Scientific Reports mentioning MedicWave and Spectrolyzer
- 2010 A novel AB isoform pattern in CSF reflects secretase inhibition in Alzheimer disease
- 2010 Assessment of the new scoring function (Conference paper)
- 2011 L-DOPA-induced Dyskinesia is Associated with Regional Increase of Striatal Dynorphin Peptides as Elucidated by Imaging Mass Spectrometry
- 2011 MALDI mass spectrometry based molecular phenotyping of CNS glial cells for prediction in mammalian brain tissue
- 2012 Discovery of Novel Urinary Biomarker Candidates for Diagnosis of Prostate Cancer (IMSC 2012 Kyoto, Kenji Nakayama)
- 2012 MALDI-MS-Based Profiling of Serum Proteome – Detection of Changes Related to Progression of Cancer and Response to Anticancer Treatment
- 2013 Data visualization in environmental proteomics
- 2013 Tools for Label-free Peptide Quantification
- 2014 A Review on Mass Spectrometry – Technique and Tools (Yerlekar)
- 2014 Functional Annotation of Orphan Human P450 Enzymes
- 2014 Radiation-Induced Changes in Serum Lipidome of Head and Neck Cancer Patients
- 2015 Identification of serum proteome signatures of locally advanced and a metastatic gastric cancer – a pilot study
- 2016 Clinical applications of MS-based protein quantification
Clinical applications of MS-based protein quantification (2016)
Bassel Sabbagh, Sonani Mindt, Michael Neumaier, & Peter Findeisen
Mass spectrometry-based assays are increasingly important in clinical laboratory medicine and nowadays are already commonly used in several areas of routine diagnostics. These include therapeutic drug monitoring, toxicology, endocrinology, pediatrics, and microbiology. Accordingly, some of the most common analyses are therapeutic drug monitoring of immunosuppressants, vitamin D, steroids, newborn screening, and bacterial identification. However, MS-based quantification of peptides and proteins for routine diagnostic use is rather rare up to now despite excellent analytical specificity and good sensitivity.
In this study, researchers provide an overview over current fit-for-purpose assays for MS-based protein quantification. MedicWave’s software Spectrolyzer is recommended as one of the tools for label-free quantification analyses.
Identification of serum proteome signatures of locally advanced and metastatic gastric cancer: a pilot study (2015)
Agata Abramowicz, Anna Wojakowska, Agnieszka Gdowicz‑Klosok, Joanna Polanska, Pawel Rodziewicz, Pawel Polanowski, Agnieszka Namysl‑Kaletka, Monika Pietrowska, Jerzy Wydmanski, & Piotr Widlak
Potential biomarkers were discovered with a good discrimination power between healthy controls and gastric cancer patients, as well as between patients with locally advanced and metastatic cancer: The gastric cancer is one of the most common and mortal cancer worldwide. The initial asymptomatic development and further nonspecific symptoms result in diagnosis at the advanced stage with poor prognosis. Yet, no clinically useful biomarkers are available for this malignancy, and invasive gastrointestinal endoscopy remains the only reliable option at the moment. Multicomponent peptidome signatures were revealed that allowed good discrimination between healthy controls and cancer patients, as well as between patients with locally advanced and metastatic cancer. Moreover, a LC–MS/MS approach revealed 49 serum proteins with different abundances between healthy donors and cancer patients (predominantly proteins associated with inflammation and acute phase response). Furthermore, 19 serum proteins with different abundances between patients with locally advanced and metastatic cancer were identified (including proteins associated with cytokine/chemokine response and metabolism of nucleic acids). However, neither peptidome profiling nor shotgun proteomics approach allowed detecting serum components discriminating between two subgroups of patients with local disease who either developed or did not develop metastases during follow‑up. The molecular differences between locally advanced and metastatic gastric cancer, as well as more obvious differences between healthy individuals and cancer patients, have marked reflection at the level of serum proteome. However, we have no evidence that features of pre‑treatment serum proteome could predict a risk of cancer dissemination in patients treated due to local disease. Nevertheless, presented data confirmed potential applicability of a serum proteome signature‑based biomarker in diagnostics of gastric cancer.
Radiation-Induced Changes in Serum Lipidome of Head and Neck Cancer Patients (2014)
Karol Jelonek, Monika Pietrowska, Malgorzata Ros, Adam Zagdanski, Agnieszka Suchwalko, Joanna Polanska, Michal Marczyk, Tomasz Rutkowski, Krzysztof Skladowski, Malcolm R. Clench, & Piotr Widlak
Cancer radiotherapy (RT) induces response of the whole patient’s body that could be detected at the blood level. In this study, the researchers aimed to identify changes induced in serum lipidome during RT and characterize their association with doses and volumes of irradiated tissue. The major changes were observed when pre-treatment and within-treatment samples were compared. Levels of several identified phosphatidylcholines, including (PC34), (PC36) and (PC38) variants, and lysophosphatidylcholines, including (LPC16) and (LPC18) variants, were first significantly decreased and then increased in post-treatment samples. Intensities of changes were correlated with doses of radiation received by patients. Of note, such correlations were more frequent when low-to-medium doses of radiation delivered during conformal RT to large volumes of normal tissues were analyzed. Additionally, some radiation-induced changes in serum lipidome were associated with toxicity of the treatment. Obtained results indicated the involvement of choline-related signaling and potential biological importance of exposure to clinically low/medium doses of radiation in patient’s body response to radiation.
During this study, preprocessed spectra were transferred to MedicWave’s software Spectrolyzer for peak detection and binning (peak clustering) analysis. The processing steps performed in the Spectrolyzer software were also consistent with the standard procedures used for spectral data processing.
Mass Spectrometry Application in Biology (Book from 2014)
The explosive growth in scientific research over the past few decades has been extraordinary and has provided a basis for merging of individual aspects of what was once distinct scientific disciplines into more of a systems based approach. Mass spectrometry, once a specialized tool of analytical chemists has now become a vital instrument for scientist in many disciplines in exploring how complex multi-component systems function and how they are impacted by external elements. The application of mass spectrometry has advanced our knowledge in many areas of science, but perhaps one area in particular where astonishing advances have been observed are the collective group of biological sciences. Application of modern instrumentation capable of high mass resolution are routinely used in in the study of drug metabolism and position specific post-translation modifications from both in vitro and in vivo explorations that are critical to the discovery and development of new drug therapies. Mass spectrometry has also been a critical analytical tool in the – omics explosion. Various segment configurations of mass analyzer stages resulting in hybrid instruments including time-of-flight (TOF), quadrupoles (Q), and linear ion traps (LIT) coupled with an array of ionization techniques such as matrix assisted laser desorption/ionization (MALDI), electrospray ionization (ESI) etc. have given scientists the ability to generate critical data in this field. Modern instrument configurations such as QTOF, LIT-TOF and TOF-TOF allow for identification and quantitative analysis of proteins, peptides generated from protein digests, and lipids producing expansive data in proteomics and lipidomics. Likewise this same instrumentation can generate data on the complex aspects of metabolism in the field of metabolomics. A bit more recently, mass spectrometry has been used to develop a molecular imagining technology which provides a means to conduct in situ analysis of thin tissue sections. In this application mass spectrometry is used to produce images of the spatial distribution of molecules of interest within a tissue sample. This application known as “imaging MS” generates a view of biological processes from the distributions of molecules within the sample while maintaining intact histological features. The technique is applicable to various molecules including proteins, peptides, lipids, drugs, and metabolites.
In this book, the author provides a glimpse into some of the many applications of the advancing field of mass spectrometry and its application to complex biological problems. For processing of Mass Spectra, for peak detection and binning (peak clustering) analysis, the author recommends MedicWave’s software Spectrolyzer. The author states that the processing steps performed in the Spectrolyzer software is consistent with the standard procedures used for spectral data processing.
Functional Annotation of Orphan Human P450 Enzymes: Heterologous Expression and Substrate Searches by Metabolomic Approaches (2014)
In this dissertation, the researcher presented different software tools and techniques for LC-MS based metabolomic studies. The researcher recommend MedicWave’s software for LC-MS data visualization, e.g. as heat maps, with signal intensities represented with colors.
A Review on Mass Spectrometry: Technique and Tools (2014)
Ashwini Yerlekar & M.M. Kshirsagar
Protein structure prediction has gain important in area of life sciences, because of its complex structure. The protein-protein interaction is necessary to study the behavior of protein in a specific environment, and study molecular relationship in living systems. Therefore, large scale proteomics technologies are required to measure physical connection of proteins in living organisms. Mass Spectrometry uses the technique to measure mass-to-charge ratio of ion. It‘s an evolving technique for characterization of proteins. The researchers of this study focus on addressing data analysis methods for Mass Spectrometry analyses, and they recommend Spectrolyzer (formerly named Medicwave Bioinformatics Suite) for LC-MS de novo sequencing.
Tools for Label-free Peptide Quantification (2013)
Sven Nahnsen, Chris Bielow, Knut Reinert, & Oliver Kohlbacher
The researchers of this study argued that the increasing scale and complexity of quantitative proteomics studies complicate subsequent analysis of the acquired data. They argue that label-free quantification is a method that scales particularly well with respect to the number of samples. It is thus an excellent alternative to labeling techniques. The researchers review the state of the art with respect to computational tools for label-free quantification in untargeted proteomics, and they recommended among other software MedicWave’s Spectrolyzer software for label-free quantitative analyses.
Data visualization in environmental proteomics (2013)
Henry Mehlan, Frank Schmidt, Stefan Weiss, Julia Schuler, Stephan Fuchs, Katharina Riedel, & Jorg Bernhardt
The researchers in this study discusses the importance of visualization tools for proteomics studies. Including the display of single but also complex data. Visual approaches such as microcharts, heat maps, stream graphs, and tree maps will be brought to the reader’s attention and demonstrated by utilizing real data sets. MedicWave’s software Spectrolyzer is recommended as a LC-MS raw data viewer for convex hull feature visualization.
MALDI-MS-Based Profiling of Serum Proteome: Detection of Changes Related to Progression of Cancer and Response to Anticancer Treatment (2012)
Monika Pietrowska & Piotr Widłak
Mass spectrometry-based analyses of the low-molecular-weight fraction of serum proteome allow identifying proteome profiles (signatures) that are potentially useful in detection and classification of cancer. The researchers of this study argued that among all cancer biomarker candidates that can be identified by serum proteome profiling, those of value were rather those reflecting overall influence of a disease (and the therapy) upon the human organism, than products of cancer-specific genes. For this study, among other software, MedicWave’s software Spectrolyzer was used.
In spite of tens of published studies the real potential of MALDI/SELDI-based serum proteome profiling in clinical diagnostics is not clearly defined so far. Even though these studies have showed that multipeptide signatures selected in numerical tests have some potential value for classification and differentiation of cancer, none of proposed serum peptide signatures has been approved for routine diagnostics. Lack of standardization of methodological details, both experimental and computational, is an important problem in MS-based blood proteome profiling. It appears that guidelines for standardization of these multiparametric analyses should be generally accepted in the field and that identified marker candidates need to be confirmed in multicenter biasfree prospective validation studies.
Discovery of Novel Urinary Biomarker Candidates for Diagnosis of Prostate Cancer (2012)
Kenji NAKAYAMA, Takahiro INOUE, Sadanori SEKIYA, Naoki TERADA, Minoru SUZUKI, Hiroki TSUMOTO, Takashi HARA, Shin-Ichiro KAWABATA, Shinichi IWAMOTO, Kazuharu SHIMIZU, Osamu OGAWA, & Koichi TANAKA
The m/z2331 peptides have shown to be a candidate biomarker for the detection of prostate cancer: In this conference papers, researchers used peptidomic and proteomic analyses of urine samples using a matrix assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF/MS) in order to discover novel biomarkers for diagnosis of Prostate Cancer (PCa). In order to perform the data analysis on the urine samples, MedicWave’s Spectrolyzer software was applied. The researchers discovered a large amount of the m/z2331 peptides in the urine samples of the patients with prostate cancer after DRE. The urinary peptides of prostate cancer patients significantly increased rather than those in the urine samples of both the patients with benign prostatic hyperplasia (BPH) and healthy subjects. Therefore, further examinations concerning these peptides are recommended to prove that they can be a candidate biomarker for the detection of prostate cancer and for the discrimination between prostate cancer (PCa) and benign prostatic hyperplasia (BPH).
MALDI mass spectrometry based molecular phenotyping of CNS glial cells for prediction in mammalian brain tissue (2011)
Jörg Hanrieder, Grzegorz Wicher, Jonas Bergquist, Malin Andersson, & Åsa Fex-Svenningsen
MALDI-TOF-MS can be used to discriminate glial cell types using principal component analysis (PCA): In this study, researchers analyzed the intact cell suspensions by MALDI-TOF-MS, resulting in characteristic mass spectra profiles that discriminated glial cell types using principal component analysis. MALDI imaging MS was performed, and signature masses were employed as molecular tracers for prediction of oligodendroglial and astroglial localization in brain tissue. The different cell type specific protein distributions in tissue were validated using immunohistochemistry. MALDI-MS-based intact cell mass spectrometry (ICMS) of intact neuroglia is a simple and straightforward approach for characterization and discrimination of different cell types with molecular specificity. MedicWave’s data processing software was used during this study. This software is currently part of MedicWave’s software Spectrolyzer, as well as the principal component analysis (PCA) algorithm.
L-DOPA-induced Dyskinesia is Associated with Regional Increase of Striatal Dynorphin Peptides as Elucidated by Imaging Mass Spectrometry (2011)
Jörg Hanrieder, Anna Ljungdahl, Maria Fälth, Sofie Eriksson Mammo, Jonas Bergquist, & Malin Andersson
The importance of MALDI IMS analysis for the study of molecular dynamics in neurological diseases: In this study, researchers showed that MALDI IMS of striatal sections from Pdyn knockout mice were able to verify the identity of fully processed dynorphin peptides and the presence of endogenous des-tyrosine -neoendorphin. Des-tyrosine dynorphins display reduced opioid receptor binding and this points to possible novel nonopioid receptor mediated changes in the striatum of dyskinetic rats. Because des-tyrosine dynorphins can only be detected by mass spectrometry, as no antibodies are available, these findings highlight the importance of MALDI IMS analysis for the study of molecular dynamics in neurological diseases. MedicWave’s data processing software was used during this study. This software is currently part of MedicWave’s software Spectrolyzer.
Assessment of the new scoring function for protein identification by PMF (2010)
Hanna Kaminska, & Thorsteinn Rognvaldsson
A novel scoring algorithm outperforms Mascot in protein identification: In this conference paper, researchers developed a novel probability-based scoring scheme based on an innovative idea. The results of the first experiment showed that the new developed scoring method behaved noticeably better in the areas of (x,y) space representing high contamination and where the number of true masses was small. The second and additional experiment showed that this new scoring algorithm properly identified proteins to 49% while Mascot only properly identified proteins to 47%. This study therefore showed that this new scoring algorithm developed for MedicWave was more efficient than Mascot in this simulation region.
A novel Aβ isoform pattern in CSF reflects γ-secretase inhibition in Alzheimer disease (2010)
Erik Portelius, Robert A Dean, Mikael K Gustavsson, Ulf Andreasson, Henrik Zetterberg, Eric Siemers, and Kaj Blennow
Aβ isoforms may be novel sensitive biomarkers for monitoring the biochemical effect in Alzheimer disease clinical trials: In this Alzhimer disease study, researchers from the Sahlgrenska Academy were able to, by using targeted proteomics techniques, identify several short Aβ isoforms such as Aβ1-16 that in experimental settings increased during γ-secretase inhibitor treatment. Thus, the study tested the hypothesis that these shorter Aβ isoforms could be used as biomarkers of γ-secretase inhibitor treatment in clinical trials. According to this study’s results, the cerebrospinal fluid (CSF) levels of Aβ1-14, Aβ1-15, and Aβ1-16 showed a dose-dependent increase, and therefore the researchers believe that these Aβ isoforms may be novel sensitive biomarkers to monitor the biochemical effect in clinical trials. The acquired mass spectrometry data that were analyzed during this study were analyzed with the help of the software Spectrolyzer (formerly named Medicwave Bioinformatics Suite).