Identification of claudin-4 as a marker highly overexpressed in both primary and metastatic prostate cancer

In the quest for markers of expression and progression for prostate cancer (PCa), the majority of studies have focussed on molecular data exclusively from primary tumours. Although expression in metastases is inferred, a lack of correlation with secondary tumours potentially limits their applicability diagnostically and therapeutically. Molecular targets were identified by examining expression profiles of prostate cell lines using cDNA microarrays. Those genes identified were verified on PCa cell lines and tumour samples from both primary and secondary tumours using real-time RT–PCR, western blotting and immunohistochemistry. Claudin-4, coding for an integral membrane cell-junction protein, was the most significantly (P<0.00001) upregulated marker in both primary and metastatic tumour specimens compared with benign prostatic hyperplasia at both RNA and protein levels. In primary tumours, claudin-4 was more highly expressed in lower grade (Gleason 6) lesions than in higher grade (Gleason ⩾7) cancers. Expression was prominent throughout metastases from a variety of secondary sites in fresh-frozen and formalin-fixed specimens from both androgen-intact and androgen-suppressed patients. As a result of its prominent expression in both primary and secondary PCas, together with its established role as a receptor for Clostridium perfringens enterotoxin, claudin-4 may be useful as a potential marker and therapeutic target for PCa metastases

5′UTR Variants of Ribosomal Protein S19 Transcript Determine Translational Efficiency: Implications for Diamond-Blackfan Anemia and Tissue Variability

Background: Diamond-Blackfan anemia (DBA) is a lineage specific and congenital erythroblastopenia. The disease is associated with mutations in genes encoding ribosomal proteins resulting in perturbed ribosomal subunit biosynthesis. The RPS19 gene is mutated in approximately 25 % of DBA patients and a variety of coding mutations have been described, all presumably leading to haploinsufficiency. A subset of patients carries rare polymorphic sequence variants within the 59untranslated region (59UTR) of RPS19. The functional significance of these variants remains unclear. Methodology/Principal Findings: We analyzed the distribution of transcriptional start sites (TSS) for RPS19 mRNAs in testis and K562 cells. Twenty-nine novel RPS19 transcripts were identified with different 59UTR length. Quantification of expressed w.t. 59UTR variants revealed that a short 59UTR correlates with high levels of RPS19. The total levels of RPS19 transcripts showed a broad variation between tissues. We also expressed three polymorphic RPS19 59UTR variants identified in DBA patients. The sequence variants include two insertions (c.-147_-146insGCCA and c.-147_-146insAGCC) and one deletion (c.-144_-141delTTTC). The three 59UTR polymorphisms are associated with a 20–30 % reduction in RPS19 protein levels when compared to the wild-type (w.t.) 59UTR of corresponding length. Conclusions: The RPS19 gene uses a broad range of TSS and a short 59UTR is associated with increased levels of RPS19. Comparisons between tissues showed a broad variation in the total amount of RPS19 mRNA and in the distribution of TS

Missing Data in Randomized Clinical Trials for Weight Loss: Scope of the Problem, State of the Field, and Performance of Statistical Methods

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis

High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution

Are all ‘research fields’ equal? Rethinking practice for the use of data from crowd-sourcing market places

New technologies like large-scale social media sides (e.g., Facebook and Twitter) and crowdsourcing services (e.g., Amazon Mechanical Turk, Crowdflower, Clickworker) impact social science research and provide many new and interesting avenues for research. The use of these new technologies for research has not been without challenges and a recently published psychological study on Facebook led to a widespread discussion on the ethics of conducting large-scale experiments online. Surprisingly little has been said about the ethics of conducting research using commercial crowdsourcing market places. In this paper, I want to focus on the question of which ethical questions are raised by data collection with crowdsourcing tools. I briefly draw on implications of internet research more generally and then focus on the specific challenges that research with crowdsourcing tools faces. I identify fair-pay and related issues of respect for autonomy as well as problems with power dynamics between researcher and participant, which has implications for ‘withdrawal-withoutprejudice’, as the major ethical challenges with crowdsourced data. Further, I will to draw attention on how we can develop a ‘best practice’ for researchers using crowdsourcing tools

An Unexpected Function of the Prader-Willi Syndrome Imprinting Center in Maternal Imprinting in Mice

Genomic imprinting is a phenomenon that some genes are expressed differentially according to the parent of origin. Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurobehavioral disorders caused by deficiency of imprinted gene expression from paternal and maternal chromosome 15q11–q13, respectively. Imprinted genes at the PWS/AS domain are regulated through a bipartite imprinting center, the PWS-IC and AS-IC. The PWS-IC activates paternal-specific gene expression and is responsible for the paternal imprint, whereas the AS-IC functions in the maternal imprint by allele-specific repression of the PWS-IC to prevent the paternal imprinting program. Although mouse chromosome 7C has a conserved PWS/AS imprinted domain, the mouse equivalent of the human AS-IC element has not yet been identified. Here, we suggest another dimension that the PWS-IC also functions in maternal imprinting by negatively regulating the paternally expressed imprinted genes in mice, in contrast to its known function as a positive regulator for paternal-specific gene expression. Using a mouse model carrying a 4.8-kb deletion at the PWS-IC, we demonstrated that maternal transmission of the PWS-IC deletion resulted in a maternal imprinting defect with activation of the paternally expressed imprinted genes and decreased expression of the maternally expressed imprinted gene on the maternal chromosome, accompanied by alteration of the maternal epigenotype toward a paternal state spread over the PWS/AS domain. The functional significance of this acquired paternal pattern of gene expression was demonstrated by the ability to complement PWS phenotypes by maternal inheritance of the PWS-IC deletion, which is in stark contrast to paternal inheritance of the PWS-IC deletion that resulted in the PWS phenotypes. Importantly, low levels of expression of the paternally expressed imprinted genes are sufficient to rescue postnatal lethality and growth retardation in two PWS mouse models. These findings open the opportunity for a novel approach to the treatment of PWS

Characterization of FUS Mutations in Amyotrophic Lateral Sclerosis Using RNA-Seq

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease resulting in severe muscle weakness and eventual death by respiratory failure. Although little is known about its pathogenesis, mutations in fused in sarcoma/translated in liposarcoma (FUS) are causative for familial ALS. FUS is a multifunctional protein that is involved in many aspects of RNA processing. To elucidate the role of FUS in ALS, we overexpressed wild-type and two mutant forms of FUS in HEK-293T cells, as well as knocked-down FUS expression. This was followed by RNA-Seq to identify genes which displayed differential expression or altered splicing patterns. Pathway analysis revealed that overexpression of wild-type FUS regulates ribosomal genes, whereas knock-down of FUS additionally affects expression of spliceosome related genes. Furthermore, cells expressing mutant FUS displayed global transcription patterns more similar to cells overexpressing wild-type FUS than to the knock-down condition. This observation suggests that FUS mutants do not contribute to the pathogenesis of ALS through a loss-of-function. Finally, our results demonstrate that the R521G and R522G mutations display differences in their influence on transcription and splicing. Taken together, these results provide additional insights into the function of FUS and how mutations contribute to the development of ALS.ALS Foundation NetherlandsAdessium FoundationSeventh Framework Programme (European Commission) (grant number 259867)Thierry Latran FoundationNational Institutes of Health (U.S.) (NIH/NINDS grant R01NS073873)National Institute of Neurological Disorders and Stroke (U.S.) (NIH/NINDS grant numbers 1R01NS065847

Accurate molecular classification of cancer using simple rules

<p>Abstract</p> <p>Background</p> <p>One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible.</p> <p>Methods</p> <p>We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV) of training sets and classification of independent test sets.</p> <p>Results</p> <p>We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML]), lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML). Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods.</p> <p>Conclusion</p> <p>In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.</p