Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Treatment outcomes of new tuberculosis patients hospitalized in Kampala, Uganda: a prospective cohort study.

BACKGROUND: In most resource limited settings, new tuberculosis (TB) patients are usually treated as outpatients. We sought to investigate the reasons for hospitalisation and the predictors of poor treatment outcomes and mortality in a cohort of hospitalized new TB patients in Kampala, Uganda. METHODS AND FINDINGS: Ninety-six new TB patients hospitalised between 2003 and 2006 were enrolled and followed for two years. Thirty two were HIV-uninfected and 64 were HIV-infected. Among the HIV-uninfected, the commonest reasons for hospitalization were low Karnofsky score (47%) and need for diagnostic evaluation (25%). HIV-infected patients were commonly hospitalized due to low Karnofsky score (72%), concurrent illness (16%) and diagnostic evaluation (14%). Eleven HIV uninfected patients died (mortality rate 19.7 per 100 person-years) while 41 deaths occurred among the HIV-infected patients (mortality rate 46.9 per 100 person years). In all patients an unsuccessful treatment outcome (treatment failure, death during the treatment period or an unknown outcome) was associated with duration of TB symptoms, with the odds of an unsuccessful outcome decreasing with increasing duration. Among HIV-infected patients, an unsuccessful treatment outcome was also associated with male sex (P = 0.004) and age (P = 0.034). Low Karnofsky score (aHR = 8.93, 95% CI 1.88 - 42.40, P = 0.001) was the only factor significantly associated with mortality among the HIV-uninfected. Mortality among the HIV-infected was associated with the composite variable of CD4 and ART use, with patients with baseline CD4 below 200 cells/µL who were not on ART at a greater risk of death than those who were on ART, and low Karnofsky score (aHR = 2.02, 95% CI 1.02 - 4.01, P = 0.045). CONCLUSION: Poor health status is a common cause of hospitalisation for new TB patients. Mortality in this study was very high and associated with advanced HIV Disease and no use of ART

A Phase II Study of the Efficacy and Safety of Oral Selinexor in Recurrent Glioblastoma

PURPOSE: Selinexor is an oral selective inhibitor of exportin-1 (XPO1) with efficacy in various solid and hematological tumors. We assessed intra-tumoral penetration, safety, and efficacy of selinexor monotherapy for recurrent glioblastoma. PATIENTS AND METHODS: Seventy-six adults with Karnofsky Performance Status≥60 were enrolled. Patients undergoing cytoreductive surgery received up to three selinexor doses (twice weekly) pre-operatively (Arm A; N=8 patients). Patients not undergoing surgery received 50mg/m(2) (Arm B, N=24), or 60mg (Arm C, N=14) twice weekly, or 80mg once weekly (Arm D; N=30). Primary endpoint was six-month progression-free survival rate (PFS6). RESULTS: Median selinexor concentrations in resected tumors from patients receiving pre-surgical selinexor was 105.4nM (range 39.7-291nM). In Arms B, C, and D, respectively, the PFS6 was 10% (95%CI, 2.79-35.9), 7.7% (95%CI, 1.17-50.6), and 17% (95%CI, 7.78-38.3). Measurable reduction in tumor size was observed in 19 (28%) and RANO-response rate overall was 8.8% (Arm B, 8.3% (95%CI, 1.0-27.0); C:7.7% (95%CI, 0.2-36.0); D:10% (95%CI, 2.1-26.5)), with one complete and two durable partial responses in Arm D. Serious adverse events (AEs) occurred in 26 (34%) patients; one (1.3%) was fatal. The most common treatment-related AEs were fatigue (61%), nausea (59%), decreased appetite (43%) and thrombocytopenia (43%), and were manageable by supportive care and dose modification. Molecular studies identified a signature predictive of response (AUC=0.88). CONCLUSION: At 80mg weekly, single-agent selinexor induced responses and clinically relevant PFS6 with manageable side effects requiring dose reductions. Ongoing trials are evaluating safety and efficacy of selinexor in combination with other therapies for newly diagnosed or recurrent glioblastoma. TRIAL REGISTRATION: ClinicalTrials.gov, NCT0198634

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation

<p>Abstract</p> <p>Background</p> <p>External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.</p> <p>Results</p> <p>We therefore develop the concept of graph-decorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways in a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the features (e.g. genes) and are thus able to define a graph-delayed correlation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph-decorrelation algorithm (GraDe). To analyze alterations in the gene response in <it>IL-6 </it>stimulated primary mouse hepatocytes, we performed a time-course microarray experiment and applied GraDe. In contrast to standard techniques, the extracted time-resolved gene expression profiles showed that <it>IL-6 </it>activates genes involved in cell cycle progression and cell division. Genes linked to metabolic and apoptotic processes are down-regulated indicating that <it>IL-6 </it>mediated priming renders hepatocytes more responsive towards cell proliferation and reduces expenditures for the energy metabolism.</p> <p>Conclusions</p> <p>GraDe provides a novel framework for the decomposition of large-scale 'omics' data. We were able to show that including prior knowledge into the separation task leads to a much more structured and detailed separation of the time-dependent responses upon <it>IL-6 </it>stimulation compared to standard methods. A Matlab implementation of the GraDe algorithm is freely available at <url>http://cmb.helmholtz-muenchen.de/grade</url>.</p

TGFbeta Family Members Are Key Mediators in the Induction of Myofibroblast Phenotype of Human Adipose Tissue Progenitor Cells by Macrophages

International audienceOBJECTIVE: The present study was undertaken to characterize the remodeling phenotype of human adipose tissue (AT) macrophages (ATM) and to analyze their paracrine effects on AT progenitor cells. RESEARCH DESIGN AND METHODS: The phenotype of ATM, immunoselected from subcutaneous (Sc) AT originating from subjects with wide range of body mass index and from paired biopsies of Sc and omental (Om) AT from obese subjects, was studied by gene expression analysis in the native and activated states. The paracrine effects of ScATM on the phenotype of human ScAT progenitor cells (CD34(+)CD31(-)) were investigated. RESULTS: Two main ATM phenotypes were distinguished based on gene expression profiles. For ScAT-derived ATM, obesity and adipocyte-derived factors favored a pro-fibrotic/remodeling phenotype whereas the OmAT location and hypoxic culture conditions favored a pro-angiogenic phenotype. Treatment of native human ScAT progenitor cells with ScATM-conditioned media induced the appearance of myofibroblast-like cells as shown by expression of both α-SMA and the transcription factor SNAIL, an effect mimicked by TGFβ1 and activinA. Immunohistochemical analyses showed the presence of double positive α-SMA and CD34 cells in the stroma of human ScAT. Moreover, the mRNA levels of SNAIL and SLUG in ScAT progenitor cells were higher in obese compared with lean subjects. CONCLUSIONS: Human ATM exhibit distinct pro-angiogenic and matrix remodeling/fibrotic phenotypes according to the adiposity and the location of AT, that may be related to AT microenvironment including hypoxia and adipokines. Moreover, human ScAT progenitor cells have been identified as target cells for ScATM-derived TGFβ and as a potential source of fibrosis through their induction of myofibroblast-like cells

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

BACKGROUND: The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS: The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8-12 kgs weight loss) could always be differentiated from non-responders (<4 kgs weight loss). We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box) approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%+/-8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier) improved prediction accuracy to 80.9%+/-2.2%. CONCLUSION: Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition

Adipose tissue pathways involved in weight loss of cancer cachexia

White adipose tissue (WAT) constitutes our most expandable tissue and largest endocrine organ secreting hundreds of polypeptides collectively termed adipokines. Changes in WAT mass induce alterations in adipocyte secretion and function, which are linked to disturbed whole-body metabolism. Although the mechanisms controlling this are not clear they are dependent on changes in gene expression, a complex process which is regulated at several levels. Results in recent years have highlighted the role of small non-coding RNA molecules termed microRNAs (miRNAs), which regulate gene expression via post-transcriptional mechanisms. The aim of this thesis was to characterize global gene expression levels and describe novel miRNAs and adipokines controlling the function of human WAT in conditions with pathological increases or decreases in WAT mass. Obesity and cancer cachexia were selected as two models since they are both clinically relevant and characterized by involuntary changes in WAT mass. In Study I, expressional analyses were performed in subcutaneous WAT from cancer patients with or without cachexia and obese versus non-obese subjects. In total, 425 transcripts were found to be regulated in cancer cachexia. Pathway analyses based on this set of genes revealed that processes involving extracellular matrix, actin cytoskeleton and focal adhesion were significantly downregulated, whereas fatty acid metabolism was upregulated comparing cachectic with weight-stable cancer subjects. Furthermore, by overlapping these results with microarray data from an obesity study, many transcripts were found to be reciprocally regulated comparing the two conditions. This suggests that WAT gene expression in cancer cachexia and obesity are regulated by similar, albeit opposing, mechanisms. In Study II, the focus was on the family of fibroblast growth factors (FGFs), members of which have recently been implicated in the development of obesity and insulin resistance. A retrospective analysis of global gene expression data identified several FGFs (FGF1/2/7/9/13/18) to be expressed in WAT. However, only one, FGF1, was actively secreted from WAT and predominantly so from the adipocyte fraction. Moreover, FGF1 release was increased in obese compared to non-obese subjects, but was not normalized by weight loss. Although the clinical significance of these findings is not yet clear, it can be hypothesized that FGF1 may play a role in WAT growth, possibly by promoting fat cell proliferation and/or differentiation. In Study III, we identified adipose miRNAs regulated in obesity. Out of eleven miRNAs regulated by changes in body fat mass, ten controlled the production of the pro-inflammatory chemoattractant chemokine (C-C motif) ligand 2 (CCL2) when overexpressed in fat cells and for two, miR-126 and -193b, signaling circuits were defined. In Study IV, a novel adipokine, semaphorin 3C (SEMA3C), was identified by combining transcriptome and secretome data. Detailed studies focusing on SEMA3C revealed that this factor was secreted from adipocytes and induced the expression of extracellular matrix and matricellular genes in preadipocytes. Furthermore, SEMA3C mRNA levels correlated with interstitial fibrosis and insulin resistance in WAT derived from subjects with a wide range in BMI. In summary, the results presented in this thesis have delineated transcriptional alterations in WAT in two clinically relevant conditions, obesity and cancer cachexia. This has allowed the identification of novel adipokines and microRNAs with potential pathophysiological importance. These findings form the basis for further studies aiming at understanding the central role of WAT in disorders associated with metabolic complications