SIMPATIQCO: A server-based software suite which facilitates monitoring the time course of LC-MS performance metrics on orbitrap instruments

While the performance of liquid chromatography (LC) and mass spectrometry (MS) instrumentation continues to increase, applications such as analyses of complete or near-complete proteomes and quantitative studies require constant and optimal system performance. For this reason, research laboratories and core facilities alike are recommended to implement quality control (QC) measures as part of their routine workflows. Many laboratories perform sporadic quality control checks. However, successive and systematic longitudinal monitoring of system performance would be facilitated by dedicated automatic or semiautomatic software solutions that aid an effortless analysis and display of QC metrics over time. We present the software package SIMPATIQCO (SIMPle AuTomatIc Quality COntrol) designed for evaluation of data from LTQ Orbitrap, Q-Exactive, LTQ FT, and LTQ instruments. A centralized SIMPATIQCO server can process QC data from multiple instruments. The software calculates QC metrics supervising every step of data acquisition from LC and electrospray to MS. For each QC metric the software learns the range indicating adequate system performance from the uploaded data using robust statistics. Results are stored in a database and can be displayed in a comfortable manner from any computer in the laboratory via a web browser. QC data can be monitored for individual LC runs as well as plotted over time. SIMPATIQCO thus assists the longitudinal monitoring of important QC metrics such as peptide elution times, peak widths, intensities, total ion current (TIC) as well as sensitivity, and overall LC-MS system performance; in this way the software also helps identify potential problems. The SIMPATIQCO software package is available free of charge

Dried blood spot UHPLC-MS/MS analysis of oseltamivir and oseltamivircarboxylate-a validated assay for the clinic

The neuraminidase inhibitor oseltamivir (Tamiflu®) is currently the first-line therapy for patients with influenza virus infection. Common analysis of the prodrug and its active metabolite oseltamivircarboxylate is determined via extraction from plasma. Compared with these assays, dried blood spot (DBS) analysis provides several advantages, including a minimum sample volume required for the measurement of drugs in whole blood. Samples can easily be obtained via a simple, non-invasive finger or heel prick. Mainly, these characteristics make DBS an ideal tool for pediatrics and to measure multiple time points such as those needed in therapeutic drug monitoring or pharmacokinetic studies. Additionally, DBS sample preparation, stability, and storage are usually most convenient. In the present work, we developed and fully validated a DBS assay for the simultaneous determination of oseltamivir and oseltamivircarboxylate concentrations in human whole blood. We demonstrate the simplicity of DBS sample preparation, and a fast, accurate and reproducible analysis using ultra high-performance liquid chromatography coupled to a triple quadrupole mass spectrometer. A thorough validation on the basis of the most recent FDA guidelines for bioanalytical method validation showed that the method is selective, precise, and accurate (≤15% RSD), and sensitive over the relevant clinical range of 5-1,500 ng/mL for oseltamivir and 20-1,500 ng/mL for the oseltamivircarboxyl

Global proteomic characterization of microdissected estrogen receptor positive breast tumors

We here describe two proteomic datasets deposited in ProteomeXchange via PRIDE partner repository [1] with dataset identifiers PXD000484 (defined as "training") and PXD000485 (defined as "test") that have been used for the development of a tamoxifen outcome predictive signature [2]. Both datasets comprised 56 fresh frozen estrogen receptor (ER) positive primary breast tumor specimens derived from patients who received tamoxifen as first line therapy for recurrent disease. Patient groups were defined based on time to progression (TTP) after start of tamoxifen therapy (6 months cutoff): 32 good and 24 poor treatment outcome patients were comprised in the training set, respectively. The test set included 41 good and 15 poor treatment outcome patients. All specimens were subjected to laser capture microdissection (LCM) to enrich for epithelial tumor cells prior to high resolution mass spectrometric (MS) analysis. Protein identificat

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker

TP53 mutated glioblastoma stem-like cell cultures are sensitive to dual mTORC1/2 inhibition while resistance in TP53 wild type cultures can be overcome by combined inhibition of mTORC1/2 and Bcl-2

Background: Glioblastoma is the most malignant tumor of the central nervous system and still lacks effective treatment. This study explores mutational biomarkers of 11 drugs targeting either the RTK/Ras/PI3K, the p53 or the Rb pathway using 25 patient-derived glioblastoma stem-like cell cultures (GSCs). Results: We found that TP53 mutated GSCs were approximately 3.5 fold more sensitive to dual inhibition of mammalian target of rapamycin complex 1 and 2 (mTORC1/2) compared to wild type GSCs. We identified that Bcl-2(Thr56/Ser70) phosphorylation contributed to the resistance of TP53 wild type GSCs against dual mTORC1/2 inhibition. The Bcl-2 inhibitor ABT-263 (navitoclax) increased sensitivity to the mTORC1/2 inhibitor AZD8055 in TP53 wild type GSCs, while sensitivity to AZD8055 in TP53 mutated GSCs remained unchanged. Conclusion: Our data suggest that Bcl-2 confers resistance to mTORC1/2 inhibitors in TP53 wild type GSCs and that combined inhibition of both mTORC1/2 and Bcl-2 is worthwhile to explore further in TP53 wild type glioblastomas, whereas in TP53 mutated glioblastomas dual mTORC1/2 inhibitors should be explored

Analytical Investigations of Toxic p-Phenylenediamine (PPD) Levels in Clinical Urine Samples with Special Focus on MALDI-MS/MS

Para-phenylenediamine (PPD) is a common chromophoric ingredient in oxidative hair-dyes. In some African countries like Sudan, Egypt and Morocco but also in India this chemical is used alone or in combination with colouring extracts like Henna for dyeing of the hair or the skin. Excessive dermal exposure to PPD mainly leads to the N-mono- and N,N′-diacetylated products (MAPPD, DAPPD) by N-acetyltransferase 1 and 2 (NAT1 and 2) catalyzed reactions. Metabolites and PPD are mainly excreted via renal clearance. Despite a low risk of intoxication when used in due form, there are numerous cases of acute intoxication in those countries every year. At the ENT Hospital - Khartoum (Sudan) alone more than 300 cases are reported every year (∼10% fatal), mostly caused by either an accidental or intended (suicidal) high systemic exposure to pure PPD. Intoxication leads to a severe clinical syndrome including laryngeal edema, rhabdomyolysis and subsequent renal failure, neurotoxicity and acute toxic hepatitis. To date, there is no defined clinical treatment or antidote available and treatment is largely supportive. Herein, we show the development of a quick on-site identification assay to facilitate differential diagnosis in the clinic and, more importantly, the implementation of an advanced analytical platform for future in-depth investigations of PPD intoxication and metabolism is described. The current work shows a sensitive (∼25 µM) wet chemistry assay, a validated MALDI-MS/MS and HPLC-UV assay for the determination of PPD and its metabolites in human urine. We show the feasibility of the methods for measuring PPD over a range of 50–1000 µM. The validation criteria included linearity, lower limit of quantification (LLOQ), accuracy and precision, recovery and stability. Finally, PPD concentrations were determined in clinical urine samples of cases of acute intoxication and the applied technique was expanded to identify MAPPD and DAPPD in the identical samples

Lipid signature of advanced human carotid atherosclerosis assessed by mass spectrometry imaging

Carotid atherosclerosis is a risk factor for ischemic stroke, one of the main causes of mortality and disability worldwide. The disease is characterized by plaques, heterogeneous deposits of lipids, and necrotic debris in the vascular wall, which grow gradually and may remain asymptomatic for decades. However, at some point a plaque can evolve to a high-risk plaque phenotype, which may trigger a cerebrovascular event. Lipids play a key role in the development and progression of atherosclerosis, but the nature of their involvement is not fully understood. Using matrix-assisted laser desorption/ionization mass spectrometry imaging, we visualized the distribution of approximately 200 different lipid signals, originating of >90 uniquely assigned species, in 106 tissue sections of 12 human carotid atherosclerotic plaques. We performed unsupervised classification of the mass spectrometry dataset, as well as a histology-directed multivariate analysis. These data allowed us to extract the spatial lipid patterns associated with morphological plaque features in advanced plaques from a symptomatic population, revealing spatial lipid patterns in atherosclerosis and their relation to histological tissue type. The abundances of sphingomyelin and oxidized cholesteryl ester species were elevated specifically in necrotic intima areas, whereas diacylglycerols and tri-acylglycerols were spatially correlated to areas containing the coagulation protein fibrin. These results demonstrate a clear colocalization between plaque features and specific lipid classes, as well as individual lipid species in high-risk atherosclerotic plaques.Proteomic

Interpretation and Visualization of Non-Linear Data Fusion in Kernel Space: Study on Metabolomic Characterization of Progression of Multiple Sclerosis

Contains fulltext : 93904.pdf (publisher's version ) (Open Access