Molecules In Metabolic Pathways Research Articles

Pathogenetic significance of long non-coding RNAs in the development of thoracic and abdominal aortic aneurysms

Aortic aneurysm (AA) is a life-threatening condition with high prevalence and risk of severe complications. The aim of this review was to summarize the data on the role of long non-coding RNAs (lncRNAs) in the development of aortic aneurysms of various locations. Over a less than decade of lncRNA studies in AA, using experimental and bioinformatic approaches, scientists have obtained the data confirming the involvement of these molecules in metabolic pathways and pathogenetic mechanisms critical for the development of aneurysms. Regardless of the location of the pathological process (thoracic or abdominal aorta), changes in the expression levels of various lncRNAs in the tissue of the affected vessels have been established. The consistency of changes in the expression level of lncRNA, mRNA and microRNA in aortic tissues during AA development has been recorded. Also, a number of regulatory networks those are pathogenetically significant for biochemical pathways and cellular processes have been identified, in which lncRNAs act as the competing endogenous RNAs (ceRNA networks). Moreover, on the one hand, the same lncRNA can be involved in different ceRNA networks and regulate different biochemical and cellular events; on the other hand, the same pathological process is controlled by different lncRNAs. Despite some similarities in pathogenesis and the overlap of the lncRNA spectrum, identical ceRNA networks have not been described for abdominal and thoracic aortic aneurysms. Interactions between lncRNA and protein molecules, including those involved in epigenetic processes at other levels, have also been identified as potentially relevant to the pathogenesis of aortic aneurysm. For some lncRNAs, correlations of the expression level with clinically significant aortic features and biochemical findings AA were observed. The identification of regulatory RNAs that are functionally significant for aneurysm development is important for clarification of the disease pathogenesis and will also provide a basis for early diagnosis and development of new preventive and therapeutic drugs.

Pathogenetic Significance of Long Non-Coding RNAs in the Development of Thoracic and Abdominal Aortic Aneurysms.

Aortic aneurysm (AA) is a life-threatening condition with a high prevalence and risk of severe complications. The aim of this review was to summarize the data on the role of long non-coding RNAs (lncRNAs) in the development of AAs of various location. Within less than a decade of studies on the role of lncRNAs in AA, using experimental and bioinformatic approaches, scientists have obtained the data confirming the involvement of these molecules in metabolic pathways and pathogenetic mechanisms critical for the aneurysm development. Regardless of the location of pathological process (thoracic or abdominal aorta), AA was found to be associated with changes in the expression of various lncRNAs in the tissue of the affected vessels. The consistency of changes in the expression level of lncRNA, mRNA and microRNA in aortic tissues during AA development has been recordedand regulatory networks implicated in the AA pathogenesis in which lncRNAs act as competing endogenous RNAs (ceRNA networks) have been identified. It was found that the same lncRNA can be involved in different ceRNA networks and regulate different biochemical and cellular events; on the other hand, the same pathological process can be controlled by different lncRNAs. Despite some similarities in pathogenesis and overlapping of involved lncRNAs, the ceRNA networks described for abdominal and thoracic AA are different. Interactions between lncRNAs and other molecules, including those participating in epigenetic processes, have also been identified as potentially relevant to the AA pathogenesis. The expression levels of some lncRNAs were found to correlate with clinically significant aortic features and biochemical parameters. Identification of regulatory RNAs functionally significant in the aneurysm development is important for clarification of disease pathogenesis and will provide a basis for early diagnostics and development of new preventive and therapeutic drugs.

Metabolic Reprogramming and Potential Therapeutic Targets in Lymphoma.

Lymphoma is a heterogeneous group of diseases that often require their metabolism program to fulfill the demand of cell proliferation. Features of metabolism in lymphoma cells include high glucose uptake, deregulated expression of enzymes related to glycolysis, dual capacity for glycolytic and oxidative metabolism, elevated glutamine metabolism, and fatty acid synthesis. These aberrant metabolic changes lead to tumorigenesis, disease progression, and resistance to lymphoma chemotherapy. This metabolic reprogramming, including glucose, nucleic acid, fatty acid, and amino acid metabolism, is a dynamic process caused not only by genetic and epigenetic changes, but also by changes in the microenvironment affected by viral infections. Notably, some critical metabolic enzymes and metabolites may play vital roles in lymphomagenesis and progression. Recent studies have uncovered that metabolic pathways might have clinical impacts on the diagnosis, characterization, and treatment of lymphoma subtypes. However, determining the clinical relevance of biomarkers and therapeutic targets related to lymphoma metabolism is still challenging. In this review, we systematically summarize current studies on metabolism reprogramming in lymphoma, and we mainly focus on disorders of glucose, amino acids, and lipid metabolisms, as well as dysregulation of molecules in metabolic pathways, oncometabolites, and potential metabolic biomarkers. We then discuss strategies directly or indirectly for those potential therapeutic targets. Finally, we prospect the future directions of lymphoma treatment on metabolic reprogramming.

Consumption of a light meal affects serum concentrations of one-carbon metabolites and B-vitamins. A clinical intervention study.

The transfer of one-carbon units between molecules in metabolic pathways is essential for maintaining cellular homeostasis, but little is known about whether the circulating concentrations of metabolites involved in the one-carbon metabolism are affected by the prandial status. Epidemiological studies do not always consistently use fasting or non-fasting blood samples or may lack information on the prandial status of the study participants. Therefore, the main aim of the present study was to investigate the effects of a light breakfast on serum concentrations of selected metabolites and B-vitamins related to the one-carbon metabolism; i.e. the methionine-homocysteine cycle, the folate cycle, the choline oxidation pathway and the transsulfuration pathway. Sixty-three healthy adults (thirty-six women) with BMI ≥ 27 kg/m2 were included in the study. Blood was collected in the fasting state and 60 and 120 min after intake of a standardised breakfast consisting of white bread, margarine, white cheese, strawberry jam and orange juice (2218 kJ). The meal contained low amounts of choline, betaine, serine and vitamins B2, B3, B6, B9 and B12. Serum concentrations of total homocysteine, total cysteine, flavin mononucleotide, nicotinamide and pyridoxal 5'-phosphate were significantly decreased, and concentrations of choline, betaine, dimethylglycine, sarcosine, cystathionine and folate were significantly increased following breakfast intake (P < 0·05). Our findings demonstrate that the intake of a light breakfast with low nutrient content affected serum concentrations of several metabolites and B-vitamins related to the one-carbon metabolism.

Metabolic Enzymes in Sarcomagenesis: Progress Toward Biology and Therapy.

Cellular metabolism reprogramming is an emerging hallmark of cancer, which provides tumor cells with not only necessary energy but also crucial materials to support growth. Exploiting the unique features of cancer metabolism is promising in cancer therapies. The growing interest in this field has led to numerous inhibitors being developed against key molecules in metabolic pathways, though most of them are still in preclinical development. Potential targeted cancer cell metabolic pathways under investigation include glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), glutaminolysis, pentose phosphate pathway (PPP), lipid synthesis, amino acid and nucleotide metabolism. Sarcoma is a type of cancer that arises from transformed cells of mesenchymal origin, in contrast to carcinoma which originates from epithelial cells. Compared with carcinoma, progress towards harnessing the therapeutic potential of targeting sarcoma cell metabolism has been relatively slow. Recently however, with the discovery of cancer-specific mutations in metabolic enzymes such as isocitrate dehydrogenase (IDH) and succinate dehydrogenase (SDH) in certain sarcoma types, cancer cellular metabolism has been considered more as a source of new targets for treating sarcoma. In this article, we review metabolic enzymes currently tested for cancer therapies and describe the therapeutic potential of targeting IDH mutations and SDH deficiency in sarcomas.

Prediction of Interaction Between Enzymes and Small Molecules in Metabolic Pathways Through Integrating Multiple Classifiers

Information about interactions between enzymes and small molecules is important for understanding various metabolic bioprocesses. In this article we applied a majority voting system to predict the interactions between enzymes and small molecules in the metabolic pathways, by combining several classifiers including AdaBoost, Bagging and KNN together. The advantage of such a strategy is based on the principle that a predictor based majority voting systems usually provide more reliable results than any single classifier. The prediction accuracies thus obtained on a training dataset and an independent testing dataset were 82.8% and 84.8%, respectively. The prediction accuracy for the networking couples in the independent testing dataset was 75.5%, which is about 4% higher than that reported in a previous study. The web-server for the prediction method presented in this paper is available at http://chemdata.shu.edu.cn/small-enz.