MDM2-Dependent Rewiring of Metabolomic and Lipidomic Profiles in Dedifferentiated Liposarcoma Models
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ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Cultured Cells
PROVIDER: ST001405 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:Dedifferentiated liposarcoma (DDLPS) is an aggressive mesenchymal cancer marked by amplification of MDM2, an inhibitor of the tumor suppressor TP53. DDLPS patients with higher MDM2 amplification have lower chemotherapy sensitivity and worse outcome than patients with lower MDM2 amplification. We hypothesized that MDM2 amplification levels may be associated with changes in DDLPS metabolism. Six patient-derived DDLPS cell line models were subject to comprehensive metabolomic (Metabolon) and lipidomic (SCIEX 5600 TripleTOF-MS) profiling to assess associations with MDM2 amplification and their responses to metabolic perturbations. Comparing metabolomic profiles between MDM2 higher and lower amplification cells yielded a total of 17 differentially abundant metabolites across both panels (FDR < 0.05, log2 fold change < 0.75), including ceramides, glycosylated ceramides, and sphingomyelins. Disruption of lipid metabolism through statin administration resulted in a chemo-sensitive phenotype in MDM2 lower cell lines only, suggesting that lipid metabolism may be a large contributor to the more aggressive nature of MDM2 higher DDLPS tumors. This study is the first to provide comprehensive metabolomic and lipidomic characterization of DDLPS cell lines and provides evidence for MDM2-dependent differential molecular mechanisms that are critical factors in chemoresistance and could thus affect patient outcome.
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Project description:Coffee (Coffea spp.) is one of the most popular refreshing beverages globally. Coffee lipid diversity has untapped potential for improving coffee marketability because lipids contribute significantly to both the health benefits and cup quality of coffee. However, in spite of its potential importance, there have not been extensive studies of lipids among C. canephora genotypes. In this study, ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) profiling of lipid molecules was performed for 30 genotypes consisting of 15 cultivated and 15 conserved genotypes of C. canephora in Southwestern Nigeria. We identified nine classes of lipids in the 30 genotypes which belong to the 'Niaouli', 'Kouillou' and 'Java Robusta' group: among these, the most abundant lipid class was the triacylglycerols, followed by the fatty acyls group. Although 'Niaouli' diverged from the 'Kouillou' and 'Java Robusta' genotypes when their lipid profiles were compared, there was greater similarity in their lipid composition by multivariate analysis, compared to that observed when their primary metabolites and especially their secondary metabolite profiles were examined. However, distinctions could be made among genotypes. Members of the fatty acyls group had the greatest power to discriminate among genotypes, however, lipids that were low in abundance e.g. a cholesterol ester (20:3), and phosphotidylethanolamine (34:0) were also helpful to understand the relationships among C. canephora genotypes. The divergent lipid profiles identified among the C. canephora genotypes, correlated with their Single Nucleotide Polymorphism grouping as assessed by genotype-by-sequencing, and will be exploited to improve coffee cup quality.
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Project description:Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT) in 50 individuals, 25 with normal (NGT) and 25 with impaired glucose tolerance (IGT). Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for "active modules"--regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved disease classification via the interrogation of specific transporter activities.
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Project description:BackgroundSepsis is defined as a dysfunctional host response to infection. The diverse clinical presentations of sepsis pose diagnostic challenges and there is a demand for enhanced diagnostic markers for sepsis as well as an understanding of the underlying pathological mechanisms involved in sepsis. From this perspective, metabolomics has emerged as a potentially valuable tool for aiding in the early identification of sepsis that could highlight key metabolic pathways and underlying pathological mechanisms.ObjectiveThe aim of this investigation is to explore the early metabolomic and lipidomic profiles in a prospective cohort where plasma samples (n = 138) were obtained during ambulance transport among patients with infection according to clinical judgement who subsequently developed sepsis, patients who developed non-septic infection, and symptomatic controls without an infection.MethodsMultiplatform metabolomics and lipidomics were performed using UHPLC-MS/MS and UHPLC-QTOFMS. Uni- and multivariable analysis were used to identify metabolite profiles in sepsis vs symptomatic control and sepsis vs non-septic infection.ResultsUnivariable analysis disclosed that out of the 457 annotated metabolites measured across three different platforms, 23 polar, 27 semipolar metabolites and 133 molecular lipids exhibited significant differences between patients who developed sepsis and symptomatic controls following correction for multiple testing. Furthermore, 84 metabolites remained significantly different between sepsis and symptomatic controls following adjustment for age, sex, and Charlson comorbidity score. Notably, no significant differences were identified in metabolites levels when comparing patients with sepsis and non-septic infection in univariable and multivariable analyses.ConclusionOverall, we found that the metabolome, including the lipidome, was decreased in patients experiencing infection and sepsis, with no significant differences between the two conditions. This finding indicates that the observed metabolic profiles are shared between both infection and sepsis, rather than being exclusive to sepsis alone.
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Project description:IntroductionCongenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these.ObjectiveTo evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD.MethodsWe performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling.Results499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides.ConclusionsHere, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.
| S-EPMC11219374 | biostudies-literature
Project description:BackgroundThe risk of adult onset cardiovascular and metabolic (cardiometabolic) disease accrues from early life. Infection is ubiquitous in infancy and induces inflammation, a key cardiometabolic risk factor, but the relationship between infection, inflammation, and metabolic profiles in early childhood remains unexplored. We investigated relationships between infection and plasma metabolomic and lipidomic profiles at age 6 and 12 months, and mediation of these associations by inflammation.MethodsMatched infection, metabolomics, and lipidomics data were generated from 555 infants in a pre-birth longitudinal cohort. Infection data from birth to 12 months were parent-reported (total infections at age 1, 3, 6, 9, and 12 months), inflammation markers (high-sensitivity C-reactive protein [hsCRP]; glycoprotein acetyls [GlycA]) were quantified at 12 months. Metabolic profiles were 12-month plasma nuclear magnetic resonance metabolomics (228 metabolites) and liquid chromatography/mass spectrometry lipidomics (776 lipids). Associations were evaluated with multivariable linear regression models. In secondary analyses, corresponding inflammation and metabolic data from birth (serum) and 6-month (plasma) time points were used.ResultsAt 12 months, more frequent infant infections were associated with adverse metabolomic (elevated inflammation markers, triglycerides and phenylalanine, and lower high-density lipoprotein [HDL] cholesterol and apolipoprotein A1) and lipidomic profiles (elevated phosphatidylethanolamines and lower trihexosylceramides, dehydrocholesteryl esters, and plasmalogens). Similar, more marked, profiles were observed with higher GlycA, but not hsCRP. GlycA mediated a substantial proportion of the relationship between infection and metabolome/lipidome, with hsCRP generally mediating a lower proportion. Analogous relationships were observed between infection and 6-month inflammation, HDL cholesterol, and apolipoprotein A1.ConclusionsInfants with a greater infection burden in the first year of life had proinflammatory and proatherogenic plasma metabolomic/lipidomic profiles at 12 months of age that in adults are indicative of heightened risk of cardiovascular disease, obesity, and type 2 diabetes. These findings suggest potentially modifiable pathways linking early life infection and inflammation with subsequent cardiometabolic risk.FundingThe establishment work and infrastructure for the BIS was provided by the Murdoch Children's Research Institute (MCRI), Deakin University, and Barwon Health. Subsequent funding was secured from National Health and Medical Research Council of Australia (NHMRC), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women's Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Minderoo Foundation, the Ilhan Food Allergy Foundation, GMHBA, Vanguard Investments Australia Ltd, and the Percy Baxter Charitable Trust, Perpetual Trustees. In-kind support was provided by the Cotton On Foundation and CreativeForce. The study sponsors were not involved in the collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication. Research at MCRI is supported by the Victorian Government's Operational Infrastructure Support Program. This work was also supported by NHMRC Senior Research Fellowships to ALP (1008396); DB (1064629); and RS (1045161) , NHMRC Investigator Grants to ALP (1110200) and DB (1175744), NHMRC-A*STAR project grant (1149047). TM is supported by an MCRI ECR Fellowship. SB is supported by the Dutch Research Council (452173113).
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| S-EPMC7540372 | biostudies-literature
Project description:The pandemic of the coronavirus disease 2019 (COVID-19) has become a global public health crisis. The symptoms of COVID-19 range from mild to severe, but the physiological changes associated with COVID-19 are barely understood. In this study, we performed targeted metabolomic and lipidomic analyses of plasma from a cohort of patients with COVID-19 who had experienced different symptoms. We found that metabolite and lipid alterations exhibit apparent correlation with the course of disease in these patients, indicating that the development of COVID-19 affected their whole-body metabolism. In particular, malic acid of the TCA cycle and carbamoyl phosphate of the urea cycle result in altered energy metabolism and hepatic dysfunction, respectively. It should be noted that carbamoyl phosphate is profoundly down-regulated in patients who died compared with patients with mild symptoms. And, more importantly, guanosine monophosphate (GMP), which is mediated not only by GMP synthase but also by CD39 and CD73, is significantly changed between healthy subjects and patients with COVID-19, as well as between the mild and fatal cases. In addition, dyslipidemia was observed in patients with COVID-19. Overall, the disturbed metabolic patterns have been found to align with the progress and severity of COVID-19. This work provides valuable knowledge about plasma biomarkers associated with COVID-19 and potential therapeutic targets, as well as an important resource for further studies of the pathogenesis of COVID-19.
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