214 research outputs found

    Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes

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    Background: The heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level.Methods: The study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data.Results: Our result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity.Conclusions: Three naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs

    Copynumber: Efficient algorithms for single- and multi-track copy number segmentation.

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    BACKGROUND: Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number. RESULTS: A comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented. CONCLUSIONS: The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    Effect of simulated dawn on quality of sleep – a community-based trial

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    BACKGROUND: Morning light exposure administered as simulated dawn looks a promising method to treat Seasonal Affective Disorder, but it may moreover help with resetting the inaccurate organisation of body clock functions relative to sleep occurring in winter among people in general. Disturbances in sleep patterns are common and may compromise wellbeing even in the short term. Our hypothesis was that simulated dawn could improve the subjective quality of sleep during winter. METHODS: A community-based trial with 100 volunteer subjects provided with dawn simulators. Study period lasted for eight weeks, and subjects used the dawn simulators for two weeks at a time, each subject acting as his own control (ABAB-design). Main outcome measure was subjective quality of sleep recorded each morning with Groningen Sleep Quality Scale. RESULTS: 77 subjects completed the trial. Quality of sleep improved while subjects were using dawn simulator-devices (p = 0.001). The treatment became beneficial after six days' use of dawn simulator, but the effect did not last after the use was ceased. CONCLUSION: Dawn simulation may help to improve the subjective quality of sleep, but the benefits are modest. Further research is needed to verify these findings and to elucidate the mechanism by which dawn simulation acts on the sleep-wake pattern

    LICAVAL: combination therapy in acute and maintenance treatment of bipolar disorder

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    <p>Abstract</p> <p>Background</p> <p>The challenge of Bipolar Disorder (BD) treatment is due to the complexity of the disease. Current guidelines represent an effort to help clinicians in their everyday practice but still have limitations, specially concerning to long term treatment. LICAVAL (e<it>fficacy and tolerability of the combination of <b>LI</b>thium and <b>CA</b>rbamazepine compared to lithium and <b>VAL</b>proic acid in the treatment of young bipolar patients</it>) study aim to evaluate acute and maintenance phase of BD treatment with two combined drugs.</p> <p>Methods</p> <p>LICAVAL is a single site, parallel group, randomized, outcome assessor blinded trial. BD I patients according to the DSM-IV-TR, in depressive, manic,/hypomanic or mixed episode, aged 18 to 35 years are eligible. After the diagnostic assessments, the patients are allocated for one of the groups of treatment (lithium + valproic acid or lithium + carbamazepine). Patients will be followed up for 8 weeks in phase I (acute treatment), 6 months in phase II (continuation treatment) and 12 months in phase III (maintenance treatment). Outcome assessors are blind to the treatment. The main outcome is the evaluation of changes in mean scores on CGI-BP-M between baseline and endpoint at the end of each phase of the study.</p> <p>Results</p> <p>LICAVAL is currently in progress, with patients in phase I, II or III. It will extended until august 2012.</p> <p>Conclusions</p> <p>Trials comparing specific treatments efficacy in BD (head to head) can show relevant information in clinical practice. Long term treatment is an issue of great important and should be evaluated carefully in more studies as long as BD is a chronic disease.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Identifier: NCT00976794</p

    A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer

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    Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p <0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PUS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER disease. None of the expression-based predictors were prognostic in the ER subset. We found that a model including CAM and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAL Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAM as an independent predictor of survival in both ER+ and ER breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer. (C) 2014 The Authors. Published by Elsevier B.V. on behalf of Federation of European Biochemical Societies. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).Publisher PDFPeer reviewe

    DNA Copy Number Changes in Human Malignant Fibrous Histiocytomas by Array Comparative Genomic Hybridisation

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    BACKGROUND: Malignant fibrous histiocytomas (MFHs), or undifferentiated pleomorphic sarcomas, are in general high-grade tumours with extensive chromosomal aberrations. In order to identify recurrent chromosomal regions of gain and loss, as well as novel gene targets of potential importance for MFH development and/or progression, we have analysed DNA copy number changes in 33 MFHs using microarray-based comparative genomic hybridisation (array CGH). PRINCIPAL FINDINGS: In general, the tumours showed numerous gains and losses of large chromosomal regions. The most frequent minimal recurrent regions of gain were 1p33-p32.3, 1p31.3-p31.2 and 1p21.3 (all gained in 58% of the samples), as well as 1q21.2-q21.3 and 20q13.2 (both 55%). The most frequent minimal recurrent regions of loss were 10q25.3-q26.11, 13q13.3-q14.2 and 13q14.3-q21.1 (all lost in 64% of the samples), as well as 2q36.3-q37.2 (61%), 1q41 (55%) and 16q12.1-q12.2 (52%). Statistical analyses revealed that gain of 1p33-p32.3 and 1p21.3 was significantly associated with better patient survival (P = 0.021 and 0.046, respectively). Comparison with similar array CGH data from 44 leiomyosarcomas identified seven chromosomal regions; 1p36.32-p35.2, 1p21.3-p21.1, 1q32.1-q42.13, 2q14.1-q22.2, 4q33-q34.3, 6p25.1-p21.32 and 7p22.3-p13, which were significantly different in copy number between the MFHs and leiomyosarcomas. CONCLUSIONS: A number of recurrent regions of gain and loss have been identified, some of which were associated with better patient survival. Several specific chromosomal regions with significant differences in copy number between MFHs and leiomyosarcomas were identified, and these aberrations may be used as additional tools for the differential diagnosis of MFHs and leiomyosarcomas

    Allele-specific copy number analysis of tumors

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    We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of “ASCAT profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development

    Pipamperone Population Pharmacokinetics Related to Effectiveness and Side Effects in Children and Adolescents

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    Background: Pipamperone is a frequently prescribed antipsychotic in children and adolescents in the Netherlands, Belgium, and Germany. However, pediatric pharmacokinetics and the relationship with side effects and efficacy are unknown. Currently, divergent pediatric dosing recommendations exist. Objectives: The objective of this study was to describe the population pharmacokinetics of pipamperone in children and adolescents; to correlate measured and predicted pipamperone trough concentrations and predicted 24-h area under the curves with effectiveness, extrapyramidal symptoms, and sedation; and to propose dose recommendations based on simulations. Methods: Pipamperone concentrations were collected from Dutch pediatric patients in a prospective naturalistic trial (n = 8), and German pediatric patients in a therapeutic drug monitoring service (n = 22). A total of 70 pipamperone concentrations were used to develop a population pharmacokinetic model with non-linear mixed-effects modeling (NONMEM®). Additionally, an additional random sample of 21 German patients with 33 pipamperone concentrations from the same therapeutic drug monitoring service was used for external validation. Pharmacokinetic parameters were related to clinical improvement, sedation, and extrapyramidal symptoms. Simulations were performed to determine optimal dosages. Results: In a one-compartment model, the apparent volume of distribution was 416 L/70 kg and the apparent clearance was 22.1 L/h/70 kg. Allometric scaling was used to correct for differences in bodyweight. The model was successfully externally validated. The median [25th–75th percentile] measured pipamperone trough concentrations were numerically higher in responders (98.0 µg/L [56.0–180.5 µg/L]) than in non-responders (58.0 µg/L [14.9–105.5 µg/L]), although non-significant (p = 0.14). A twice-daily 0.6-mg/kg dosage was better than a fixed dosage to attain the concentration range observed in responders. Conclusions: Our findings suggest that pipamperone therapeutic reference ranges may be lower for children with behavioral problems than recommended for adults with psychotic symptoms (100–400 µg/L). When dosing pipamperone in children and adolescents, bodyweight should be taken into account

    The effect of five years versus two years of specialised assertive intervention for first episode psychosis - OPUS II: study protocol for a randomized controlled trial

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    <p>Abstract</p> <p>Background</p> <p>The Danish OPUS I trial randomized 547 patients with first-episode psychosis to a two-year early-specialised assertive treatment programme (OPUS) versus standard treatment. The two years OPUS treatment had significant positive effects on psychotic and negative symptoms, secondary substance abuse, treatment adherence, lower dosage of antipsychotic medication, and a higher treatment satisfaction. However, three years after end of the OPUS treatment, the positive clinical effects were not sustained, except that OPUS-treated patients were significantly less likely to be institutionalised compared with standard-treated patients. The major objective of the OPUS II trial is to evaluate the effects of five years of OPUS treatment versus two years of OPUS treatment.</p> <p>Methods</p> <p>The OPUS II trial is designed as a randomized, open label, parallel group trial with blinded outcome assessment. Based on our sample size estimation, 400 patients treated in OPUS for two years will be randomized to further three years of OPUS treatment versus standard treatment. The specialized assertive OPUS treatment consists of three core elements: assertive community treatment, psycho-educational family treatment, and social skills training.</p> <p>Discussion</p> <p>It has been hypothesized that there is a critical period from onset up to five years, which represents a window of opportunity where a long-term course can be influenced. Extending the specialized assertive OPUS treatment up to five years may allow the beneficial effects to continue beyond the high-risk period, through consolidation of improved social and functional outcome.</p> <p>Trial registration</p> <p>Clinical Trial.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT00914238">NCT00914238</a></p
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