Publications
228 results found
Lewis MR, Pearce JTM, Spagou K, et al., 2016, Development and Application of Ultra-Performance Liquid Chromatography-TOF MS for Precision Large Scale Urinary Metabolic Phenotyping, Analytical Chemistry, Vol: 88, Pages: 9004-9013, ISSN: 1520-6882
To better understand the molecular mechanisms underpinning physiological variation in human populations, metabolic phenotyping approaches are increasingly being applied to studies involving hundreds and thousands of biofluid samples. Hyphenated ultra-performance liquid chromatography and mass spectrometry (UPLC-MS) has become a fundamental tool for this purpose. Yet, the seemingly inevitable need to analyze large studies in multiple analytical batches for UPLC-MS analysis poses a challenge to data quality which has been recognized in the field. Herein we describe in detail a fit-for-purpose UPLC-MS platform, method set, and sample analysis workflow, capable of sustained analysis on an industrial scale and allowing batch-free operation for large studies. Using complementary reversed-phase chromatography (RPC) and hydrophilic interaction liquid chromatography (HILIC) together with high resolution orthogonal acceleration time-of-flight mass spectrometry, exceptional measurement precision is exemplified with independent epidemiological sample sets of approximately 650 and 1000 participant samples. Evaluation of molecular reference targets in repeated injections of pooled quality control (QC) samples distributed throughout each experiment demonstrates a mean retention time relative standard deviation (RSD) of <0.3% across all assays in both studies and a mean peak area RSD of <15% in the raw data. To more globally assess the quality of the profiling data, untargeted feature extraction was performed followed by data filtration according to feature intensity response to QC sample dilution. Analysis of the remaining features within the repeated QC sample measurements demonstrated median peak area RSD values of <20% for the RPC assays and <25% for the HILIC assays. These values represent the quality of the raw data, as no normalization or feature-specific intensity correction was applied. While the data in each experiment was acquired in a single continuous batch
St John ER, Al-Khudairi R, Ashrafian H, et al., 2016, Diagnostic accuracy of intraoperative techniques for margin assessment in breast cancer surgery: a meta-analysis, Annals of Surgery, Vol: 265, Pages: 300-310, ISSN: 1528-1140
OBJECTIVE: The aim of this study was to conduct a systematic review and meta-analysis to clarify the diagnostic accuracy of intraoperative breast margin assessment (IMA) techniques against which the performance of emerging IMA technologies may be compared. SUMMARY OF BACKGROUND DATA: IMA techniques have failed to penetrate routine practice due to limitations, including slow reporting times, technical demands, and logistics. Emerging IMA technologies are being developed to reduce positive margin and re-excision rates and will be compared with the diagnostic accuracy of existing techniques. METHOD: Studies were identified using electronic bibliographic searches up to January 2016. MESH terms and all-field search terms included "Breast Cancer" AND "Intraoperative" AND "Margin." Only clinical studies with raw diagnostic accuracy data as compared with final permanent section histopathology were included. A bivariate model for diagnostic meta-analysis was used to attain overall pooled sensitivity and specificity. RESULTS: Eight hundred thirty-eight unique studies revealed 35 studies for meta-analysis. Pooled sensitivity (Sens), specificity (Spec), and area under the receiver operating characteristic curve (AUROC) values were calculated per group (Sens, Spec, AUROC): frozen section = 86%, 96%, 0.96 (n = 9); cytology = 91%, 95%, 0.98 (n = 11); intraoperative ultrasound = 59%, 81%, 0.78 (n = 4); specimen radiography = 53%, 84%, 0.73 (n = 9); optical spectroscopy = 85%, 87%, 0.88 (n = 3). CONCLUSIONS: Pooled data suggest that frozen section and cytology have the greatest diagnostic accuracy. However, these methods are resource intensive and turnaround times for results have prevented widespread international adoption. Emerging technologies need to compete with the diagnostic accuracy of existing techniques while offering advantages in terms of speed, cost, and reliability.
Strittmatter N, Lovrics A, Sessler J, et al., 2016, Shotgun Lipidomic Profiling of the NCI60 Cell Line Panel Using Rapid Evaporative Ionization Mass Spectrometry., Analytical Chemistry, Vol: 88, Pages: 7507-7514, ISSN: 1086-4377
Rapid evaporative ionization mass spectrometry (REIMS) was used for the rapid mass spectrometric profiling of cancer cell lines. Spectral reproducibility was assessed for three different cell lines, and the extent of interclass differences and intraclass variance was found to allow the identification of these cell lines based on the REIMS data. Subsequently, the NCI60 cell line panel was subjected to REIMS analysis, and the resulting data set was investigated for its distinction of individual cell lines and different tissue types of origin. Information content of REIMS spectral profiles of cell lines were found to be similar to those obtained from mammalian tissues although pronounced differences in relative lipid intensity were observed. Ultimately, REIMS was shown to detect changes in lipid content of cell lines due to mycoplasma infection. The data show that REIMS is an attractive means to study cell lines involving minimal sample preparation and analysis times in the range of seconds.
Abbassi-Ghadi N, Golf O, Kumar S, et al., 2016, Imaging of esophageal lymph node metastases by desorption electrospray ionization mass spectrometry, Cancer Research, Vol: 76, Pages: 5647-5656, ISSN: 1538-7445
Histopathological assessment of lymph node metastases (LNM) depends on subjective analysis of cellular morphology with inter-/intra-observer variability. In this study, LNM from esophageal adenocarcinoma was objectively detected using desorption electrospray ionization-mass spectrometry imaging (DESI-MSI). Ninety lymph nodes and their primary tumor biopsies from 11 esophago-gastrectomy specimens were examined and analyzed by DESI-MSI. Images from mass spectrometry and corresponding histology were co-registered and analyzed using multivariate statistical tools. The MSIs revealed consistent lipidomic profiles of individual tissue types found within lymph nodes. Spatial mapping of the profiles showed identical distribution patterns as per the tissue types in matched immunohistochemistry images. Lipidomic profile comparisons of LNM versus the primary tumor revealed a close association in contrast to benign lymph node tissue types. This similarity was used for the objective prediction of LNM in mass spectrometry images utilizing the average lipidomic profile of esophageal adenocarcinoma. The multivariate statistical algorithm developed for LNM identification demonstrated a sensitivity, specificity, positive predictive value and negative predictive value of 89.5, 100, 100 and 97.2 per-cent, respectively, when compared to gold-standard immunohistochemistry. DESI-MSI has the potential to be a diagnostic tool for peri-operative identification of LNM and compares favorably with techniques currently used by histopathology experts.
Lund-Palau H, Turnbull AR, Bush A, et al., 2016, Pseudomonas aeruginosa infection in cystic fibrosis: pathophysiological mechanisms and therapeutic approaches, Expert Review of Respiratory Medicine, Vol: 10, Pages: 685-697, ISSN: 1747-6348
Pseudomonas aeruginosa is a remarkably versatile environmental bacterium with an extraordinary capacity to infect the cystic fibrosis (CF) lung. Infection with P. aeruginosa occurs early, and although eradication can be achieved following early detection, chronic infection occurs in over 60% of adults with CF. Chronic infection is associated with accelerated disease progression and increased mortality. Extensive research has revealed complex mechanisms by which P. aeruginosa adapts to and persists within the CF airway. Yet knowledge gaps remain, and prevention and treatment strategies are limited by the lack of sensitive detection methods and by a narrow armoury of antibiotics. Further developments in this field are urgently needed in order to improve morbidity and mortality in people with CF. Here, we summarize current knowledge of pathophysiological mechanisms underlying P. aeruginosa infection in CF. Established treatments are discussed, and an overview is offered of novel detection methods and therapeutic strategies in development.
Balog J, Perenyi D, Guallar-Hoyas C, et al., 2016, Identification of the Species of Origin for Meat Products by Rapid Evaporative Ionization Mass Spectrometry, Journal of Agricultural and Food Chemistry, Vol: 64, Pages: 4793-4800, ISSN: 1520-5118
Increasingly abundant food fraud cases have brought food authenticity and safety into major focus. This study presents a fast and effective way to identify meat products using rapid evaporative ionization mass spectrometry (REIMS). The experimental setup was demonstrated to be able to record a mass spectrometric profile of meat specimens in a time frame of <5 s. A multivariate statistical algorithm was developed and successfully tested for the identification of animal tissue with different anatomical origin, breed, and species with 100% accuracy at species and 97% accuracy at breed level. Detection of the presence of meat originating from a different species (horse, cattle, and venison) has also been demonstrated with high accuracy using mixed patties with a 5% detection limit. REIMS technology was found to be a promising tool in food safety applications providing a reliable and simple method for the rapid characterization of food products.
St John ER, Rossi M, Pruski P, et al., 2016, Intraoperative tissue identification by mass spectrometric technologies, TrAC Trends in Analytical Chemistry, Vol: 85, Pages: 2-9, ISSN: 0165-9936
Mass spectrometric (MS) approaches developed for tissue identification in surgical environments are reviewed. MS Imaging (MSI) techniques enable the direct analysis of human tissue and can be used as an alternative means for margin assessment. While MSI-based approaches were demonstrated to improve the examiner-related variance of the data, the time demand and the cost of these analyses remained high. Furthermore, the necessity of MS expertise for the clinical deployment of these techniques has hindered large-scale clinical testing. The advent of ‘ambient’ MS methods contributed to the application of MSI techniques in this field, however alternative methods have been developed for the direct analysis of tissue samples without sample preparation. One group of methods employs surgical tissue manipulation for ionization while the other one uses minimally invasive probes for sampling prior to ionization. The methods are summarised and compared with regard to the information delivered, turnaround time and tissue identification performance.
Tillner J, McKenzie JS, Jones EA, et al., 2016, Investigation of the Impact of Desorption Electrospray Ionization Sprayer Geometry on Its Performance in Imaging of Biological Tissue., Analytical Chemistry, Vol: 88, Pages: 4808-4816, ISSN: 0003-2700
In this study, the impact of sprayer design and geometry on performance in desorption electrospray ionization mass spectrometry (DESI-MS) is assessed, as the sprayer is thought to be a major source of variability. Absolute intensity repeatability, spectral composition, and classification accuracy for biological tissues are considered. Marked differences in tissue analysis performance are seen between the commercially available and a lab-built sprayer. These are thought to be associated with the geometry of the solvent capillary and the resulting shape of the primary electrospray. Experiments with a sprayer with a fixed solvent capillary position show that capillary orientation has a crucial impact on tissue complex lipid signal and can lead to an almost complete loss of signal. Absolute intensity repeatability is compared for five lab-built sprayers using pork liver sections. Repeatability ranges from 1 to 224% for individual sprayers and peaks of different spectral abundance. Between sprayers, repeatability is 16%, 9%, 23%, and 34% for high, medium, low, and very low abundance peaks, respectively. To assess the impact of sprayer variability on tissue classification using multivariate statistical tools, nine human colorectal adenocarcinoma sections are analyzed with three lab-built sprayers, and classification accuracy for adenocarcinoma versus the surrounding stroma is assessed. It ranges from 80.7 to 94.5% between the three sprayers and is 86.5% overall. The presented results confirm that the sprayer setup needs to be closely controlled to obtain reliable data, and a new sprayer setup with a fixed solvent capillary geometry should be developed.
Ashton S, Song YH, Nolan J, et al., 2016, Aurora kinase inhibitor nanoparticles target tumors with favorable therapeutic index in vivo, Science Translational Medicine, Vol: 8, ISSN: 1946-6242
A class of drugs, called kinase inhibitors, could stop cancer in its tracks…if only these drugs could reach the tumors, stay for a while, and not be toxic. Hypothesizing that a nanoparticle formulation would solve the inhibitors’ woes, Ashton and colleagues investigated several different compositions of so-called Accurins—polymeric particles that encapsulate charged drugs through ion pairing. An Aurora B kinase, once formulated in Accurins, demonstrated a much-improved therapeutic index and preclinical efficacy compared with its parent molecule, when administered to rats and mice bearing human tumors. The Accurins allowed for sustained release of the drug over days, and did not have the same blood toxicity seen with the parent drug. A phase 1 trial is the next step for this nanomedicine, and additional preclinical studies will reveal whether such nanoformulations can improve the tolerability and efficacy of the broader class of molecularly targeted cancer therapeutics, including cell cycle inhibitors.
Abbassi-Ghadi N, Jones EA, Gomez-Romero M, et al., 2015, A Comparison of DESI-MS and LC-MS for the Lipidomic Profiling of Human Cancer Tissue, Journal of the American Society for Mass Spectrometry, Vol: 27, Pages: 255-264, ISSN: 1044-0305
In this study, we make a direct comparison between desorptionelectrospray ionization-mass spectrometry (DESI-MS) and ultraperformance liquidchromatography-electrospray ionization-mass spectrometry (UPLC-ESI-MS) platformsfor the profiling of glycerophospholipid (GPL) species in esophageal cancertissue. In particular, we studied the similarities and differences in the range of GPLsdetected and the congruency of their relative abundances as detected by eachanalytical platform. The main differences between mass spectra of the two modalitieswere found to be associated with the variance in adduct formation of common GPLs,rather than the presence of different GPL species. Phosphatidylcholines as formateadducts in UPLC-ESI-MS accounted for the majority of differences in negative ionmode and alkali metal adducts of phosphatidylcholines in DESI-MS for positive ion mode. Comparison of therelative abundance of GPLs, normalized to a common peak, revealed a correlation coefficient of 0.70 (P < 0.001).The GPL profile detected by DESI-MS is congruent to UPLC-ESI-MS, which reaffirms the role of DESI-MS forlipidomic profiling and a potential premise for quantification.
Szabo E, Szatmari I, Szonyi L, et al., 2015, Quantitative analytical method for the determination of biotinidase activity in dried blood spot samples, Analytical Chemistry, Vol: 87, Pages: 10573-10578, ISSN: 0003-2700
Biotinidase activity assay is included in most newborn screening protocols, and the positive results are confirmed by quantitative enzyme activity measurements. In our study, we describe a new quantitative analytical method for the determination of biotinidase activity using the blood sample deposited onto filter paper as the assay medium, by predepositing N-biotinyl-p-aminobenzoic acid onto the standard sample collection paper. The analysis of the assay mixture requires a simple extraction step from a dried blood spot followed by the quantification of product by LC-MS. The method provides a simple and reliable enzyme assay method that enables the rapid diagnosis of biotinidase deficiency (BD). Out of the measured 36 samples, 13 were healthy with lower enzyme activities, 16 were patients with partial BD, and 7 were patients with profound BD with residual activity below 10%. Expression of enzyme activity in percentage of mean activity of negative controls allows comparison of the different techniques. The obtained results are in good agreement with activity data determined from both dried blood spots and serum samples, giving an informative diagnostic value.
Balog J, Kumar, Alexander J, et al., 2015, In vivo endoscopic tissue identification tool utilising Rapid Evaporative Ionization Mass Spectrometry (REIMS), Angewandte Chemie International Edition, Vol: 54, Pages: 11059-11062, ISSN: 1433-7851
Gastrointestinal cancers are a leading cause of mortality, accounting for 23 % of cancer-related deaths worldwide. In order to improve outcomes from these cancers, novel tissue characterization methods are needed to facilitate accurate diagnosis. Rapid evaporative ionization mass spectrometry (REIMS) is a technique developed for the in vivo classification of human tissue through mass spectrometric analysis of aerosols released during electrosurgical dissection. This ionization technique was further developed by utilizing surface induced dissociation and was integrated with an endoscopic polypectomy snare to allow in vivo analysis of the gastrointestinal tract. We tested the classification performance of this novel endoscopic REIMS method in vivo. It was shown to be capable of differentiating between healthy layers of the intestinal wall, cancer, and adenomatous polyps based on the REIMS fingerprint of each tissue type in vivo.
Bundy JG, Liebeke M, Strittmatter N, et al., 2015, Unique metabolites protect earthworms against plant polyphenols, Nature Communications, Vol: 6, Pages: 1-7, ISSN: 2041-1723
All higher plants produce polyphenols, for defence against above-ground herbivory. These polyphenols also influence the soil micro- and macrofauna that break down plant leaf litter. Polyphenols therefore indirectly affect the fluxes of soil nutrients and, ultimately, carbon turnover and ecosystem functioning in soils. It is unknown how earthworms, the major component of animal biomass in many soils, cope with high-polyphenol diets. Here, we show that earthworms possess a class of unique surface-active metabolites in their gut, which we term ‘drilodefensins’. These compounds counteract the inhibitory effects of polyphenols on earthworm gut enzymes, and high polyphenol diets increase drilodefensin concentrations in both laboratory and field populations. This shows that drilodefensins protect earthworms from the harmful effects of ingested polyphenols. We have identified the key mechanism for adaptation to a dietary challenge in an animal group that has a major role in organic matter recycling in soils worldwide.
Chekmeneva E, Correia G, Denes J, et al., 2015, Development of nanoelectrospray high resolution isotope dilution mass spectrometry for targeted quantitative analysis of urinary metabolites: application to population profiling and clinical studies, Analytical Methods, Vol: 7, Pages: 5122-5133, ISSN: 1759-9679
An automated chip-based electrospray platform was used to develop a high-throughput nanoelectrospray high resolution mass spectrometry (nESI-HRMS) method for multiplexed parallel untargeted and targeted quantitative metabolic analysis of urine samples. The method was demonstrated to be suitable for metabolic analysis of large sample numbers and can be applied to large-scale epidemiological and stratified medicine studies. The method requires a small amount of sample (5 μL of injectable volume containing 250 nL of original sample), and the analysis time for each sample is three minutes per sample to acquire data in both negative and positive ion modes. Identification of metabolites was based on the high resolution accurate mass and tandem mass spectrometry using authentic standards. The method was validated for 8 targeted metabolites and was shown to be precise and accurate. The mean accuracy of individual measurements being 106% and the intra- and inter-day precision (expressed as relative standard deviations) were 9% and 14%, respectively. Selected metabolites were quantified by standard addition calibration using the stable isotope labelled internal standards in a pooled urine sample, to account for any matrix effect. The multiple point standard addition calibration curves yielded correlation coefficients greater than 0.99, and the linear dynamic range was more than three orders of magnitude. As a proof-of-concept the developed method was applied for targeted quantitative analysis of a set of 101 urine samples obtained from female participants with different pregnancy outcomes. In addition to the specifically targeted metabolites, several other metabolites were quantified relative to the internal standards. Based on the calculated concentrations, some metabolites showed significant differences according to different pregnancy outcomes. The acquired high resolution full-scan data were used for further untargeted fingerprinting and improved the differentiation of
Oetjen J, Veselkov K, Watrous J, et al., 2015, Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry, GigaScience, Vol: 4, ISSN: 2047-217X
Background: Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS hasunique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatialorganization of biological processes, and has growing potential to be introduced into routine use in both biologyand medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3Dimaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack ofpublicly available benchmark datasets needed to evaluate and compare algorithms.Findings: High-quality 3D imaging MS datasets from different biological systems at several labs were acquired,supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights,an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two typesof 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected frommurine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies culturedin Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectaladenocarcinoma.Conclusions: With the aim to stimulate computational research in the field of computational 3D imaging MS, selectedhigh-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.
Guenther S, Muirhead LJ, Speller AVM, et al., 2015, Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry, Cancer Research, Vol: 75, Pages: 1828-1837, ISSN: 0008-5472
Breast cancer is a heterogeneous disease characterized by varying responses to therapeutic agents and significant differences in long-term survival. Thus, there remains an unmet need for early diagnostic and prognostic tools and improved histologic characterization for more accurate disease stratification and personalized therapeutic intervention. This study evaluated a comprehensive metabolic phenotyping method in breast cancer tissue that uses desorption electrospray ionization mass spectrometry imaging (DESI MSI), both as a novel diagnostic tool and as a method to further characterize metabolic changes in breast cancer tissue and the tumor microenvironment. In this prospective single-center study, 126 intraoperative tissue biopsies from tumor and tumor bed from 50 patients undergoing surgical resections were subject to DESI MSI. Global DESI MSI models were able to distinguish adipose, stromal, and glandular tissue based on their metabolomic fingerprint. Tumor tissue and tumor-associated stroma showed evident changes in their fatty acid and phospholipid composition compared with normal glandular and stromal tissue. Diagnosis of breast cancer was achieved with an accuracy of 98.2% based on DESI MSI data (PPV 0.96, NVP 1, specificity 0.96, sensitivity 1). In the tumor group, correlation between metabolomic profile and tumor grade/hormone receptor status was found. Overall classification accuracy was 87.7% (PPV 0.92, NPV 0.9, specificity 0.9, sensitivity 0.92). These results demonstrate that DESI MSI may be a valuable tool in the improved diagnosis of breast cancer in the future. The identified tumor-associated metabolic changes support theories of de novo lipogenesis in tumor tissue and the role of stroma tissue in tumor growth and development and overall disease prognosis. Cancer Res; 75(9); 1828–37. ©2015 AACR.
Szekeres M, Nadasy GL, Turu G, et al., 2015, Endocannabinoid-mediated modulation of G<sub>q/11</sub> protein-coupled receptor signaling-induced vasoconstriction and hypertension, MOLECULAR AND CELLULAR ENDOCRINOLOGY, Vol: 403, Pages: 46-56, ISSN: 0303-7207
- Author Web Link
- Cite
- Citations: 26
Golf O, Strittmatter N, Karancsi T, et al., 2015, Rapid evaporative ionization mass spectrometry imaging platform for direct mapping from bulk tissue and bacterial growth media, Analytical Chemistry, Vol: 87, Pages: 2527-2534, ISSN: 0003-2700
Rapid evaporative ionization mass spectrometry (REIMS) technology allows real time intraoperative tissue classification and the characterization and identification of microorganisms. In order to create spectral libraries for training the classification models, reference data need to be acquired in large quantities as classification accuracy generally improves as a function of number of training samples. In this study, we present an automated high-throughput method for collecting REIMS data from heterogeneous organic tissue. The underlying instrumentation consists of a 2D stage with an additional high-precision z-axis actuator that is equipped with an electrosurgical diathermy-based sampling probe. The approach was validated using samples of human liver with metastases and bacterial strains, cultured on solid medium, belonging to the species P. aeruginosa, B. subtilis, and S. aureus. For both sample types, spatially resolved spectral information was obtained that resulted in clearly distinguishable multivariate clustering between the healthy/cancerous liver tissues and between the bacterial species.
Abbassi-Ghadi N, Jones EA, Veselkov KA, et al., 2015, Repeatability and reproducibility of desorption electrospray ionization-mass spectrometry (DESI-MS) for the imaging analysis of human cancer tissue: a gateway for clinical applications, Analytical Methods: advancing methods and applications, Vol: 7, Pages: 71-80, ISSN: 1759-9660
In this study, we aim to demonstrate the repeatability and reproducibility of DESI-MS for the imaging analysis of human cancer tissue using a set of optimal geometric and electrospray solvent parameters. Oesophageal cancer tissue was retrieved from four quadrants of a freshly removed tumor specimen, snap frozen, cryo-sectioned and mounted on glass slides for DESI-MS image acquisition. Prior to assessing precision, optimal geometric and electrospray solvent parameters were determined to maximize the number of detected lipid species and associated Total Ion Count (TIC). The same settings were utilized for all subsequent experiments. Repeatability measurements were performed using the same instrument, by the same operator on a total of 16 tissue sections (four from each quadrant of the tumor). Reproducibility measurements were determined in a different laboratory, on a separate DESI-MS platform and by an independent operator on 4 sections of one quadrant and compared to the corresponding measurements made for the repeatability experiments. The mean ± SD CV of lipid ion intensities was found to be 22 ± 7% and 18 ± 8% as measures of repeatability and reproducibility, respectively. In conclusion, DESI-MS has acceptable levels of reproducibility for the analysis of lipids in human cancer tissue and is suitable for the purposes of clinical research and diagnostics.
Golf O, Muirhead LJ, Speller A, et al., 2015, XMS: cross-platform normalization method for multimodal mass spectrometric tissue profiling, Journal of the American Society for Mass Spectrometry, Vol: 26, Pages: 44-54, ISSN: 1044-0305
Here we present a proof of concept cross-platform normalization approach to convert raw mass spectra acquired by distinct desorption ionization methods and/or instrumental setups to cross-platform normalized analyte profiles. The initial step of the workflow is database driven peak annotation followed by summarization of peak intensities of different ions from the same molecule. The resulting compound-intensity spectra are adjusted to a method-independent intensity scale by using predetermined, compound-specific normalization factors. The method is based on the assumption that distinct MS-based platforms capture a similar set of chemical species in a biological sample, though these species may exhibit platform-specific molecular ion intensity distribution patterns. The method was validated on two sample sets of (1) porcine tissue analyzed by laser desorption ionization (LDI), desorption electrospray ionization (DESI), and rapid evaporative ionization mass spectrometric (REIMS) in combination with Fourier transformation-based mass spectrometry; and (2) healthy/cancerous colorectal tissue analyzed by DESI and REIMS with the latter being combined with time-of-flight mass spectrometry. We demonstrate the capacity of our method to reduce MS-platform specific variation resulting in (1) high inter-platform concordance coefficients of analyte intensities; (2) clear principal component based clustering of analyte profiles according to histological tissue types, irrespective of the used desorption ionization technique or mass spectrometer; and (3) accurate “blind” classification of histologic tissue types using cross-platform normalized analyte profiles.
Wiley JS, Takats Z, Ouyang Z, et al., 2015, Desorption Electrospray Mass Spectrometry, AMBIENT IONIZATION MASS SPECTROMETRY, Editors: Domin, Cody, Publisher: ROYAL SOC CHEMISTRY, Pages: 307-333, ISBN: 978-1-84973-926-9
- Author Web Link
- Cite
- Citations: 2
Berisha A, Dold S, Guenther S, et al., 2014, A comprehensive high-resolution mass spectrometry approach for characterization of metabolites by combination of ambient ionization, chromatography and imaging methods, Rapid Communications in Mass Spectrometry, Vol: 28, Pages: 1779-1791, ISSN: 0951-4198
RATIONALEAn ideal method for bioanalytical applications would deliver spatially resolved quantitative information in real time and without sample preparation. In reality these requirements can typically not be met by a single analytical technique. Therefore, we combine different mass spectrometry approaches: chromatographic separation, ambient ionization and imaging techniques, in order to obtain comprehensive information about metabolites in complex biological samples.METHODSSamples were analyzed by laser desorption followed by electrospray ionization (LD‐ESI) as an ambient ionization technique, by matrix‐assisted laser desorption/ionization (MALDI) mass spectrometry imaging for spatial distribution analysis and by high‐performance liquid chromatography/electrospray ionization mass spectrometry (HPLC/ESI‐MS) for quantitation and validation of compound identification. All MS data were acquired with high mass resolution and accurate mass (using orbital trapping and ion cyclotron resonance mass spectrometers). Grape berries were analyzed and evaluated in detail, whereas wheat seeds and mouse brain tissue were analyzed in proof‐of‐concept experiments.RESULTSIn situ measurements by LD‐ESI without any sample preparation allowed for fast screening of plant metabolites on the grape surface. MALDI imaging of grape cross sections at 20 µm pixel size revealed the detailed distribution of metabolites which were in accordance with their biological function. HPLC/ESI‐MS was used to quantify 13 anthocyanin species as well as to separate and identify isomeric compounds. A total of 41 metabolites (amino acids, carbohydrates, anthocyanins) were identified with all three approaches. Mass accuracy for all MS measurements was better than 2 ppm (root mean square error).CONCLUSIONSThe combined approach provides fast screening capabilities, spatial distribution information and the possibility to quantify metabolites. Accurate mass measurements proved to be critical in order to relia
Swales JG, Tucker JW, Strittmatter N, et al., 2014, Mass spectrometry imaging of cassette-dosed drugs for higher throughput pharmacokinetic and biodistribution analysis, Analytical Chemistry, Vol: 86, Pages: 8473-8480, ISSN: 0003-2700
Cassette dosing of compounds for preclinical drug plasma pharmacokinetic analysis has been shown to be a powerful strategy within the pharmaceutical industry for increasing throughput while decreasing the number of animals used. Presented here for the first time is data on the application of a cassette dosing strategy for label-free tissue distribution studies. The aim of the study was to image the spatial distribution of eight nonproprietary drugs (haloperidol, bufuralol, midazolam, clozapine, terfenadine, erlotinib, olanzapine, and moxifloxacin) in multiple tissues after oral and intravenous cassette dosing (four compounds per dose route). An array of mass spectrometry imaging technologies, including matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI), liquid extraction surface analysis tandem mass spectrometry (LESA-MS/MS), and desorption electrospray ionization mass spectrometry (DESI-MS) was used. Tissue analysis following intravenous and oral administration of discretely and cassette-dosed compounds demonstrated similar relative abundances across a range of tissues indicating that a cassette dosing approach was applicable. MALDI MSI was unsuccessful in detecting all of the target compounds; therefore, DESI MSI, a complementary mass spectrometry imaging technique, was used to detect additional target compounds. In addition, by adapting technology used for tissue profiling (LESA-MS/MS) low spatial resolution mass spectrometry imaging (∼1 mm) was possible for all targets across all tissues. This study exemplifies the power of multiplatform MSI analysis within a pharmaceutical research and development (R&D) environment. Furthermore, we have illustrated that the cassette dosing approach can be readily applied to provide combined, label-free pharmacokinetic and drug distribution data at an early stage of the drug discovery/development process while minimizing animal usage.
Strittmatter N, Rebec M, Jones EA, et al., 2014, Characterization and identification of clinically relevant microorganisms using rapid evaporative ionization mass spectrometry, Analytical Chemistry, Vol: 86, Pages: 6555-6562, ISSN: 0003-2700
Rapid evaporative ionization mass spectrometry (REIMS) was investigated for its suitability as a general identification system for bacteria and fungi. Strains of 28 clinically relevant bacterial species were analyzed in negative ion mode, and corresponding data was subjected to unsupervised and supervised multivariate statistical analyses. The created supervised model yielded correct cross-validation results of 95.9%, 97.8%, and 100% on species, genus, and Gram-stain level, respectively. These results were not affected by the resolution of the mass spectral data. Blind identification tests were performed for strains cultured on different culture media and analyzed using different instrumental platforms which led to 97.8–100% correct identification. Seven different Escherichia coli strains were subjected to different culture conditions and were distinguishable with 88% accuracy. In addition, the technique proved suitable to distinguish five pathogenic Candida species with 98.8% accuracy without any further modification to the experimental workflow. These results prove that REIMS is sufficiently specific to serve as a culture condition-independent tool for the identification and characterization of microorganisms.
Takats Z, 2014, Analysis of dried blood spot samples by high resolution mass spectrometry - From newborn screening to cancer diagnostics, Clinical Biochemistry, Vol: 47, Pages: 699-699, ISSN: 0009-9120
Abbassi-Ghadi N, Veselkov K, Kumar S, et al., 2014, Discrimination of lymph node metastases using desorption electrospray ionisation-mass spectrometry imaging, Chemical Communications, Vol: 50, Pages: 3661-3664, ISSN: 1359-7345
Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) has been used for the identification of cancer within lymph nodes with accurate spatial distribution in comparison to gold standard matched immuno-histopathological images. The metabolic profile of the cancerous lymph nodes was similar to that of the primary tumour site.
Mirnezami R, Spagou K, Vorkas PA, et al., 2014, Chemical mapping of the colorectal cancer microenvironment via MALDI imaging mass spectrometry (MALDI-MSI) reveals novel cancer-associated field effects, Molecular Oncology, Vol: 8, Pages: 39-49, ISSN: 1574-7891
Matrix‐assisted laser desorption ionisation imaging mass spectrometry (MALDI‐MSI) is a rapidly advancing technique for intact tissue analysis that allows simultaneous localisation and quantification of biomolecules in different histological regions of interest. This approach can potentially offer novel insights into tumour microenvironmental (TME) biochemistry. In this study we employed MALDI‐MSI to evaluate fresh frozen sections of colorectal cancer (CRC) tissue and adjacent healthy mucosa obtained from 12 consenting patients undergoing surgery for confirmed CRC. Specifically, we sought to address three objectives: (1) To identify biochemical differences between different morphological regions within the CRC TME; (2) To characterise the biochemical differences between cancerous and healthy colorectal tissue using MALDI‐MSI; (3) To determine whether MALDI‐MSI profiling of tumour‐adjacent tissue can identify novel metabolic ‘field effects’ associated with cancer. Our results demonstrate that CRC tissue harbours characteristic phospholipid signatures compared with healthy tissue and additionally, different tissue regions within the CRC TME reveal distinct biochemical profiles. Furthermore we observed biochemical differences between tumour‐adjacent and tumour‐remote healthy mucosa. We have referred to this ‘field effect’, exhibited by the tumour locale, as cancer‐adjacent metaboplasia (CAM) and this finding builds on the established concept of field cancerisation.
Veselkov KA, Mirnezami R, Strittmatter N, et al., 2014, Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer, Proceedings of the National Academy of Sciences of the United States of America, Vol: 111, Pages: 1216-1221, ISSN: 0027-8424
Mass spectrometry imaging (MSI) provides the opportunity toinvestigate tumor biology from an entirely novel biochemicalperspective and could lead to the identification of a new pool ofcancer biomarkers. Effective clinical translation of histology-drivenMSI in systems oncology requires precise colocalization of morphologicaland biochemical features as well as advanced methodsfor data treatment and interrogation. Currently proposed MSIworkflows are subject to several limitations, including nonoptimizedraw data preprocessing, imprecise image coregistration,and limited pattern recognition capabilities. Here we outline acomprehensive strategy for histology-driven MSI, using desorptionelectrospray ionization that covers (i) optimized data preprocessingfor improved information recovery; (ii) precise imagecoregistration; and (iii) efficient extraction of tissue-specific molecularion signatures for enhanced biochemical distinction of differenttissue types. The proposed workflow has been used to investigateregion-specific lipid signatures in colorectal cancer tissue. Uniquelipid patterns were observed using this approach according totissue type, and a tissue recognition system using multivariatemolecular ion patterns allowed highly accurate (>98%) identificationof pixels according to morphology (cancer, healthy mucosa,smooth muscle, and microvasculature). This strategy offers uniqueinsights into tumor microenvironmental biochemistry and shouldfacilitate compilation of a large-scale tissue morphology-specificMSI spectral database with which to pursue next-generation, fullyautomated histological approaches.
Abbassi-Ghadi N, Kumar S, Huang J, et al., 2013, Metabolomic profiling of oesophago-gastric cancer: A systematic review, European Journal of Cancer Care, Vol: 49, Pages: 3625-3637, ISSN: 0961-5423
AimsThis review aims to identify metabolomic biomarkers of oesophago-gastric (OG) cancer in human biological samples, and to discuss the dominant metabolic pathways associated with the observed changes.MethodsA systematic review of the literature, up to and including 9th November 2012, was conducted for experimental studies investigating the metabolomic profile of human biological samples from patients with OG cancer compared to a control group. Inclusion criteria for analytical platforms were mass spectrometry or nuclear magnetic resonance spectroscopy. The QUADAS-2 tool was used to assess the quality of the included studies.ResultsTwenty studies met the inclusion criteria and samples utilised for metabolomic analysis included tissue (n = 11), serum (n = 8), urine (n = 1) and gastric content (n = 1). Several metabolites of glycolysis, the tricarboxylic acid cycle, anaerobic respiration and protein/lipid metabolism were found to be significantly different between cancer and control samples. Lactate and fumurate were the most commonly recognised biomarkers of OG cancer related to cellular respiration. Valine, glutamine and glutamate were the most commonly identified amino acid biomarkers. Products of lipid metabolism including saturated and un-saturated free fatty acids, ketones and aldehydes and triacylglycerides were also identified as biomarkers of OG cancer. Unclear risk of bias for patient selection was reported for the majority of studies due to the lack of clarity regarding patient recruitment.ConclusionThe application of metabolomics for biomarker detection in OG cancer presents new opportunities for the purposes of screening and therapeutic monitoring. Future studies should provide clear details of patient selection and develop metabolite assays suitable for progress beyond phase 1 pre-clinical exploratory studies.
Balog J, Sasi-Szabo L, Kinross J, et al., 2013, Intraoperative tissue identification using rapid evaporative ionization mass spectrometry, Science Translational Medicine, Vol: 5, Pages: 1-11, ISSN: 1946-6234
Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that allows near–real-time characterization of human tissue in vivo by analysis of the aerosol (“smoke”) released during electrosurgical dissection. The coupling of REIMS technology with electrosurgery for tissue diagnostics is known as the intelligent knife (iKnife). This study aimed to validate the technique by applying it to the analysis of fresh human tissue samples ex vivo and to demonstrate the translation to real-time use in vivo in a surgical environment. A variety of tissue samples from 302 patients were analyzed in the laboratory, resulting in 1624 cancerous and 1309 noncancerous database entries. The technology was then transferred to the operating theater, where the device was coupled to existing electrosurgical equipment to collect data during a total of 81 resections. Mass spectrometric data were analyzed using multivariate statistical methods, including principal components analysis (PCA) and linear discriminant analysis (LDA), and a spectral identification algorithm using a similar approach was implemented. The REIMS approach differentiated accurately between distinct histological and histopathological tissue types, with malignant tissues yielding chemical characteristics specific to their histopathological subtypes. Tissue identification via intraoperative REIMS matched the postoperative histological diagnosis in 100% (all 81) of the cases studied. The mass spectra reflected lipidomic profiles that varied between distinct histological tumor types and also between primary and metastatic tumors. Thus, in addition to real-time diagnostic information, the spectra provided additional information on divergent tumor biochemistry that may have mechanistic importance in cancer.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.