University of Duisburg-Essen

About: University of Duisburg-Essen is a education organization based out in Essen, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 16072 authors who have published 39972 publications receiving 1109199 citations.

Fasting Cycles Retard Growth of Tumors and Sensitize a Range of Cancer Cell Types to Chemotherapy

Abstract: Short-term starvation (or fasting) protects normal cells, mice, and potentially humans from the harmful side effects of a variety of chemotherapy drugs. Here, we show that treatment with starvation conditions sensitized yeast cells (Saccharomyces cerevisiae) expressing the oncogene-like RAS2val19 to oxidative stress and 15 of 17 mammalian cancer cell lines to chemotherapeutic agents. Cycles of starvation were as effective as chemotherapeutic agents in delaying progression of different tumors and increased the effectiveness of these drugs against melanoma, glioma, and breast cancer cells. In mouse models of neuroblastoma, fasting cycles plus chemotherapy drugs—but not either treatment alone—resulted in long-term cancer-free survival. In 4T1 breast cancer cells, short-term starvation resulted in increased phosphorylation of the stress-sensitizing Akt and S6 kinases, increased oxidative stress, caspase-3 cleavage, DNA damage, and apoptosis. These studies suggest that multiple cycles of fasting promote differential stress sensitization in a wide range of tumors and could potentially replace or augment the efficacy of certain chemotherapy drugs in the treatment of various cancers.

Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

Abstract: TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOG, we analyzed similar to 480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 x 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 x 10(-8)) and BRCA1 mutation carrier (P = 1.1 x 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 x 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 x 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 x 10(-12)) and BRCA1 mutation carrier (P = 1.6 x 10-14) breast and invasive ovarian (P = 1.3 x 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.

Sustainable data analysis with Snakemake.

Abstract: Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.

The nanoparticle biomolecule corona: lessons learned – challenge accepted?

Abstract: Besides the wide use of engineered nanomaterials (NMs) in technical products, their applications are not only increasing in biotechnology and biomedicine, but also in the environmental field. While the physico-chemical properties and behaviour of NMs can be characterized accurately under idealized conditions, this is no longer the case in complex physiological or natural environments. Herein, proteins and other biomolecules rapidly bind to NMs, forming a protein/biomolecule corona that critically affects the NMs' (patho)biological and technical identities. As the corona impacts the in vitro and/or in vivo NM applications in humans and ecosystems, a mechanistic understanding of its relevance and of the biophysical forces regulating corona formation is mandatory. Based on recent insights, we here critically review and present an updated concept of corona formation and evolution. We comment on how corona signatures may be linked to effects at the nano–bio interface in physiological and environmental systems. In order to comprehensively analyse corona profiles and to mechanistically understand the coronas' biological/ecological impact, we present a tiered multidisciplinary approach. To stimulate progress in this field, we introduce the potential impact of the corona for NM–microbiome–(human)host interactions and the novel concept of ‘nanologicals’, i.e., the nanomaterial-specific targeting of molecular machines. We conclude by discussing the relevant challenges that still need to be resolved in this field.

The placebo response in medicine: minimize, maximize or personalize?

Abstract: The therapeutic outcome of a drug or procedure is influenced by the placebo response in both drug development and clinical practice. Enck and colleagues examine how the placebo response can be utilized in these settings to ensure that the most desirable outcome is attained. Our understanding of the mechanisms mediating or moderating the placebo response to medicines has grown substantially over the past decade and offers the opportunity to capitalize on its benefits in future drug development as well as in clinical practice. In this article, we discuss three strategies that could be used to modulate the placebo response, depending on which stage of the drug development process they are applied. In clinical trials the placebo effect should be minimized to optimize drug–placebo differences, thus ensuring that the efficacy of the investigational drug can be truly evaluated. Once the drug is approved and in clinical use, placebo effects should be maximized by harnessing patients' expectations and learning mechanisms to improve treatment outcomes. Finally, personalizing placebo responses — which involves considering an individual's genetic predisposition, personality, past medical history and treatment experience — could also maximize therapeutic outcomes.