Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data

Karnovsky, Alla; Weymouth, Terry E.; Hull, Tim; Tarcea, V. Glenn; Scardoni, Giovanni; Laudanna, Carlo; Sartor, Maureen A.; Stringer, Kathleen A.; Jagadish, H. V.; Burant, Charles F.; Athey, Brian D.; Omenn, Gilbert S.

doi:10.1093/bioinformatics/btr661

Cited by 377 publications

(284 citation statements)

References 43 publications

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“…19 Visualization of metabolic pathways was achieved by using metscape 2 running on cytoscape. 20,21 The clinical characteristics, molecular features, and outcomes were compared between CN-AML with low and high PRSs. For prognosis analysis, complete remission (CR) was defined as previously described.…”

Section: Data Treatment and Statistical Analysismentioning

confidence: 99%

A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value

Chen

Wang

Zhao

et al. 2014

Blood

248

273

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• Acute myeloid leukemia (AML) patients present an altered glucose metabolism signature.• A panel of 6 metabolite biomarkers involved in glucose metabolism are identified with prognostic value for cytogenetically normal AML.Acute myeloid leukemia (AML) is a group of hematological malignancies with high heterogeneity. There is an increasing need to improve the risk stratification of AML patients, including those with normal cytogenetics, using molecular biomarkers. Here, we report a metabolomics study that identified a distinct glucose metabolism signature with 400 AML patients and 446 healthy controls. The glucose metabolism signature comprises a panel of 6 serum metabolite markers, which demonstrated prognostic value in cytogenetically normal AML patients. We generated a prognosis risk score (PRS) with 6 metabolite markers for each patient using principal component analysis. A low PRS was able to predict patients with poor survival independently of wellestablished markers. We further compared the gene expression patterns of AML blast cells between low and high PRS groups, which correlated well to the metabolic pathways involving the 6 metabolite markers, with enhanced glycolysis and trichloracetic acid cycle at gene expression level in low PRS group. In vitro results demonstrated enhanced glycolysis contributed to decreased sensitivity to antileukemic agent arabinofuranosyl cytidine (Ara-C), whereas inhibition of glycolysis suppressed AML cell proliferation and potentiated cytotoxicity of Ara-C. Our study provides strong evidence for the use of serum metabolites and metabolic pathways as novel prognostic markers and potential therapeutic targets for AML. (Blood. 2014;124(10):1645-1654

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Section: Data Treatment and Statistical Analysismentioning

confidence: 99%

A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value

Chen

Wang

Zhao

et al. 2014

Blood

248

273

View full text Add to dashboard Cite

show abstract

“…Integrates different -omics levels by relying on existing biological knowledge gathered from metabolic pathways such as Kegg and wikipathways (Kutmon et al 2015) InCroMAP and IMPALA for integrated pathway-based analysis Eichner et al (2014), Kamburov et al (2011) SAMNetWeb to generate biological networks with transcriptomics and proteomics data Gosline et al (2015) MetScape cytoscape plugin to produce metabolic networks from transcriptomics and metabolite data Karnovsky et al (2012) …”

Section: Pathway-based Integrationmentioning

confidence: 99%

Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes

et al. 2015

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Worldwide population is aging, and a large part of the growing burden associated with age-related conditions can be prevented or delayed by promoting healthy lifestyle and normalizing metabolic risk factors. However, a better understanding of the pleiotropic effects of available nutritional interventions and their influence on the multiple processes affected by aging is needed to select and implement the most promising actions. New methods of analysis are required to tackle the complexity of the interplay between nutritional interventions and aging, and to make sense of a growing amount of -omics data being produced for this purpose. In this paper, we review how various systems biology-inspired methods of analysis can be applied to the study of the molecular basis of nutritional interventions promoting healthy aging, notably caloric restriction and polyphenol supplementation. We specifically focus on the role that different versions of network analysis, molecular signature identification and multiomics data integration are playing in elucidating the complex mechanisms underlying nutrition, and provide some examples on how to extend the application of these methods using available microarray data.

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“…Compound network were generated and visualized using Cytoscape based Metscape plugin (http://www.metscape.ncibi.org/tryplugin. html;Karnovsky et al 2012). Markov clustering based module analysis was performed to analyze the complex biological network(Zhu et al 2015).…”

mentioning

confidence: 99%

Identification of serum metabolic markers for diagnosis of women with dormant genital tuberculosis

et al. 2016

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Introduction Genital tuberculosis (GTB) in women is one of the common causes of infertility in emerging countries. As an intracellular pathogen, Mycobacterium tuberculosis in the endometrium significantly alters the host metabolism in dormant GTB cases. Nuclear magnetic resonance (NMR) based metabolic profiling has emerged as a useful tool for identification of biomarkers in biological fluids. Objective To investigate NMR based serum metabolic profile of dormant GTB women as compared to controls. Methods Dormant GTB women (n = 26) and unexplained infertile women (controls; n = 26), healthy proven fertile women undergoing voluntary sterilization (n = 25) and women undergoing recurrent spontaneous miscarriage (RSM) (n = 27) were included in the study. 700 MHz proton NMR spectra of serum collected from these patients were recorded. Multivariate analysis including principal component analysis, partial least squares discriminant analysis and orthogonal projection to latent structurediscriminant analysis was applied to all the spectra. Association of dysregulated serum metabolites with our earlier findings related to altered endometrial tissue metabolites in dormant GTB women was studied using multiple correlation analysis. Results This study indicates a clear metabolic differentiation between women with dormant GTB and controls. Metabolites including 3-hydroxybutyrate, succinate, citrate, acetate, L-glutamine, L-lysine, glutamate, L-threonine and 1-methyl histidine were found to be significantly upregulated in serum of women with dormant GTB compared with controls. Pearson's correlation analysis showed a significant correlation between the expression of endometrial tissue and serum metabolites. Conclusions The set of identified metabolites may be considered as candidate markers for the diagnosis of dormant GTB and help clinicians in early therapeutic management.

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Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 377 publications

References 43 publications

A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value

A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value

Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes

Identification of serum metabolic markers for diagnosis of women with dormant genital tuberculosis

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