TNF-alpha differentially modulates subunit levels of respiratory electron transport complexes of ER/PR plus ve/-ve breast cancer cells to regulate mitochondrial complex activity and tumorigenic potential

Background: Tumor necrosis factor-α (TNF-α) is an immunostimulatory cytokine that is consistently high in the breast tumor microenvironment (TME); however, its differential role in mitochondrial functions and cell survival in ER/PR +ve and ER/PR −ve breast cancer cells is not well understood. Methods: In the current study, we investigated TNF-α modulated mitochondrial proteome using high-resolution mass spectrometry and identified the differentially expressed proteins in two different breast cancer cell lines, ER/PR positive cell line; luminal, MCF-7 and ER/PR negative cell line; basal-like, MDA-MB-231 and explored its implication in regulating the tumorigenic potential of breast cancer cells. We also compared the activity of mitochondrial complexes, ATP, and ROS levels between MCF-7 and MDA-MB-231 in the presence of TNF-α. We used Tumor Immune Estimation Resource (TIMER) webserver to analyze the correlation between TNF-α and mitochondrial proteins in basal and luminal breast cancer patients. Kaplan-Meier method was used to analyze the correlation between mitochondrial protein expression and survival of breast cancer patients. Results: The proteome analysis revealed that TNF-α differentially altered the level of critical proteins of mitochondrial respiratory chain complexes both in MCF-7 and MDA-MB-231, which correlated with differential assembly and activity of mitochondrial ETC complexes. The inhibition of the glycolytic pathway in the presence of TNF-α showed that glycolysis is indispensable for the proliferation and clonogenic ability of MDA-MB-231 cells (ER/ PR −ve) as compared to MCF-7 cells (ER/PR +ve). The TIMER database showed a negative correlation between the expressions of TNF-α and key regulators of mitochondrial OXPHOS complexes in basal breast vs lobular carcinoma. Conversely, patient survival analysis showed an improved relapse-free survival with increased expression of identified proteins of ETC complexes and survival of the breast cancer patients. Conclusion: The evidence presented in our study convincingly demonstrates that TNF-α regulates the survival and proliferation of aggressive tumor cells by modulating the levels of critical assembly factors and subunits involved in mitochondrial respiratory chain supercomplexes organization and function. This favors the rewiring of mitochondrial metabolism towards anaplerosis to support the survival and proliferation of breast cancer cells. Collectively, the results strongly suggest that TNF-α differentially regulates metabolic adaptation in ER/PR +ve (MCF- 7) and ER/PR −ve (MDA-MB-231) cells by modulating the mitochondrial supercomplex assembly and activity

Relationship between Environmental Phthalate Exposure and the Intelligence of School-Age Children

BACKGROUND: Concern over phthalates has emerged because of their potential toxicity to humans. OBJECTIVE: We investigated the relationship between the urinary concentrations of phthalate metabolites and children`s intellectual functioning. METHODS: This study enrolled 667 children at nine elementary schools in five South Korean cities. A cross-sectional examination of urine phthalate concentrations was performed, and scores on neuro-psychological tests were obtained from both the children and their mothers. RESULTS: We measured mono-2-ethylhexyl phthalate (MEHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), both metabolites of di(2-ethylhexyl)phthalate (DEHP), and mono-n-butyl phthalate (MBP), a metabolite of dibutyl phthalate (DBP), in urine samples. The geometric mean (ln) concentrations of MEHP, MEOHP, and MBP were 21.3 mu g/L [geometric SD (GSD) = 2.2 mu g/L; range, 0.5-445.4], 18.0 mu g/L (GSD = 2.4; range, 0.07-291.1), and 48.9 mu g/L (GSD = 2.2; range, 2.1-1645.5), respectively. After adjusting for demographic and developmental covariates, the Full Scale IQ and Verbal IQ scores were negatively associated with DEHP metabolites but not with DBP metabolites. We also found a significant negative relationship between the urine concentrations of the metabolites of DEHP and DBP and children`s vocabulary subscores. After controlling for maternal IQ, a significant inverse relationship between DEHP metabolites and vocabulary subscale score remained. Among boys, we found a negative association between increasing MEHP phthalate concentrations and the sum of DEHP metabolite concentrations and Wechsler Intelligence Scale for Children vocabulary score; however, among girls, we found no significant association between these variables. CONCLUSION: Controlling for maternal IQ and other covariates, the results show an inverse relationship between phthalate metabolites and IQ scores; however, given the limitations in cross-sectional epidemiology, prospective studies are needed to fully explore these associations.This work was funded by the Eco-Technopia 21 project of Korea Institute of Environmental Science and Technology (091-081-059).Cho SC, 2010, J CHILD PSYCHOL PSYC, V51, P1050, DOI 10.1111/j.1469-7610.2010.02250.xKim BN, 2009, BIOL PSYCHIAT, V66, P958, DOI 10.1016/j.biopsych.2009.07.034Tanida T, 2009, TOXICOL LETT, V189, P40, DOI 10.1016/j.toxlet.2009.04.005Ghisari M, 2009, TOXICOL LETT, V189, P67, DOI 10.1016/j.toxlet.2009.05.004Barnett JH, 2009, AM J PSYCHIAT, V166, P909, DOI 10.1176/appi.ajp.2009.08081251Kim Y, 2009, NEUROTOXICOLOGY, V30, P564, DOI 10.1016/j.neuro.2009.03.012Engel SM, 2009, NEUROTOXICOLOGY, V30, P522, DOI 10.1016/j.neuro.2009.04.001Kamrin MA, 2009, J TOXICOL ENV HEAL B, V12, P157, DOI 10.1080/10937400902729226Brown JS, 2009, SCHIZOPHRENIA BULL, V35, P256, DOI 10.1093/schbul/sbm147Bellinger DC, 2008, NEUROTOXICOLOGY, V29, P828, DOI 10.1016/j.neuro.2008.04.005Wolff MS, 2008, ENVIRON HEALTH PERSP, V116, P1092, DOI 10.1289/ehp.11007van Neerven S, 2008, PROG NEUROBIOL, V85, P433, DOI 10.1016/j.pneurobio.2008.04.006Hatch EE, 2008, ENVIRON HEALTH-GLOB, V7, DOI 10.1186/1476-069X-7-27Zevalkink J, 2008, J GENET PSYCHOL, V169, P72Kolarik B, 2008, ENVIRON HEALTH PERSP, V116, P98, DOI 10.1289/ehp.10498SATHYANARAYANA S, 2008, CURR PROBL PEDIAT AD, V38, P34KHO YL, 2008, J ENV HLTH SCI, V34, P271Huang PC, 2007, HUM REPROD, V22, P2715, DOI 10.1093/humrep/dem205Janjua NR, 2007, ENVIRON SCI TECHNOL, V41, P5564, DOI 10.1021/es0628755Meeker JD, 2007, ENVIRON HEALTH PERSP, V115, P1029, DOI 10.1289/ehp.9852Fromme H, 2007, INT J HYG ENVIR HEAL, V210, P21, DOI 10.1016/j.ijheh.2006.09.005Xu Y, 2007, ARCH TOXICOL, V81, P57, DOI 10.1007/s00204-006-0143-8Pereira C, 2007, ACTA HISTOCHEM, V109, P29, DOI 10.1016/j.acthis.2006.09.008Hauser R, 2006, EPIDEMIOLOGY, V17, P682, DOI 10.1097/01.ede.0000235996.89953.d7Zhu DF, 2006, BRAIN, V129, P2923, DOI 10.1093/brain/awl215Andrade AJM, 2006, TOXICOLOGY, V227, P185, DOI 10.1016/j.tox.2006.07.022Lottrup G, 2006, INT J ANDROL, V29, P172, DOI 10.1111/j.1365-2605.2005.00642.xBreous E, 2005, MOL CELL ENDOCRINOL, V244, P75, DOI 10.1016/j.mce.2005.06.009Wenzel A, 2005, MOL CELL ENDOCRINOL, V244, P63, DOI 10.1016/j.mce.2005.02.008Kato K, 2005, ANAL CHEM, V77, P2985, DOI 10.1021/ac0481248Tanaka T, 2005, FOOD CHEM TOXICOL, V43, P581, DOI 10.1016/j.fct.2005.01.001Duty SM, 2005, HUM REPROD, V20, P604, DOI 10.1093/humrep/deh656Kota BP, 2005, PHARMACOL RES, V51, P85, DOI 10.1016/j.phrs.2004.07.012Hays T, 2005, CARCINOGENESIS, V26, P219, DOI 10.1093/carcin/bgh285Hauser R, 2004, ENVIRON HEALTH PERSP, V112, P1734, DOI 10.1289/ehp.7212Bornehag CG, 2004, ENVIRON HEALTH PERSP, V112, P1393, DOI 10.1289/ehp.7187Ishido M, 2004, J NEUROCHEM, V91, P69, DOI 10.1111/j.1471-4159.2004.02696.xMink PJ, 2004, EPIDEMIOLOGY, V15, P385, DOI 10.1097/01.ede.0000128402.86336.7eBellinger DC, 2004, EPIDEMIOLOGY, V15, P383, DOI 10.1097/01.ede.0000129525.15064.a4Shea KM, 2003, PEDIATRICS, V111, P1467Tanaka T, 2002, FOOD CHEM TOXICOL, V40, P1499, DOI 10.1016/S0278-6915(02)00073-XHoppin JA, 2002, ENVIRON HEALTH PERSP, V110, P515SATTLER JM, 2001, ASSESSMENT CHILDRENRice D, 2000, ENVIRON HEALTH PERSP, V108, P511Bellinger DC, 2000, NEUROTOXICOL TERATOL, V22, P133LIM YR, 2000, KOR J CLIN PSYCHOL, V19, P563Braissant O, 1998, ENDOCRINOLOGY, V139, P2748Peters JM, 1997, CARCINOGENESIS, V18, P2029Baldini IM, 1997, PROG NEURO-PSYCHOPH, V21, P925Roberts RA, 1997, FUND APPL TOXICOL, V38, P107PARK KS, 1996, DEV KEDI WISC INDIVIMONZANI F, 1993, CLIN INVESTIGATOR, V71, P367SILVERSTEIN AB, 1990, J CLIN PSYCHOL, V46, P333HINTON RH, 1986, ENVIRON HEALTH PERSP, V70, P195KIM MK, 1986, SEOUL J PSYCHIAT, V11, P194KAUFMAN AS, 1976, CONTEMP EDUC PSYCHOL, V1, P1801

Efficient and accurate greedy search methods for mining functional modules in protein interaction networks

<p>Abstract</p> <p>Background</p> <p>Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures.</p> <p>Methods</p> <p>In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules.</p> <p>Results</p> <p>The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms.</p> <p>Conclusions</p> <p>Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.</p

Deep-Inelastic Inclusive ep Scattering at Low x and a Determination of alpha_s

A precise measurement of the inclusive deep-inelastic e^+p scattering cross section is reported in the kinematic range 1.5<= Q^2 <=150 GeV^2 and 3*10^(-5)<= x <=0.2. The data were recorded with the H1 detector at HERA in 1996 and 1997, and correspond to an integrated luminosity of 20 pb^(-1). The double differential cross section, from which the proton structure function F_2(x,Q^2) and the longitudinal structure function F_L(x,Q^2) are extracted, is measured with typically 1% statistical and 3% systematic uncertainties. The measured partial derivative (dF_2(x,Q^2)/dln Q^2)_x is observed to rise continuously towards small x for fixed Q^2. The cross section data are combined with published H1 measurements at high Q^2 for a next-to-leading order DGLAP QCD analysis.The H1 data determine the gluon momentum distribution in the range 3*10^(-4)<= x <=0.1 to within an experimental accuracy of about 3% for Q^2 =20 GeV^2. A fit of the H1 measurements and the mu p data of the BCDMS collaboration allows the strong coupling constant alpha_s and the gluon distribution to be simultaneously determined. A value of alpha _s(M_Z^2)=0.1150+-0.0017 (exp) +0.0009-0.0005 (model) is obtained in NLO, with an additional theoretical uncertainty of about +-0.005, mainly due to the uncertainty of the renormalisation scale.Comment: 68 pages, 24 figures and 18 table

SDF1 in the dorsal corticospinal tract promotes CXCR4+ cell migration after spinal cord injury

<p>Abstract</p> <p>Background</p> <p>Stromal cell-derived factor-1 (SDF1) and its major signaling receptor, CXCR4, were initially described in the immune system; however, they are also expressed in the nervous system, including the spinal cord. After spinal cord injury, the blood brain barrier is compromised, opening the way for chemokine signaling between these two systems. These experiments clarified prior contradictory findings on normal expression of SDF1 and CXCR4 as well as examined the resulting spinal cord responses resulting from this signaling.</p> <p>Methods</p> <p>These experiments examined the expression and function of SDF1 and CXCR4 in the normal and injured adult mouse spinal cord primarily using CXCR4-EGFP and SDF1-EGFP transgenic reporter mice.</p> <p>Results</p> <p>In the uninjured spinal cord, SDF1 was expressed in the dorsal corticospinal tract (dCST) as well as the meninges, whereas CXCR4 was found only in ependymal cells surrounding the central canal. After spinal cord injury (SCI), the pattern of SDF1 expression did not change rostral to the lesion but it disappeared from the degenerating dCST caudally. By contrast, CXCR4 expression changed dramatically after SCI. In addition to the CXCR4+ cells in the ependymal layer, numerous CXCR4+ cells appeared in the peripheral white matter and in the dorsal white matter localized between the dorsal corticospinal tract and the gray matter rostral to the lesion site. The non-ependymal CXCR4+ cells were found to be NG2+ and CD11b+ macrophages that presumably infiltrated through the broken blood-brain barrier. One population of macrophages appeared to be migrating towards the dCST that contains SDF1 rostral to the injury but not towards the caudal dCST in which SDF1 is no longer present. A second population of the CXCR4+ macrophages was present near the SDF1-expressing meningeal cells.</p> <p>Conclusions</p> <p>These observations suggest that attraction of CXCR4+ macrophages is part of a programmed response to injury and that modulation of the SDF1 signaling system may be important for regulating the inflammatory response after SCI.</p

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Aldo-keto reductases are biomarkers of NRF2 activity and are co-ordinately overexpressed in non-small cell lung cancer

BACKGROUND: Although the nuclear factor-erythroid 2-related factor 2 (NRF2) pathway is one of the most frequently dysregulated in cancer, it is not clear whether mutational status is a good predictor of NRF2 activity. Here we utilise four members of the aldo-keto reductase (AKR) superfamily as biomarkers to address this question. METHODS: Twenty-three cell lines of diverse origin and NRF2-pathway mutational status were used to determine the relationship between AKR expression and NRF2 activity. AKR expression was evaluated in lung cancer biopsies and Cancer Genome Atlas (TCGA) and Oncomine data sets. RESULTS: AKRs were expressed at a high basal level in cell lines carrying mutations in the NRF2 pathway. In non-mutant cell lines, co-ordinate induction of AKRs was consistently observed following activation of NRF2. Immunohistochemical analysis of lung tumour biopsies and interrogation of TCGA data revealed that AKRs are enriched in both squamous cell carcinomas (SCCs) and adenocarcinomas that contain somatic alterations in the NRF2 pathway but, in the case of SCC, AKRs were also enriched in most other tumours. CONCLUSIONS: An AKR biomarker panel can be used to determine NRF2 status in tumours. Hyperactivation of the NRF2 pathway is far more prevalent in lung SCC than previously predicted by genomic analyses

Dimethyl Sulfoxide Promotes the Multiple Functions of the Tumor Suppressor HLJ1 through Activator Protein-1 Activation in NSCLC Cells

Background: Dimethyl sulfoxide (DMSO) is an amphipathic molecule that displays a diversity of antitumor activities. Previous studies have demonstrated that DMSO can modulate AP-1 activity and lead to cell cycle arrest at the G1 phase. HLJ1 is a newly identified tumor and invasion suppressor that inhibits tumorigenesis and cancer metastasis. Its transcriptional activity is regulated by the transcription factor AP-1. However, the effects of DMSO on HLJ1 are still unknown. In the present study, we investigate the antitumor effects of DMSO through HLJ1 induction and demonstrate the mechanisms involved. Methods and Findings: Low-HLJ1-expressing highly invasive CL1–5 lung adenocarcinoma cells were treated with various concentrations of DMSO. We found that DMSO can significantly inhibit cancer cell invasion, migration, proliferation, and colony formation capabilities through upregulation of HLJ1 in a concentration-dependent manner, whereas ethanol has no effect. In addition, the HLJ1 promoter and enhancer reporter assay revealed that DMSO transcriptionally upregulates HLJ1 expression through an AP-1 site within the HLJ1 enhancer. The AP-1 subfamily members JunD and JunB were significantly upregulated by DMSO in a concentration-dependent manner. Furthermore, pretreatment with DMSO led to a significant increase in the percentage of UV-induced apoptotic cells. Conclusions: Our results suggest that DMSO may be an important stimulator of the tumor suppressor protein HLJ1 throug

Inhibitory effect of 4-O-methylhonokiol on lipopolysaccharide-induced neuroinflammation, amyloidogenesis and memory impairment via inhibition of nuclear factor-kappaB in vitro and in vivo models

<p>Abstract</p> <p>Background</p> <p>Neuroinflammation is important in the pathogenesis and progression of Alzheimer disease (AD). Previously, we demonstrated that lipopolysaccharide (LPS)-induced neuroinflammation caused memory impairments. In the present study, we investigated the possible preventive effects of 4-<it>O</it>-methylhonokiol, a constituent of <it>Magnolia officinalis</it>, on memory deficiency caused by LPS, along with the underlying mechanisms.</p> <p>Methods</p> <p>We investigated whether 4-<it>O</it>-methylhonokiol (0.5 and 1 mg/kg in 0.05% ethanol) prevents memory dysfunction and amyloidogenesis on AD model mice by intraperitoneal LPS (250 μg/kg daily 7 times) injection. In addition, LPS-treated cultured astrocytes and microglial BV-2 cells were investigated for anti-neuroinflammatory and anti-amyloidogenic effect of 4-<it>O</it>-methylhonkiol (0.5, 1 and 2 μM).</p> <p>Results</p> <p>Oral administration of 4-<it>O</it>-methylhonokiol ameliorated LPS-induced memory impairment in a dose-dependent manner. In addition, 4-<it>O</it>-methylhonokiol prevented the LPS-induced expression of inflammatory proteins; inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) as well as activation of astrocytes (expression of glial fibrillary acidic protein; GFAP) in the brain. In <it>in vitro </it>study, we also found that 4-<it>O</it>-methylhonokiol suppressed the expression of iNOS and COX-2 as well as the production of reactive oxygen species, nitric oxide, prostaglandin E₂, tumor necrosis factor-α, and interleukin-1β in the LPS-stimulated cultured astrocytes. 4-<it>O</it>-methylhonokiol also inhibited transcriptional and DNA binding activity of NF-κB via inhibition of IκB degradation as well as p50 and p65 translocation into nucleus of the brain and cultured astrocytes. Consistent with the inhibitory effect on neuroinflammation, 4-<it>O</it>-methylhonokiol inhibited LPS-induced Aβ_1-42generation, β- and γ-secretase activities, and expression of amyloid precursor protein (APP), BACE1 and C99 as well as activation of astrocytes and neuronal cell death in the brain, in cultured astrocytes and in microglial BV-2 cells.</p> <p>Conclusion</p> <p>These results suggest that 4-<it>O</it>-methylhonokiol inhibits LPS-induced amyloidogenesis via anti-inflammatory mechanisms. Thus, 4-<it>O</it>-methylhonokiol can be a useful agent against neuroinflammation-associated development or the progression of AD.</p