Prediction of regulatory targets of alternative isoforms of the epidermal growth factor receptor in a glioblastoma cell line.

BackgroundThe epidermal growth factor receptor (EGFR) is a major regulator of proliferation in tumor cells. Elevated expression levels of EGFR are associated with prognosis and clinical outcomes of patients in a variety of tumor types. There are at least four splice variants of the mRNA encoding four protein isoforms of EGFR in humans, named I through IV. EGFR isoform I is the full-length protein, whereas isoforms II-IV are shorter protein isoforms. Nevertheless, all EGFR isoforms bind the epidermal growth factor (EGF). Although EGFR is an essential target of long-established and successful tumor therapeutics, the exact function and biomarker potential of alternative EGFR isoforms II-IV are unclear, motivating more in-depth analyses. Hence, we analyzed transcriptome data from glioblastoma cell line SF767 to predict target genes regulated by EGFR isoforms II-IV, but not by EGFR isoform I nor other receptors such as HER2, HER3, or HER4.ResultsWe analyzed the differential expression of potential target genes in a glioblastoma cell line in two nested RNAi experimental conditions and one negative control, contrasting expression with EGF stimulation against expression without EGF stimulation. In one RNAi experiment, we selectively knocked down EGFR splice variant I, while in the other we knocked down all four EGFR splice variants, so the associated effects of EGFR II-IV knock-down can only be inferred indirectly. For this type of nested experimental design, we developed a two-step bioinformatics approach based on the Bayesian Information Criterion for predicting putative target genes of EGFR isoforms II-IV. Finally, we experimentally validated a set of six putative target genes, and we found that qPCR validations confirmed the predictions in all cases.ConclusionsBy performing RNAi experiments for three poorly investigated EGFR isoforms, we were able to successfully predict 1140 putative target genes specifically regulated by EGFR isoforms II-IV using the developed Bayesian Gene Selection Criterion (BGSC) approach. This approach is easily utilizable for the analysis of data of other nested experimental designs, and we provide an implementation in R that is easily adaptable to similar data or experimental designs together with all raw datasets used in this study in the BGSC repository, https://github.com/GrosseLab/BGSC

The ape lottery : chimpanzees fail to consider spatial information when drawing statistical inferences

Funding: this work was supported by a research grant of the German Science Foundation DFG (grant # RA 2155/3-1) to Hannes Rakoczy and Josep Call. We acknowledge additional support by the Leibniz Association through funding for the Leibniz ScienceCampus Primate Cognition.Humans and nonhuman great apes share a sense for intuitive statistics, making intuitive probability judgments based on proportional information. This ability is of tremendous importance, in particular for predicting the outcome of events using prior information and for inferring general regularities from limited numbers of observations. Already in infancy, humans functionally integrate intuitive statistics with other cognitive domains, rendering this type of reasoning a powerful tool to make rational decisions in a variety of contexts. Recent research suggests that chimpanzees are capable of one type of such cross-domain integration: The integration of statistical and social information. Here, we investigated whether apes can also integrate physical information into their statistical inferences. We tested 14 sanctuary-living chimpanzees in a new task setup consisting of two “gumball machine”-apparatuses that were filled with different combinations of preferred and non-preferred food items. In four test conditions, subjects decided which of two apparatuses they wanted to operate to receive a random sample, while we varied both the proportional composition of the food items as well as their spatial configuration above and below a barrier. To receive the more favorable sample, apes needed to integrate proportional and spatial information. Chimpanzees succeeded in conditions in which we provided them either with proportional information or spatial information, but they failed to correctly integrate both types of information when they were in conflict. Whether these limitations in chimpanzees' performance reflect true limits of cognitive competence or merely performance limitations due to accessory task demands is still an open question.Publisher PDFPeer reviewe

Deployment of RDFa, Microdata, and Microformats on the Web – A Quantitative Analysis

More and more websites embed structured data describing for instance products, reviews, blog posts, people, organizations, events, and cooking recipes into their HTML pages using markup standards such as Microformats, Microdata and RDFa. This development has accelerated in the last two years as major Web companies, such as Google, Facebook, Yahoo!, and Microsoft, have started to use the embedded data within their applications. In this paper, we analyze the adoption of RDFa, Microdata, and Microformats across the Web. Our study is based on a large public Web crawl dating from early 2012 and consisting of 3 billion HTML pages which originate from over 40 million websites. The analysis reveals the deployment of the different markup standards, the main topical areas of the published data as well as the different vocabularies that are used within each topical area to represent data. What distinguishes our work from earlier studies, published by the large Web companies, is that the analyzed crawl as well as the extracted data are publicly available. This allows our findings to be verified and to be used as starting points for further domain-specific investigations as well as for focused information extraction endeavors

Causes and Consequences of A Glutamine Induced Normoxic HIF1 Activity for the Tumor Metabolism

The transcription factor hypoxia-inducible factor 1 (HIF1) is the crucial regulator of genes that are involved in metabolism under hypoxic conditions, but information regarding the transcriptional activity of HIF1 in normoxic metabolism is limited. Different tumor cells were treated under normoxic and hypoxic conditions with various drugs that affect cellular metabolism. HIF1ff was silenced by siRNA in normoxic/hypoxic tumor cells, before RNA sequencing and bioinformatics analyses were performed while using the breast cancer cell line MDA-MB-231 as a model. Differentially expressed genes were further analyzed and validated by qPCR, while the activity of the metabolites was determined by enzyme assays. Under normoxic conditions, HIF1 activity was significantly increased by (i) glutamine metabolism, which was associated with the release of ammonium, and it was decreased by (ii) acetylation via acetyl CoA synthetase (ACSS2) or ATP citrate lyase (ACLY), respectively, and (iii) the presence of L-ascorbic acid, citrate, or acetyl-CoA. Interestingly, acetylsalicylic acid, ibuprofen, L-ascorbic acid, and citrate each significantly destabilized HIF1ff only under normoxia. The results from the deep sequence analyses indicated that, in HIF1-siRNA silenced MDA-MB-231 cells, 231 genes under normoxia and 1384 genes under hypoxia were transcriptionally significant deregulated in a HIF1-dependent manner. Focusing on glycolysis genes, it was confirmed that HIF1 significantly regulated six normoxic and 16 hypoxic glycolysis-associated gene transcripts. However, the results from the targeted metabolome analyses revealed that HIF1 activity affected neither the consumption of glucose nor the release of ammonium or lactate; however, it significantly inhibited the release of the amino acid alanine. This study comprehensively investigated, for the first time, how normoxic HIF1 is stabilized, and it analyzed the possible function of normoxic HIF1 in the transcriptome and metabolic processes of tumor cells in a breast cancer cell model. Furthermore, these data imply that HIF1 compensates for the metabolic outcomes of glutaminolysis and, subsequently, theWarburg effect might be a direct consequence of the altered amino acid metabolism in tumor cells

Multicenter Collaborative Study to Optimize Mass Spectrometry Workflows of Clinical Specimens

The foundation for integrating mass spectrometry (MS)-based proteomics into systems medicine is the development of standardized start-to-finish and fit-for-purpose workflows for clinical specimens. An essential step in this pursuit is to highlight the common ground in a diverse landscape of different sample preparation techniques and liquid chromatography-mass spectrometry (LC-MS) setups. With the aim to benchmark and improve the current best practices among the proteomics MS laboratories of the CLINSPECT-M consortium, we performed two consecutive round-robin studies with full freedom to operate in terms of sample preparation and MS measurements. The six study partners were provided with two clinically relevant sample matrices: plasma and cerebrospinal fluid (CSF). In the first round, each laboratory applied their current best practice protocol for the respective matrix. Based on the achieved results and following a transparent exchange of all lab-specific protocols within the consortium, each laboratory could advance their methods before measuring the same samples in the second acquisition round. Both time points are compared with respect to identifications (IDs), data completeness, and precision, as well as reproducibility. As a result, the individual performances of participating study centers were improved in the second measurement, emphasizing the effect and importance of the expert-driven exchange of best practices for direct practical improvements

Height, selected genetic markers and prostate cancer risk:Results from the PRACTICAL consortium

Background: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. Methods: We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. Results: The results suggest that height is associated with high-grade prostate cancer risk. Men with height 4180cm are at a 22% increased risk as compared to men with height o173cm (OR 1.22, 95% CI 1.01–1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. Conclusions: There was no evidence of gene-environment interaction between height and the selected candidate SNPs. Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.</p

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification