A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

<p>Abstract</p> <p>Introduction</p> <p>Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma) are used in our study.</p> <p>Method</p> <p>Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.</p> <p>Results</p> <p>Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.</p> <p>Conclusion</p> <p>The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.</p

Аудіовізуальні особливості пейзажистики ранніх балад Т. Шевченка

(uk) У статті осмислюються аудіовізуальні особливості пейзажотворення в ранній творчості Тараса Шевченка. На матеріалі балад «Причинна», «Тополя», «Утоплена» розглядається сугестивна майстерність поета, здатність до живописання словом, створення ілюзії присутності реципієнта в художньому світі твору.(en) Audiovisual features of the landscape descriptionin the early Shevchenko’s ballads. The paper interprets audiovisual features of the landscape description in the early works of Taras Shevchenko. Suggestive poetic skill, capability of word skill, creating the illusion of recipient’s presence in the worldof the art works are considered on the material of the ballads "The Girl under a Spell", "Poplar", "A Drowned Girl"

Treating Cancer as an Infectious Disease—Viral Antigens as Novel Targets for Treatment and Potential Prevention of Tumors of Viral Etiology

Nearly 20% of human cancers worldwide have an infectious etiology with the most prominent examples being hepatitis B and C virus-associated hepatocellular carcinoma and human papilloma virus-associated cervical cancer. There is an urgent need to find new approaches to treatment and prevention of virus-associated cancers.Viral antigens have not been previously considered as targets for treatment or prevention of virus-associated cancers. We hypothesized that it was possible to treat experimental HPV16-associated cervical cancer (CC) and Hepatitis B-associated hepatocellular carcinoma (HCC) by targeting viral antigens expressed on cancer cells with radiolabeled antibodies to viral antigens. Treatment of experimental CC and HCC tumors with (188)Re-labeled mAbs to E6 and HBx viral proteins, respectively, resulted in significant and dose-dependent retardation of tumor growth in comparison with untreated mice or mice treated with unlabeled antibodies.This strategy is fundamentally different from the prior uses of radioimmunotherapy in oncology, which targeted tumor-associated human antigens and promises increased specificity and minimal toxicity of treatment. It also raises an exciting possibility to prevent virus-associated cancers in chronically infected patients by eliminating cells infected with oncogenic viruses before they transform into cancer

A comparative metabolomics investigation of flavonoid variation in colored faba bean flowers

IntroductionFaba bean (Vicia faba L.) flowers are edible and used as garnishes because of their aroma, sweet flavor and attractive colors. Anthocyanins are the common plant pigments that give flowers their vivid colors, whereas non-anthocyanin flavonoids can serve as co-pigments that can modify the color intensity of flowers.ObjectivesTo explore the polyphenol diversity and differences in standard and wing petals of faba bean flowers; and identify glycosylated flavonoids that contribute to flower color.MethodsFlower standard and wing petals from 30 faba bean genotypes (eight color groups with a total of 60 samples) were used for polyphenol extraction. Samples were analyzed using a targeted method and a semi-untargeted analysis using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with photodiode array (PDA) detection. Compound Discoverer software was used for polyphenol identification and multivariate analysis.ResultsThe semi-untargeted analysis guided by the PDA detected 90 flavonoid metabolites present in faba bean flower petals. Ten anthocyanins largely influenced the flower colors, but other flavonoids (63 flavonols and 12 flavones) found with variable levels in different flower color groups appeared to also influence color, especially in mixed colors.ConclusionAnalysis of the different colored faba bean flowers confirmed that the color variation between the flowers was mainly controlled by anthocyanins in brown, red and purple-red flowers. Of the other flavonoids, multiglycosylated kaempferols were abundant in white and brown flowers, monoglycosylated kaempferols were common in red and purple-red flowers, and quercetin and apigenin glycosides were abundant co-pigments in purple-red flowers.Peer reviewe

Advanced mass spectrometry-based multi-omics technologies for exploring the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the primary hepatic malignancies and is the third most common cause of cancer related death worldwide. Although a wealth of knowledge has been gained concerning the initiation and progression of HCC over the last half century, efforts to improve our understanding of its pathogenesis at a molecular level are still greatly needed, to enable clinicians to enhance the standards of the current diagnosis and treatment of HCC. In the post-genome era, advanced mass spectrometry driven multi-omics technologies (e.g., profiling of DNA damage adducts, RNA modification profiling, proteomics, and metabolomics) stand at the interface between chemistry and biology, and have yielded valuable outcomes from the study of a diversity of complicated diseases. Particularly, these technologies are being broadly used to dissect various biological aspects of HCC with the purpose of biomarker discovery, interrogating pathogenesis as well as for therapeutic discovery. This proof of knowledge-based critical review aims at exploring the selected applications of those defined omics technologies in the HCC niche with an emphasis on translational applications driven by advanced mass spectrometry, toward the specific clinical use for HCC patients. This approach will enable the biomedical community, through both basic research and the clinical sciences, to enhance the applicability of mass spectrometry-based omics technologies in dissecting the pathogenesis of HCC and could lead to novel therapeutic discoveries for HCC

Detection of Fungal Jasmonates by Liquid Chromatography Paired with Mass Spectrometry

10.1007/978-1-0716-0142-6_142085189-19