Abstract:Oxidized phospholipids (oxPAPC) induce endothelial dysfunction and atherosclerosis. Here we show that oxPAPC induce a gene network regulating serine-glycine metabolism with the mitochondrial methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD2) as a causal regulator using integrative network modeling and Bayesian network analysis in human aortic endothelial cells. The cluster is activated in human plaque material and by atherogenic lipoproteins isolated from plasma of patients with coronary artery di… Show more
“…Nevertheless, macrophages are not the only target of oxPAPC. Our data on GM-CSF-derived phagocytes as well as data in the literature on endothelial cells 43 demonstrate that oxPAPC-dependent metabolic changes are not unique to macrophages or even immune cells. It will be important in future studies to address the moieties contained in oxPAPC that alter the metabolism of other cell types and how these changes affect inflammation and/or atherosclerosis.…”
Pathogen-associated molecular patterns (PAMPs) have the capacity to couple inflammatory gene expression to changes in macrophage metabolism, both of which influence subsequent inflammatory activities. Similar to their microbial counterparts, several self-encoded damageassociated molecular patterns (DAMPs) induce inflammatory gene expression. However, whether this symmetry in host responses between PAMPs and DAMPs extends to metabolic shifts is unclear. Here we report that the self-encoded oxidized phospholipid oxPAPC alters the metabolism of macrophages exposed to lipopolysaccharide (LPS). While cells activated by LPS rely exclusively on glycolysis, macrophages exposed to oxPAPC also use mitochondrial respiration, feed the Krebs cycle with glutamine and favor the accumulation of oxaloacetate in the cytoplasm: this metabolite potentiates IL-1β production, resulting in hyperinflammation. Similar metabolic adaptions occur in vivo in hypercholesterolemic mice and human subjects. Drugs that interfere with oxPAPC-driven metabolic changes reduce atherosclerotic plaque formation in mice, thereby underscoring the importance of DAMP-mediated activities in pathophysiological conditions. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:
“…Nevertheless, macrophages are not the only target of oxPAPC. Our data on GM-CSF-derived phagocytes as well as data in the literature on endothelial cells 43 demonstrate that oxPAPC-dependent metabolic changes are not unique to macrophages or even immune cells. It will be important in future studies to address the moieties contained in oxPAPC that alter the metabolism of other cell types and how these changes affect inflammation and/or atherosclerosis.…”
Pathogen-associated molecular patterns (PAMPs) have the capacity to couple inflammatory gene expression to changes in macrophage metabolism, both of which influence subsequent inflammatory activities. Similar to their microbial counterparts, several self-encoded damageassociated molecular patterns (DAMPs) induce inflammatory gene expression. However, whether this symmetry in host responses between PAMPs and DAMPs extends to metabolic shifts is unclear. Here we report that the self-encoded oxidized phospholipid oxPAPC alters the metabolism of macrophages exposed to lipopolysaccharide (LPS). While cells activated by LPS rely exclusively on glycolysis, macrophages exposed to oxPAPC also use mitochondrial respiration, feed the Krebs cycle with glutamine and favor the accumulation of oxaloacetate in the cytoplasm: this metabolite potentiates IL-1β production, resulting in hyperinflammation. Similar metabolic adaptions occur in vivo in hypercholesterolemic mice and human subjects. Drugs that interfere with oxPAPC-driven metabolic changes reduce atherosclerotic plaque formation in mice, thereby underscoring the importance of DAMP-mediated activities in pathophysiological conditions. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:
“…Bayesian network analysis has been used to identify diagnostic and prognostic markers. It can describe the mutual relationships among biological variables and identify key driver(s) in complex biological networks [17, 18]. The network is generated using combined conditional probabilities of each node (or variable) affecting all other nodes in the network.…”
Objective
This study evaluates the utility of urinary pro-thrombotic molecules such as tissue factor (TF), anti-thrombotic molecules such as tissue factor pathway inhibitor (TFPI), and fibrinolytic molecules such as plasmin and d-dimer as biomarkers of lupus nephritis (LN).
Methods
Urine samples from 113 biopsy-proven LN patients (89 active LN and 24 inactive LN), 45 chronic kidney disease patients, and 41 healthy controls were examined for d-dimer, plasmin, TF, and TFPI levels by ELISA. The area under the receiver operating characteristic curve (AUC) analysis, multivariate regression analysis, and Bayesian network analysis were performed to assess the diagnostic value of the assayed molecules in LN.
Results
Although urinary d-dimer, plasmin, TF, and TFPI were all elevated in active LN compared to all control groups, and correlated with rSLEDAI and SLICC RAS disease activity indices, urine plasmin emerged as the strongest independent predictor of eGFR and renal disease status, by multivariate regression analysis and Bayesian network analysis. Whereas urine plasmin discriminated active LN from inactive disease with an AUC of 0.84, the combination of urine plasmin and TFPI discriminated ALN from ILN with an AUC of 0.86, with both surpassing the specificity and positive predictive value of traditional markers such as anti-dsDNA and complement C3.
Conclusion
Both thrombogenic and thrombolytic cascades appear to be upregulated in lupus nephritis, with proteins from both cascades appearing in the urine. Of the coagulation cascade proteins surveyed, urine plasmin emerges as the strongest predictor of eGFR and clinical renal disease in patients with LN.
Electronic supplementary material
The online version of this article (10.1186/s13075-019-1959-y) contains supplementary material, which is available to authorized users.
“…A, Images of the subcutaneous tumours formed in the nude mice after injection of shMTHFD2 and shCtrl transfected H1299 cells. 10 The exact mechanistic role of MTHFD2 in cancer is still a topic in the future. C, Mean tumour weights 48 d after transplantation was shown.…”
Section: Discussionmentioning
confidence: 99%
“…MTHFD2 plays a critical role in controlling N6‐methyladenosine (m6A) methylation of HIF‐2α levels and the oxidation of methylene‐THF to 10‐formyl‐THF in mitochondria, which results in promoted metabolic reprograming and tumour growth . In addition, MTHFD2‐dependent glycine synthesis is a prerequisite for angiogenesis . The exact mechanistic role of MTHFD2 in cancer is still a topic in the future.…”
Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a bifunctional enzyme located in the mitochondria. It has been reported to be overexpressed in several malignancies. However, the relationship between the expression of MTHFD2 and non-small cell lung cancer (NSCLC) remains largely unknown. In this study, we found that MTHFD2 was significantly overexpressed in NSCLC tissues and cell lines. Knockdown of MTHFD2 resulted in reduced cell growth and tumorigenicity in vitro and in vivo. Besides, the mRNA and protein expression level of cell cycle genes, such as CCNA2, MCM7 and SKP2, was decreased in MTHFD2 knockdown H1299 cells. Our results indicate that the inhibitory effect of MTHFD2 knockdown on NSCLC may be mediated via suppressing cell cycle-related genes. These findings delineate the role of MTHFD2 in the development of NSCLC and may have potential applications in the treatment of NSCLC. K E Y W O R D S bioinformatics, cell cycle, methylenetetrahydrofolate dehydrogenase 2, non-small cell lung cancer | 1569 YU et al. S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Yu C, Yang L, Cai M, et al. Downregulation of MTHFD2 inhibits NSCLC progression by suppressing cycle-related genes. J Cell Mol Med.
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