Die Bedeutung reaktiver Sauerstoffspezies für die Lipotoxizität in insulinproduzierenden Zellen

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Role of thioredoxin reductase 1 and thioredoxin interacting protein in prognosis of breast cancer

Introduction: The purpose of this work was to study the prognostic influence in breast cancer of thioredoxin reductase 1 (TXNRD1) and thioredoxin interacting protein (TXNIP), key players in oxidative stress control that are currently evaluated as possible therapeutic targets. Methods: Analysis of the association of TXNRD1 and TXNIP RNA expression with the metastasis-free interval (MFI) was performed in 788 patients with node-negative breast cancer, consisting of three individual cohorts (Mainz, Rotterdam and Transbig). Correlation with metagenes and conventional clinical parameters (age, pT stage, grading, hormone and ERBB2 status) was explored. MCF-7 cells with a doxycycline-inducible expression of an oncogenic ERBB2 were used to investigate the influence of ERBB2 on TXNRD1 and TXNIP transcription. Results: TXNRD1 was associated with worse MFI in the combined cohort (hazard ratio = 1.955; P < 0.001) as well as in all three individual cohorts. In contrast, TXNIP was associated with better prognosis (hazard ratio = 0.642; P < 0.001) and similar results were obtained in all three subcohorts. Interestingly, patients with ERBB2-status-positive tumors expressed higher levels of TXNRD1. Induction of ERBB2 in MCF-7 cells caused not only an immediate increase in TXNRD1 but also a strong decrease in TXNIP. A subsequent upregulation of TXNIP as cells undergo senescence was accompanied by a strong increase in levels of reactive oxygen species. Conclusions: TXNRD1 and TXNIP are associated with prognosis in breast cancer, and ERBB2 seems to be one of the factors shifting balances of both factors of the redox control system in a prognostic unfavorable manner

Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes

<p>Abstract</p> <p>Background</p> <p>A major goal of the analysis of high-dimensional RNA expression data from tumor tissue is to identify prognostic signatures for discriminating patient subgroups. For this purpose genome-wide identification of bimodally expressed genes from gene array data is relevant because distinguishability of high and low expression groups is easier compared to genes with unimodal expression distributions.</p> <p>Recently, several methods for the identification of genes with bimodal distributions have been introduced. A straightforward approach is to cluster the expression values and score the distance between the two distributions. Other scores directly measure properties of the distribution. The kurtosis, e.g., measures divergence from a normal distribution. An alternative is the outlier-sum statistic that identifies genes with extremely high or low expression values in a subset of the samples.</p> <p>Results</p> <p>We compare and discuss scores for bimodality for expression data. For the genome-wide identification of bimodal genes we apply all scores to expression data from 194 patients with node-negative breast cancer. Further, we present the first comprehensive genome-wide evaluation of the prognostic relevance of bimodal genes. We first rank genes according to bimodality scores and define two patient subgroups based on expression values. Then we assess the prognostic significance of the top ranking bimodal genes by comparing the survival functions of the two patient subgroups. We also evaluate the global association between the bimodal shape of expression distributions and survival times with an enrichment type analysis.</p> <p>Various cluster-based methods lead to a significant overrepresentation of prognostic genes. A striking result is obtained with the outlier-sum statistic (<it>p </it>< 10^-12). Many genes with heavy tails generate subgroups of patients with different prognosis.</p> <p>Conclusions</p> <p>Genes with high bimodality scores are promising candidates for defining prognostic patient subgroups from expression data. We discuss advantages and disadvantages of the different scores for prognostic purposes. The outlier-sum statistic may be particularly valuable for the identification of genes to be included in prognostic signatures. Among the genes identified as bimodal in the breast cancer data set several have not yet previously been recognized to be prognostic and bimodally expressed in breast cancer.</p

Antagonism Between Saturated and Unsaturated Fatty Acids in ROS Mediated Lipotoxicity in Rat Insulin-Producing Cells

Background/Aims: Elevated levels of non-esterified fatty acids (NEFAs) are under suspicion to mediate β-cell dysfunction and β-cell loss in type 2 diabetes, a phenomenon known as lipotoxicity. Whereas saturated fatty acids show a strong cytotoxic effect upon insulin-producing cells, unsaturated fatty acids are not toxic and can even prevent toxicity. Experimental evidence suggests that oxidative stress mediates lipotoxicity and there is evidence that the subcellular site of ROS formation is the peroxisome. However, the interaction between unsaturated and saturated NEFAs in this process is unclear. Methods: Toxicity of rat insulin-producing cells after NEFA incubation was measured by MTT and caspase assays. NEFA induced H2O2 formation was quantified by organelle specific expression of the H2O2 specific fluorescence sensor protein HyPer. Results: The saturated NEFA palmitic acid had a significant toxic effect on the viability of rat insulin-producing cells. Unsaturated NEFAs with carbon chain lengths >14 showed, irrespective of the number of double bonds, a pronounced protection against palmitic acid induced toxicity. Palmitic acid induced H2O2 formation in the peroxisomes of insulin-producing cells. Oleic acid incubation led to lipid droplet formation, but in contrast to palmitic acid induced neither an ER stress response nor peroxisomal H2O2 generation. Furthermore, oleic acid prevented palmitic acid induced H2O2 production in the peroxisomes. Conclusion: Thus unsaturated NEFAs prevent deleterious hydrogen peroxide generation during peroxisomal β-oxidation of long-chain saturated NEFAs in rat insulin-producing cells

A Novel and Cross-Species Active Mammalian INDY (NaCT) Inhibitor Ameliorates Hepatic Steatosis in Mice with Diet-Induced Obesity

Mammalian INDY (mINDY, NaCT, gene symbol SLC13A5) is a potential target for the treatment of metabolically associated fatty liver disease (MAFLD). This study evaluated the effects of a selective, cross-species active, non-competitive, non-substrate-like inhibitor of NaCT. First, the small molecule inhibitor ETG-5773 was evaluated for citrate and succinate uptake and fatty acid synthesis in cell lines expressing both human NaCT and mouse Nact. Once its suitability was established, the inhibitor was evaluated in a diet-induced obesity (DIO) mouse model. DIO mice treated with 15 mg/kg compound ETG-5773 twice daily for 28 days had reduced body weight, fasting blood glucose, and insulin, and improved glucose tolerance. Liver triglycerides were significantly reduced, and body composition was improved by reducing fat mass, supported by a significant reduction in the expression of genes for lipogenesis such as SREBF1 and SCD1. Most of these effects were also evident after a seven-day treatment with the same dose. Further mechanistic investigation in the seven-day study showed increased plasma β-hydroxybutyrate and activated hepatic adenosine monophosphate-activated protein kinase (AMPK), reflecting findings from Indy (-/-) knockout mice. These results suggest that the inhibitor ETG-5773 blocked citrate uptake mediated by mouse and human NaCT to reduce liver steatosis and body fat and improve glucose regulation, proving the concept of NaCT inhibition as a future liver treatment for MAFLD