Mapping of ESE-1 subdomains required to initiate mammary epithelial cell transformation via a cytoplasmic mechanism

<p>Abstract</p> <p>Background</p> <p>The ETS family transcription factor ESE-1 is often overexpressed in human breast cancer. ESE-1 initiates transformation of MCF-12A cells via a non-transcriptional, cytoplasmic process that is mediated by a unique 40-amino acid serine and aspartic acid rich (SAR) subdomain, whereas, ESE-1's nuclear transcriptional property is required to maintain the transformed phenotype of MCF7, ZR-75-1 and T47D breast cancer cells.</p> <p>Results</p> <p>To map the minimal functional nuclear localization (NLS) and nuclear export (NES) signals, we fused in-frame putative NLS and NES motifs between GFP and the SAR domain. Using these GFP constructs as reporters of subcellular localization, we mapped a single NLS to six basic amino acids (²⁴²HGKRRR²⁴⁷) in the AT-hook and two CRM1-dependent NES motifs, one to the pointed domain (NES1: ¹⁰²LCNCALEELRL¹¹²) and another to the DNA binding domain (DBD), (NES2: ²⁷⁵LWEFIRDILI²⁸⁴). Moreover, analysis of a putative NLS located in the DBD (³¹⁶GQKKKNSN³²³) by a similar GFP-SAR reporter or by internal deletion of the DBD, revealed this sequence to lack NLS activity. To assess the role of NES2 in regulating ESE-1 subcellular localization and subsequent transformation potency, we site-specifically mutagenized NES2, within full-length GFP-ESE-1 and GFP-NES2-SAR reporter constructs. These studies show that site-specific mutation of NES2 completely abrogates ESE-1 transforming activity. Furthermore, we show that exclusive cytoplasmic targeting of the SAR domain is sufficient to initiate transformation, and we report that an intact SAR domain is required, since block mutagenesis reveals that an intact SAR domain is necessary to maintain its full transforming potency. Finally, using a monoclonal antibody targeting the SAR domain, we demonstrate that the SAR domain contains a region accessible for protein - protein interactions.</p> <p>Conclusions</p> <p>These data highlight that ESE-1 contains NLS and NES signals that play a critical role in regulating its subcellular localization and function, and that an intact SAR domain mediates MEC transformation exclusively in the cytoplasm, via a novel nontranscriptional mechanism, whereby the SAR motif is accessible for ligand and/or protein interactions. These findings are significant, since they provide novel molecular insights into the functions of ETS transcription factors in mammary cell transformation.</p

Production and validation of durable, high quality standardized malaria microscopy slides for teaching, testing and quality assurance during an era of declining diagnostic proficiency

Background: Sets of Giemsa-stained, blood smear slides with systematically verified composite diagnoses would contribute substantially to development of externally validated quality assurance systems for the microscopic diagnosis of malaria. Methods: whole blood from Plasmodium-positive donors in Cambodia and Indonesia and individuals with no history of risk for malaria was collected. Using standard operating procedures, technicians prepared Giemsastained thick and thin smears from each donor. One slide from each of the first 35 donations was distributed to each of 28 individuals acknowledged by reputation as having expertise in the microscopic diagnosis of malaria. These reference readers recorded presence or absence of Plasmodium species and parasite density. A composite diagnosis for each donation was determined based on microscopic findings and species-specific small subunit ribosomal RNA (ssrRNA) DNA polymerase chain reaction (PCR) amplification. Results: More than 12, 000 slides were generated from 124 donations. Reference readers correctly identified presence of parasites on 85% of slides with densities \u3c100 parasites/μl, which improved to 100% for densities \u3e350 parasites/μl. Percentages of agreement with composite diagnoses were highest for Plasmodium falciparum (99%), followed by Plasmodium vivax (86%). Conclusion: Herein, a standardized method for producing large numbers of consistently high quality, durable Giemsa-stained blood smears and validating composite diagnoses for the purpose of creating a malaria slide repository in support of initiatives to improve training and competency assessment amidst a background of variability in diagnosis is described

Reader technique as a source of variability in determining malaria parasite density by microscopy

BACKGROUND: Accurate identification and quantification of malaria parasites are critical for measuring clinical trial outcomes. Positive and negative diagnosis is usually sufficient for the assessment of therapeutic outcome, but vaccine or prophylactic drug trials require measuring density of infection as a primary endpoint. Microscopy is the most established and widely-used technique for quantifying parasite densities in the blood. METHODS: Results obtained by 24–27 expert malaria microscopists, who had independently read 895 slides from 35 donors, were analysed to understand how reader technique contributes to discrepancy in measurements of parasite density over a wide range of densities. RESULTS: Among these 35 donations, standard deviations ranged from 30% to 250% of the mean parasite density and the percent discrepancy was inversely correlated with the mean parasite density. The number of white blood cells indexed and whether parasites were counted in the thick film or thin film were shown to significantly contribute to discrepancy amongst microscopists. CONCLUSION: Errors in microscopy measurements are not widely appreciated or addressed but have serious consequences for efficacy trials, including possibly abandoning promising vaccine candidates

Biomarkers Predictive of Exacerbations in the SPIROMICS and COPDGene Cohorts

Rationale: Chronic obstructive pulmonary disease exacerbations are associated with disease progression, higher healthcare cost, and increased mortality. Published predictors of future exacerbations include previous exacerbation, airflow obstruction, poor overall health, home oxygen use, and gastroesophageal reflux

The value of blood cytokines and chemokines in assessing COPD

Background: Blood biomarkers are increasingly used to stratify high risk chronic obstructive pulmonary disease (COPD) patients; however, there are fewer studies that have investigated multiple biomarkers and replicated in multiple large well-characterized cohorts of susceptible current and former smokers. Methods: We used two MSD multiplex panels to measure 9 cytokines and chemokines in 2123 subjects from COPDGene and 1117 subjects from SPIROMICS. These biomarkers included: interleukin (IL)-2, IL-6, IL-8, IL-10, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, eotaxin/CCL-11, eotaxin-3/CCL-26, and thymus and activation-regulated chemokine (TARC)/CCL-17. Regression models adjusted for clinical covariates were used to determine which biomarkers were associated with the following COPD phenotypes: airflow obstruction (forced expiratory flow at 1 s (FEV1%) and FEV1/forced vital capacity (FEV1/FVC), chronic bronchitis, COPD exacerbations, and emphysema. Biomarker-genotype associations were assessed by genome-wide association of single nucleotide polymorphisms (SNPs). Results: Eotaxin and IL-6 were strongly associated with airflow obstruction and accounted for 3–5% of the measurement variance on top of clinical variables. IL-6 was associated with progressive airflow obstruction over 5 years and both IL-6 and IL-8 were associated with progressive emphysema over 5 years. None of the biomarkers were consistently associated with chronic bronchitis or COPD exacerbations. We identified one novel SNP (rs9302690 SNP) that was associated with CCL17 plasma measurements. Conclusion: When assessing smoking related pulmonary disease, biomarkers of inflammation such as IL-2, IL-6, IL-8, and eotaxin may add additional modest predictive value on top of clinical variables alone. Trial registration COPDGene (ClinicalTrials.gov Identifier: NCT02445183). Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) (ClinicalTrials.gov Identifier: NCT 01969344). Electronic supplementary material The online version of this article (10.1186/s12931-017-0662-2) contains supplementary material, which is available to authorized users

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 x 10(-13)) and African ancestries (rs2066702; P = 2.2 x 10(-9)). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.Peer reviewe