-range-targeted proteomics by mass spectrometry (MS). However, in most SRM-MS biomarker validation studies, the sample size is very small, and in particular smaller than the number of proteins measured in the experiment. Moreover, the data can be noisy due to a low number of ions detected per peptide by the instrument. In this article, those issues are addressed by a model-based Bayesian method for classification of SRM-MS data. The methodology is likelihood-free, using approximate Bayesian computation implemented via a Markov chain Monte Carlo procedure and a kernel-based Optimal Bayesian Classifier. Extensive experimental results demonstrate that the proposed method outperforms classical methods such as linear discriminant analysis and 3NN, when sample size is small, dimensionality is large, the data are noisy, or a combination of these.

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Phosphoproteomics is an important tool for the unbiased investigation of signaling network activation and has particular application to unraveling aberrant signaling driving cancer progression. However, validating the behavior of specific phosphosites across multiple experimental conditions remains challenging, due to limitations inherent in discovery-based proteomic workflows and the limited availability of high-quality antibodies required for alternative, immunoaffinity-based methods. Targeted phosphoproteomics enables specific phosphosites to be quantified reproducibly across multiple experimental conditions. Importantly, targeted phosphoproteomic assays can be designed rapidly on the basis of data acquired in discovery proteomic experiments and circumvent the requirement of immunoaffinity techniques for reliable antibodies raised to specific, potentially poorly immunogenic phosphopeptides. In the following protocol, we present a method for the relative quantification of phosphosites across multiple experimental conditions and/or technical and biological replicates.

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Protein phosphorylation, one of the most common types of post-translational modifications, is the central regulatory mechanism of cellular signaling networks. In human cells, thousands of proteins are continuously and dynamically phosphorylated and dephosphorylated at specific sites and times in response to external and internal stimuli. Reversible phosphorylation is facilitated by the action of two protein superfamilies: kinases and phosphatases. Kinases play an essential role in almost every relevant physiological process in human cells and their deregulation is linked to pathologies ranging from cancer to autoimmune diseases.Systematic identification of kinases expressed in a particular cell type, quantification of their abundance, and precise determination of their phosphorylation stoichiometry are essential to understand the cellular signaling networks and physiology of a sample. Our protocol outlines the steps to build and use a high-throughput, comprehensive, modular, and robust selected reaction monitoring (SRM) proteomics framework to facilitate quantification of the kinome state in research or clinical human samples.

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Glycosylation often plays a key role in the safety and efficacy of therapeutic proteins to patients, thus underlying the need for consistent control of this important post-translational modification during biologics production. In this study, we profiled the site-specific evolution of N-glycans on a CTLA4-Fc-fusion protein, from the intracellular secretory pathway to the conditioned medium (CM) in fed-batch cell culture. For this, we developed an approach that combined sub-cellular fractionation with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses. The study revealed that there was a significant amount of heterogeneity in the glycans displayed amongst the three distinct N-glycosylation sites. Furthermore, 54-60% of the intracellular protein was characterized by Man8 and Man9 glycans on day 10, when the cell density peaks, indicative of a significant bottleneck between the endoplasmic reticulum (ER) and the cis-Golgi. At longer culture duration, the accumulation of intracellular protein with bi-antennary-fucosylated GlcNAc-terminated residues identified the formation of another bottleneck in the medial and trans-Golgi compartments, which subsequently led to a decrease in sialylated species in the secreted protein. Glucose deprivation caused a reduction in the Man8 and Man9 glycans in favor of Man5 glycans and bi-antennary-fucosylated GlcNAc-terminated residues in the organellar pool of the Fc-fusion protein. However, transient deprivation of glucose did not lead to major differences in the glycan profile of proteins secreted into the CM. The approach developed here allows us to probe the secretory pathway and sheds light on the site-specific intracellular processing of glycans during fed-batch cell culture, thus serving as an initial step towards their rational control. Biotechnol. Bioeng. 2017;114: 1550-1560. © 2017 Wiley Periodicals, Inc.

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Loxapine is an antipsychotic medication used for the treatment of schizophrenia. In vivo, loxapine is metabolized to multiple metabolites. A high performance liquid chromatographic-tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the determination of loxapine and 4 of its metabolites, loxapine N-oxide, amoxapine (N-desmethyl loxapine), 8-hydroxyloxapine and 7-hydroxyloxapine, in human plasma to support regulated clinical development. During method development, several technical challenges such as poor chromatography, separation of structural isomers, and inadequate sensitivity were met and overcome. The final method utilized micro-elution solid phase extraction (SPE) to extract plasma samples (100µL), and the resulting extracts were analyzed using reversed phase LC-MS/MS using a turbo-ionspray interface in positive ionization mode with selected reaction monitoring (SRM). The method was fully validated according to the current regulatory guidance for bioanalysis over the calibration curve range 0.0500-50.0ng/mL for all analytes using 1/x2-weighted linear regression analysis. Based on three separate runs, the between-run precision and inter-day precision for all five analytes at all concentrations, including the LLOQ (lower limit of quantitation) quality control at 0.0500ng/mL, varied from 0.0% to 13.8%, while the accuracy ranged from 86.4% to 109.3% of nominal. The extraction recoveries of loxapine and the four metabolites were above 80%. Various forms of short-term and long-term stability were established in both solutions and matrix, including the stability of loxapine and the four metabolites in human plasma for up to 260days of storage at -20°C. This method has been used to support a regulated clinical study, which included the successful execution of incurred sample reanalysis (ISR) testing. To the best of our knowledge, this is the first published methodology in which these five analytes were quantified with a single extraction and injection.

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The importance of biomarkers has long been recognized by the public, scientific community, and industry. Yet despite extensive efforts and funding investments in biomarker discovery, only 109 protein biomarkers in plasma or serum were approved by the US Food and Drug Administration throughout 2008 (Anderson NL. Clin Chem 56:177-185, 2010), and even fewer protein biomarkers are currently used routinely in the clinic. In recent years, the introduction of new protein biomarkers approved by the US Food and Drug Administration has fallen to an average of 1.5 per year (a median of only 1 per year) (Anderson NL. Clin Chem 56:177-185, 2010). The low efficiency of biomarker development is due to several reasons, including the poor quality of clinical samples, the gap between subjective clinical definition of a disease and objective protein measurements, and high false discovery rate of differentially expressed proteins identified in the initial discovery phase (Rifai N, Gillette MA, Carr SA. Nat Biotechnol 24:971-983, 2006). It has become clear that the vast majority of differentially expressed proteins identified in the discovery phase will ultimately fail as useful clinical biomarkers, and only few true positive candidates can move through the biomarker development pipeline. Isolation of true biomarkers from the large pool of differentially expressed proteins identified in the discovery phase becomes the greatest challenge and the bottleneck in most biomarker pipelines. To succeed, after the initial discovery study (see Chap. 20 ), the authenticity of biomarker candidates need to be tested in a pilot study with high throughput, high accuracy and reasonable cost. This essential process is addressed by qualification and verification phase of the biomarker development pipeline.

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The central nervous system is responsible for an array of cognitive functions such as memory, learning, language, and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the identification and quantification of thousands of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

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This work was aimed at estimating the concentrations of proteins encoded by human chromosome 18 (Chr 18) in plasma samples of 54 healthy male volunteers (aged 20-47). These young persons have been certified by the medical evaluation board as healthy subjects ready for space flight training. Over 260 stable isotope-labeled peptide standards (SIS) were synthesized to perform the measurements of proteins encoded by Chr 18. Selected reaction monitoring (SRM) with SIS allowed an estimate of the levels of 84 of 276 proteins encoded by Chr 18. These proteins were quantified in whole and depleted plasma samples. Concentration of the proteins detected varied from 10-6 M (transthyretin, P02766) to 10-11 M (P4-ATPase, O43861). A minor part of the proteins (mostly representing intracellular proteins) was characterized by extremely high inter individual variations. The results provide a background for studies of a potential biomarker in plasma among proteins encoded by Chr 18. The SRM raw data are available in ProteomeXchange repository (PXD004374).

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Absolute measurements of protein abundance are important in the understanding of biological processes and the precise computational modeling of biological pathways. We developed targeted LC-MS/MS assays in the selected reaction monitoring (SRM) mode to quantify over 50 mitochondrial proteins in a single run. The targeted proteins cover the tricarboxylic acid cycle, fatty acid ß-oxidation, oxidative phosphorylation, and the detoxification of reactive oxygen species. Assays used isotopically labeled concatemers as internal standards designed to target murine mitochondrial proteins and their human orthologues. Most assays were also suitable to quantify the corresponding protein orthologues in rats. After exclusion of peptides that did not pass the selection criteria, we arrived at SRM assays for 55 mouse, 52 human, and 51 rat proteins. These assays were optimized in isolated mitochondrial fractions from mouse and rat liver and cultured human fibroblasts and in total liver extracts from mouse, rat, and human. The developed proteomics approach is suitable for the quantification of proteins in the mitochondrial energy metabolic pathways in mice, rats, and humans as a basis for translational research. Initial data show that the assays have great potential for elucidating the adaptive response of human patients to mutations in mitochondrial proteins in a clinical setting.

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Two liquid chromatographic-tandem mass spectrometric (LC-MS/MS) methods have been developed and validated for the quantitative determination of polymyxin B1, polymyxin B2 and polymyxin B1-1 concentrations in human plasma and treated urine. During method development, technical challenges such as the separation of structural isomers polymyxin B1and polymyxin B1-1 and nonspecific binding in urine samples were encountered and overcome. Two automated solid phase extraction methods were used to extract plasma samples (100µL) and urine samples (200µL) and the resulting extracts were analyzed using reversed phase LC-MS/MS with an electrospray (ESI) interface and selected reaction monitoring (SRM) in the positive ionization mode. Both methods were validated over a calibration curve range of 5.00-2000ng/mL with a linear regression and 1/x(2) weighting. The between-run relative standard deviation (%RSD) ranged from 4.5 to 9.5% for the plasma assay and from 1.1 to 7.1% for the urine assay. For the plasma assay, the between-run accuracy ranged from 100.5 to 115.2% of nominal at all QC concentrations including the LLOQ. For the urine assay, the between-run accuracy ranged from 92.0 to 106% of nominal at all QC concentrations including the LLOQ. The extraction recoveries for all polymyxins in both assays were between 54.0 and 64.2%. Long term matrix storage stability for all polymyxins was established at both -20°C and -70°C for up to 85 days in human plasma and for up to 55 days in treated human urine. Both assays were used for the measurement of polymyxin B1, polymyxin B2 and polymyxin B1-1 concentrations in human plasma and treated urine for the determination of bioequivalence and toxicokinetic parameters in clinical studies.

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