ORP4L Extracts and Presents PIP2 from Plasma Membrane for PLC beta 3 Catalysis : Targeting It Eradicates Leukemia Stem Cells

Leukemia stem cells (LSCs) are a rare subpopulation of abnormal hematopoietic stem cells (HSCs) that propagates leukemia and are responsible for the high frequency of relapse in therapies. Detailed insights into LSCs' survival will facilitate the identification of targets for therapeutic approaches. Here, we develop an inhibitor, LYZ-81, which targets ORP4L with high affinity and specificity and selectively eradicates LCSs in vitro and in vivo. ORP4L is expressed in LSCs but not in normal HSCs and is essential for LSC bioenergetics and survival. It extracts PIP2 from the plasma membrane and presents it to PLC beta 3, enabling IP3 generation and subsequentCa(2+)-dependent bioenergetics. LYZ-81 binds ORP4L competitively with PIP2 and blocks PIP2 hydrolysis, resulting in defective Ca2+ signaling. The results provide evidence that LSCs can be eradicated through the inhibition of ORP4L by LYZ-81, which may serve as a starting point of drug development for the elimination of LSCs to eventually cure leukemia.Peer reviewe

Lipidomics Analysis Reveals Efficient Storage of Hepatic Triacylglycerides Enriched in Unsaturated Fatty Acids after One Bout of Exercise in Mice

Background: Endurance exercise induces lipolysis, increases circulating concentrations of free fatty acids (FFA) and the uptake and oxidation of fatty acids in the working muscle. Less is known about the regulation of lipid metabolism in the liver during and post-exercise

Plasma and Liver Lipidomics Response to an Intervention of Rimonabant in ApoE*3Leiden.CETP Transgenic Mice

Background: Lipids are known to play crucial roles in the development of life-style related risk factors such as obesity, dyslipoproteinemia, hypertension and diabetes. The first selective cannabinoid-1 receptor blocker rimonabant, an anorectic anti-obesity drug, was frequently used in conjunction with diet and exercise for patients with a body mass index greater than 30 kg/m2 with associated risk factors such as type II diabetes and dyslipidaemia in the past. Less is known about the impact of this drug on the regulation of lipid metabolism in plasma and liver in the early stage of obesity. Methodology/Principal Findings: We designed a four-week parallel controlled intervention on apolipoprotein E3 Leiden cholesteryl ester transfer protein (ApoE&z.ast;3Leiden.CETP) transgenic mice with mild overweight and hypercholesterolemia. A liquid chromatography-linear ion trap-Fourier transform ion cyclotron resonance-mass spectrometric approach was employed to investigate plasma and liver lipid responses to the rimonabant intervention. Rimonabant was found to induce a significant body weight loss (9.4%, p<0.05) and a significant plasma total cholesterol reduction (24%, p<0.05). Six plasma and three liver lipids in ApoE&z.ast;3Leiden.CETP transgenic mice were detected to most significantly respond to rimonabant treatment. Distinct lipid patterns between the mice were observed for both plasma and liver samples in rimonabant treatment vs. non-treated controls. This study successfully applied, for the first time, systems biology based lipidomics approaches to evaluate treatment effects of rimonabant in the early stage of obesity. Conclusion: The effects of rimonabant on lipid metabolism and body weight reduction in the early stage obesity were shown to be moderate in ApoE&z.ast;3Leiden.CETP mice on high-fat diet. © 2011 Hu et al

Lipidomics Reveals Multiple Pathway Effects of a Multi-Components Preparation on Lipid Biochemistry in ApoE*3Leiden.CETP Mice

Background: Causes and consequences of the complex changes in lipids occurring in the metabolic syndrome are only partly understood. Several interconnected processes are deteriorating, which implies that multi-target approaches might be more successful than strategies based on a limited number of surrogate markers. Preparations from Chinese Medicine (CM) systems have been handed down with documented clinical features similar as metabolic syndrome, which might help developing new intervention for metabolic syndrome. The progress in systems biology and specific animal models created possibilities to assess the effects of such preparations. Here we report the plasma and liver lipidomics results of the intervention effects of a preparation SUB885C in apolipoprotein E3 Leiden cholesteryl ester transfer protein (ApoE*3Leiden.CETP) mice. SUB885C was developed according to the principles of CM for treatment of metabolic syndrome. The cannabinoid receptor type 1 blocker rimonabant was included as a general control for the evaluation of weight and metabolic responses. Methodology/Principal Findings: ApoE*3Leiden.CETP mice with mild hypercholesterolemia were divided into SUB885C-, rimonabant- and non-treated control groups. SUB885C caused no weight loss, but significantly reduced plasma cholesterol (-49%, p <0.001), CETP levels (-31%,

Study on the Nonlinear Conductivity of SiC/ZnO/Epoxy Resin Micro- and Nanocomposite Materials

To investigate the inhomogeneous distribution of electric fields in insulating equipment and components, five nonlinear-conductance composite materials based on epoxy resin (EP) (nano-SiC/EP, nano-ZnO/EP, micro-ZnO/EP, nano-SiC/ZnO/EP, and nano-micro-SiC/ZnO/EP), were prepared using nano-SiC, nano-ZnO, and micro-ZnO particles as fillers. The mass fractions of the inorganic fillers were 1, 3, and 5 wt%, respectively. The direct current (DC) voltage characteristics of the composites showed that the electrical conductivities and nonlinear coefficients of the composites utilizing single-filler types increased with increasing inorganic filler content. Under the same conditions, the conductivity and nonlinear coefficient of SiC/EP were both larger than those of the nano-ZnO/EP and micro-ZnO/EP. However, the nonlinear coefficient of the composites was significantly affected by the simultaneous addition of the two inorganic fillers, micro-ZnO and nano-SiC. When the content ratio of micro-ZnO to nano-SiC was 2:3, the nonlinear coefficient of the composite reached a maximum value of 3.506, significantly higher than those of the other samples. Compared with the nano-SiC/EP, micro-ZnO/EP and nano-ZnO/EP composites with 5 wt% inorganic filler, the nonlinear coefficient of the two-filler composite was greater by a factor of 0.82, 2.48, and 5.01, respectively

Serum lipid profiling of patients with chronic hepatitis B, cirrhosis, and hepatocellular carcinoma by ultra fast LC/IT-TOF MS

In this study, an ultra fast LC/IT-TOF MS (UFLC/IT-TOF MS)-based serum lipidomics method was employed to characterize the serum lipid profile of patients with chronic hepatitis B, cirrhosis, and hepatocellular carcinoma (HCC). After data collection and processing, 96 lipids including lysophosphatidylcholines, phosphatidylcholines, sphingomyelins, triacylglycerides, and cholesterol esters were identified and used for subsequent data analysis. Partial least squares-discriminant analysis revealed that patients with liver diseases had distinctly different serum lipid profile from that of healthy controls; while cirrhosis and HCC patients had a similar serum lipid profile, but different from that of hepatitis patients. The ANOVA analysis found 75 of the 96 identified lipids to be abnormally regulated, among which most of these lipids were downregulated in cirrhosis and HCC patients compared with those of healthy controls and hepatitis patients, while hepatitis patients induced several lipids downregulated and others upregulated compared with those of healthy controls, indicating the aberrant lipid metabolism in patients with liver diseases. This work demonstrated the utility of UFLC/IT-TOF MS-based serum lipidomics as a powerful tool to investigate the lipid metabolism of liver diseases

A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks

Analyzing omics data from a network-based perspective can facilitate biomarker discovery. To improve disease diagnosis and identify prospective information indicating the onset of complex disease, a computational method for identifying potential biomarkers based on differential sub-networks (PBDSN) is developed. In PB-DSN, Pearson correlation coefficient (PCC) is used to measure the relationship between feature ratios and to infer potential networks. A differential sub-network is extracted to identify crucial information for discriminating different groups and indicating the emergence of complex diseases. Subsequently, PB-DSN defines potential biomarkers based on the topological analysis of these differential sub-networks. In this study, PB-DSN is applied to handle a static genomics dataset of small, round blue cell tumors and a time-series metabolomics dataset of hepatocellular carcinoma. PB-DSN is compared with support vector machine-recursive feature elimination, multivariate empirical Bayes statistics, analyzing time-series data based on dynamic networks, molecular networks based on PCC, PinnacleZ, graph-based iterative group analysis, KeyPathwayMiner and BioNet. The better performance of PB-DSN not only demonstrates its effectiveness for the identification of discriminative features that facilitate disease classification, but also shows its potential for the identification of warning signals

Breast cancer primary tumor ER expression pattern predicts its expression concordance in matched synchronous lymph node metastases

Abstract Background Estrogen receptor (ER) expression is important for treatment selection and prognostication of breast cancer patients. Although the metastases are the main targets of endocrine therapy, ER status is often based on the primary tumor. However, ER expression in breast cancer primary lesion may not match with its synchronous metastatic lesions in some cases. In this study, we analyzed ER expression concordance between breast cancer primary tumor and metastatic lesions. Methods Paraffin blocks of 100 primary breast invasive ductal carcinoma cases with axillary lymph node metastases were collected. Five tissue cores were punched out from individual primary breast cancer, and one tissue core from each lymph node metastases to assemble tissue microarrays for ER staining. Samples were then scored as 0, 1+, 2+, and 3+ according to the number and intensity of ER stained tumor cells. Results For cases with ER 3+ (strong expression) in all cores of primary lesions (n = 38), ER expression in metastatic lymph node was found in 94.7% of the patients. 91.0% of the metastatic lymph nodes were ER positive, and 84.3% of them to be 3+. Among the 46 cases of ER negative expression in all cores of primary lesions, 39 of them had all the metastatic nodes being ER negative, and ER negative nodes were seen in 95.7% of the metastases. As for 16 cases of ER inconsistent expression in primary lesions, 4 cases showed negative ER expression in all metastatic nodes, 2 cases displayed diffuse consistent ER 3+ expression, and 10 cases displayed variant ER expression. Conclusions The findings suggest that ER expression concordance between breast cancer primary lesion and its matched metastatic lesions could be estimated by primary tumor ER expression pattern

Large-scaled human serum sphingolipid profiling by using reversed-phase liquid chromatography coupled with dynamic multiple reaction monitoring of mass spectrometry: Method development and application in hepatocellular carcinoma

Sphingolipids are a family of bioactive molecules with high structural diversity and complexity. They not only serve as integral components of cellular membrane, but also play pivotal roles in signaling and other cellular events. It is desirable for the development of sensitive, robust and structural-specific analytical approaches enabling rapid determination of as many sphingolipid species as possible. Herein we present an analytical method for large-scaled profiling of sphigolipids in human serum, which consisted of an improved extraction protocol using tert-butyl methyl ether combined with mild alkaline hydrolysis, and an ultra high performance reversed-phase liquid chromatography-dynamic multiple reaction monitoring-mass spectrometric (RPLC-dynamic MRM-MS) method. In total 84 endogenous sphingolipid species covering six subcategories (i.e. free sphingoid base, dihydroceramide, ceramide, hexosylceramide, lactosylceramide, and sphingomyelin), were separated and quantified in a single run within 10 min. A broad linear range over 2.5-4 orders of magnitude (r(2)>0.99), a limit of detection of 0.01-0.17 pmol/mL, and a limit of quantitation of 0.02-0.42 pmol/mL were obtained for each subcategory. Average recovery of each subcategory was within 85.6-95.6%. Median values of coefficient of variation (CV) of all detected 84 sphingolipids were 3.9% and 6.8% for intraday and interday precision, respectively. This method was exemplarily applied in a study regarding dysregulated sphingolipid homeostasis in hepatocellular carcinoma. The establishment of this method provides a useful tool for serum-based high throughput screening of sphingolipid biomarkers and mechanism investigation of sphingolipid metabolic regulation in human disease. (C) 2013 Elsevier B.V. All rights reserved