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Bhujbal S.V.,CRP Sante | Bhujbal S.V.,University of Groningen | de Vos P.,University of Groningen | Niclou S.P.,CRP Sante
Advanced Drug Delivery Reviews | Year: 2014

Malignant brain tumors including glioblastoma are incurable cancers. Over the last years a number of promising novel treatment approaches have been investigated including the application of inhibitors of receptor tyrosine kinases and downstream targets, immune-based therapies and anti-angiogenic agents. Unfortunately so far the major clinical trials in glioblastoma patients did not deliver clear clinical benefits. Systemic brain tumor therapy is seriously hampered by poor drug delivery to the brain. Although in glioblastoma, the blood brain barrier is disrupted in the tumor core, the major part of the tumor is largely protected by an intact blood brain barrier. Active cytotoxic compounds encapsulated into liposomes, micelles, and nanoparticles constitute novel treatment options because they can be designed to facilitate entry into the brain parenchyma. In the case of biological therapeutics, encapsulation of therapeutic cells and their implantation into the surgical cavity represents another promising approach. This technology provides long term release of the active compound at the tumor site and reduces side effects associated with systemic delivery. The proof of principle of encapsulated cell factories has been successfully demonstrated in experimental animal models and should pave the way for clinical application. Here we review the challenges associated with the treatment of brain tumors and the different encapsulation options available for drugs and living cells, with an emphasis on alginate based cell encapsulation technology. © 2014 Elsevier B.V.


Torsvik A.,University of Bergen | Bjerkvig R.,University of Bergen | Bjerkvig R.,CRP Sante
Cancer Treatment Reviews | Year: 2013

Mesenchymal (multipotent) stem/stromal cells (MSCs) may affect cancer progression through a number of secreted factors triggering activation of various cell signaling pathways. Depending on receptor status, phosphatase and tensin homolog (PTEN) status, or Wnt activation in the cancer cells, the signals may either result in increased growth and metastasis or lead to inhibition of growth with increased cell death. Thus, MSCs can play a dual role in cancer progression depending on the cellular context wherein they reside. The phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway has a central role in regulating tumor growth, and several MSC secreted factors stimulate activation of this pathway. A comprehensive understanding of the signals regulating MSC-tumor cross-talk is highly important for the development of MSCs as potential therapeutic vehicles. Thus, the presented review focuses on factors released by MSCs and on the dual role they may have on various stages of tumorigenesis. © 2012 Elsevier Ltd.


Vausort M.,CRP Sante | Wagner D.R.,Center Hospitalier | Devaux Y.,CRP Sante
Circulation Research | Year: 2014

Rationale: Long noncoding RNAs (lncRNAs) constitute a novel class of noncoding RNAs that regulate gene expression. Although recent data suggest that lncRNAs may be associated with cardiac disease, little is known about lncRNAs in the setting of myocardial ischemia. Objective: To measure lncRNAs in patients with myocardial infarction (MI). Methods and Results: We enrolled 414 patients with acute MI treated by primary percutaneous coronary intervention. Blood samples were harvested at the time of reperfusion. Expression levels of 5 lncRNAs were measured in peripheral blood cells by quantitative polymerase chain reaction: hypoxia inducible factor 1A antisense RNA 2, cyclin-dependent kinase inhibitor 2B antisense RNA 1 (ANRIL), potassium voltage-gated channel, KQT-like subfamily, member 1 opposite strand/antisense transcript 1 (KCNQ1OT1), myocardial infarction-associated transcript, and metastasisassociated lung adenocarcinoma transcript 1. Levels of hypoxia inducible factor 1A antisense RNA 2, KCNQ1OT1, and metastasis-associated lung adenocarcinoma transcript 1 were higher in patients with MI than in healthy volunteers (P<0.01), and levels of ANRIL were lower in patients with MI (P=0.003). Patients with ST-segment-elevation MI had lower levels of ANRIL (P<0.001), KCNQ1OT1 (P<0.001), myocardial infarction-associated transcript (P<0.001), and metastasis-associated lung adenocarcinoma transcript 1 (P=0.005) when compared with patients with non-STsegment. elevation MI. Levels of ANRIL were associated with age, diabetes mellitus, and hypertension. Patients presenting within 3 hours of chest pain onset had elevated levels of hypoxia inducible factor 1A antisense RNA 2 when compared with patients presenting later on. ANRIL, KCNQ1OT1, myocardial infarction-associated transcript, and metastasis-associated lung adenocarcinoma transcript 1 were significant univariable predictors of left ventricular dysfunction as assessed by an ejection fraction ≤40% at 4-month follow-up. In multivariable and reclassification analyses, ANRIL and KCNQ1OT1 improved the prediction of left ventricular dysfunction by a model, including demographic features, clinical parameters, and cardiac biomarkers. Conclusions: Levels of lncRNAs in blood cells are regulated after MI and may help in prediction of outcome. This motivates further investigation of the role of lncRNAs after MI. © 2014 American Heart Association, Inc.


Targeted MS analyses based on selected reaction monitoring (SRM) has enabled significant achievements in proteomic quantification, such that its application to clinical studies has augured great advancements for life sciences. The approach has been challenged by the complexity of clinical samples that affects the selectivity of measurements, in many cases limiting analytical performances to a larger extent than expected. This Personal Perspective discusses some insight to better comprehend the mismatch between the often underestimated sample complexity and the selectivity of SRM measurements performed on a triple quadrupole instrument. The implications for the design and evaluation of SRM assays are discussed and illustrated with selected examples, providing a baseline for a more critical use of the technique in the context of clinical samples and to evaluate alternative methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Thomas C.,CRP Sante
Frontiers in Plant Science | Year: 2012

Progress in live-cell imaging of the cytoskeleton has significantly extended our knowledge about the organization and dynamics of actin filaments near the plasma membrane of plant cells. Noticeably, two populations of filamentous structures can be distinguished. On the one hand, fine actin filaments which exhibit an extremely dynamic behavior basically characterized by fast polymerization and prolific severing events, a process referred to as actin stochastic dynamics. On the other hand, thick actin bundles which are composed of several filaments and which are comparatively more stable although they constantly remodel as well. There is evidence that the actin cytoskeleton plays critical roles in trafficking and signaling at both the cell cortex and organelle periphery but the exact contribution of actin bundles remains unclear. A common view is that actin bundles provide the long-distance tracks used by myosin motors to deliver their cargo to growing regions and accordingly play a particularly important role in cell polarization. However, several studies support that actin bundles are more than simple passive highways and display multiple and dynamic roles in the regulation of many processes, such as cell elongation, polar auxin transport, stomatal and chloroplast movement, and defense against pathogens. The list of identified plant actin-bundling proteins is ever expanding, supporting that plant cells shape structurally and functionally different actin bundles. Here I review the most recently characterized actin-bundling proteins, with a particular focus on those potentially relevant to membrane trafficking and/or signaling. © 2012 Thomas.


Senn S.,CRP Sante
Statistics in Medicine | Year: 2013

I consider seven misunderstandings that may be encountered about the nature, purpose and properties of randomisation in clinical trials. Some concern the practical realities of clinical research on patients. Others are to do with the value and purpose of balance. Still others are to do with a confusion about the role of conditioning in valid statistical inference. I consider a simple game of chance involving two dice to illustrate some points about inference and then consider the seven misunderstandings in turn. I conclude that although one should not make a fetish of randomisation, when proposing alternatives to randomisation in clinical trials, one should be very careful to be precise about the exact nature of the alternative being considered if one is to avoid the danger of underestimating the advantages that randomisation can offer. © 2012 John Wiley & Sons, Ltd.


Steinmetz A.,CRP Sante
Anti-cancer agents in medicinal chemistry | Year: 2014

We have studied the anti-cancer activities of antofine N-oxide isolated and purified from the medicinal plant Cynanchum vincetoxicum. Antofine N-oxide displayed a strong inhibitory effect on several solid tumor cell lines (glioblastoma, breast carcinoma and lung carcinoma) and on a T-cell leukemia cell line. Remarkably, its cytotoxic effect was considerably weaker in non-cancer cells. Antofine N-oxide was found to inhibit proliferation of the solid tumor cells whereas it caused apoptotic cell death in the leukemia cells. A microarray analysis after a short treatment revealed that the number of differentially expressed genes was considerably higher in solid tumor than in leukemia cells. Up-regulated genes in the three solid tumor cell lines include genes related to TNFα signaling, of which TNFα was among the most significantly induced. A functional analysis revealed that TNFR1 signaling was most likely activated in the solid tumor cells. The increased mRNA levels of several genes of this pathway (namely TNFα, TNFAIP3 and BIRC3) were confirmed by real-time quantitative PCR after different treatment durations. Finally a slight inhibition of NFκB-mediated transcription was observed in the same cells. Together our results suggest that inhibition of cell proliferation in solid tumor cells essentially occurs through TNFα signaling whereas this pathway is not activated in leukemia cells. Apoptotic cell death in the latter is induced by a distinct yet unknown pathway.


Lesur A.,CRP Sante | Domon B.,CRP Sante
Proteomics | Year: 2015

Targeted quantitative proteomic analyses aim at systematically measuring the abundance of proteins in large sets of samples, without biases or missing values. One typical implementation is the verification of biomarker candidates in bodily fluids, which measures extended lists of validated transitions using triple quadrupole instruments in selected reaction monitoring (SRM) mode. However, the selectivity of this mass spectrometer is limited by the resolving power of its mass analyzers, and interferences may require the reanalysis of the samples. Despite the efforts undertaken in the development of software, and resources to design SRM studies, and to analyze and validate the data, the process remains tedious and time consuming. The development of fast scanning high-resolution and accurate mass (HRAM) spectrometers, such as the quadrupole TOF and the quadrupole orbitrap instruments, offers alternatives for targeted analyses. The selectivity of HRAM measurements in complex samples is greatly improved by effectively separating co-eluting interferences. The fragment ion chromatograms are extracted from the high-resolution MS/MS data using a narrow mass tolerance. The entire process is straightforward as the selection of fragment ions is performed postacquisition. This account describes the different HRAM techniques and discusses their advantages and limitations in the context of targeted proteomic analyses. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Azuaje F.,CRP Sante
Cardiovascular Research | Year: 2013

This article introduces fundamental concepts to guide the analysis and interpretation of drug-target interaction networks. An overview of the generation and integration of interaction networks is followed by key strategies for extracting biologically meaningful information. The article highlights how this information can enable novel translational and clinically motivated applications. Important advances for the discovery of new treatments and for the detection of adverse drug effects are discussed. Examples of applications and findings originating from cardiovascular research are presented. The review ends with a discussion of crucial challenges and opportunities. © 2012 Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2012.


Background: Measures of node centrality in biological networks are useful to detect genes with critical functional roles. In gene co-expression networks, highly connected genes (i.e., candidate hubs) have been associated with key disease-related pathways. Although different approaches to estimating gene centrality are available, their potential biological relevance in gene co-expression networks deserves further investigation. Moreover, standard measures of gene centrality focus on binary interaction networks, which may not always be suitable in the context of co-expression networks. Here, I also investigate a method that identifies potential biologically meaningful genes based on a weighted connectivity score and indicators of statistical relevance.Results: The method enables a characterization of the strength and diversity of co-expression associations in the network. It outperformed standard centrality measures by highlighting more biologically informative genes in different gene co-expression networks and biological research domains. As part of the illustration of the gene selection potential of this approach, I present an application case in zebrafish heart regeneration. The proposed technique predicted genes that are significantly implicated in cellular processes required for tissue regeneration after injury.Conclusions: A method for selecting biologically informative genes from gene co-expression networks is provided, together with free open software.Reviewers: This article was reviewed by Anthony Almudevar, Maciej M Kańduła (nominated by David P Kreil) and Christine Wells. © 2014 Azuaje; licensee BioMed Central Ltd.

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