487 research outputs found

    A clinical tool for predicting survival in ALS

    Get PDF
    Background: Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. Methods: 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Findings: Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. Interpretation: A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors

    Maximising response to postal questionnaires – A systematic review of randomised trials in health research

    Get PDF
    Background Postal self-completion questionnaires offer one of the least expensive modes of collecting patient based outcomes in health care research. The purpose of this review is to assess the efficacy of methods of increasing response to postal questionnaires in health care studies on patient populations. Methods The following databases were searched: Medline, Embase, CENTRAL, CDSR, PsycINFO, NRR and ZETOC. Reference lists of relevant reviews and relevant journals were hand searched. Inclusion criteria were randomised trials of strategies to improve questionnaire response in health care research on patient populations. Response rate was defined as the percentage of questionnaires returned after all follow-up efforts. Study quality was assessed by two independent reviewers. The Mantel-Haenszel method was used to calculate the pooled odds ratios. Results Thirteen studies reporting fifteen trials were included. Implementation of reminder letters and telephone contact had the most significant effect on response rates (odds ratio 3.7, 95% confidence interval 2.30 to 5.97 p = <0.00001). Shorter questionnaires also improved response rates to a lesser degree (odds ratio 1.4, 95% confidence interval 1.19 to 1.54). No evidence was found that incentives, re-ordering of questions or including an information brochure with the questionnaire confer any additional advantage. Conclusion Implementing repeat mailing strategies and/or telephone reminders may improve response to postal questionnaires in health care research. Making the questionnaire shorter may also improve response rates. There is a lack of evidence to suggest that incentives are useful. In the context of health care research all strategies to improve response to postal questionnaires require further evaluation

    Loss of synergistic transcriptional feedback loops drives diverse B-cell cancers

    Get PDF
    BACKGROUND: The most common B-cell cancers, chronic lymphocytic leukemia/lymphoma (CLL), follicular and diffuse large B-cell (FL, DLBCL) lymphomas, have distinct clinical courses, yet overlapping cell-of-origin . Dynamic changes to the epigenome are essential regulators of B-cell differentiation. Therefore, we reasoned that these distinct cancers may be driven by shared mechanisms of disruption in transcriptional circuitry. METHODS: We compared purified malignant B-cells from 52 patients with normal B-cell subsets (germinal center centrocytes and centroblasts, naïve and memory B-cells) from 36 donor tonsils using \u3e325 high-resolution molecular profiling assays for histone modifications, open chromatin (ChIP-, FAIRE-seq), transcriptome (RNA-seq), transcription factor (TF) binding, and genome copy number (microarrays). FINDINGS: From the resulting data, we identified gains in active chromatin in enhancers/super-enhancers that likely promote unchecked B-cell receptor signaling, including one we validated near the immunoglobulin superfamily receptors FCMR and PIGR. More striking and pervasive was the profound loss of key B-cell identity TFs, tumor suppressors and their super-enhancers, including EBF1, OCT2(POU2F2), and RUNX3. Using a novel approach to identify transcriptional feedback, we showed that these core transcriptional circuitries are self-regulating. Their selective gain and loss form a complex, iterative, and interactive process that likely curbs B-cell maturation and spurs proliferation. INTERPRETATION: Our study is the first to map the transcriptional circuitry of the most common blood cancers. We demonstrate that a critical subset of B-cell TFs and their cognate enhancers form self-regulatory transcriptional feedback loops whose disruption is a shared mechanism underlying these diverse subtypes of B-cell lymphoma. FUNDING: National Institute of Health, Siteman Cancer Center, Barnes-Jewish Hospital Foundation, Doris Duke Foundation

    The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes

    Get PDF
    The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.The METABRIC project was funded by Cancer Research UK, the British Columbia Cancer Foundation and Canadian Breast Cancer Foundation BC/Yukon. This sequencing project was funded by CRUK grant C507/A16278 and Illumina UK performed all the sequencing. The authors also acknowledge the support of the University of Cambridge, Hutchinson Whampoa, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre, the Centre for Translational Genomics (CTAG) Vancouver and the BCCA Breast Cancer Outcomes Unit. We thank the Genomics, Histopathology, and Biorepository Core Facilities at the Cancer Research UK Cambridge Institute, and the Addenbrooke’s Human Research Tissue Bank (supported by the National Institute for Health Research Cambridge Biomedical Research Centre).This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1147

    Crystallographic and cellular characterisation of two mechanisms stabilising the native fold of α1-Antitrypsin: implications for disease and drug design

    Get PDF
    The common Z mutant (Glu342Lys) of α1-antitrypsin results in the formation of polymers that are retained within hepatocytes. This causes liver disease whilst the plasma deficiency of an important proteinase inhibitor predisposes to emphysema. The Thr114Phe and Gly117Phe mutations border a surface cavity identified as a target for rational drug design. These mutations preserve inhibitory activity but reduce the polymerisation of wild-type native α1-antitrypsin in vitro and increase secretion in a Xenopus oocyte model of disease. To understand these effects, we have crystallised both mutants and solved their structures. The 2.2 Å structure of Thr114Phe α1-antitrypsin demonstrates that the effects of the mutation are mediated entirely by well-defined partial cavity blockade and allows in silico screening of fragments capable of mimicking the effects of the mutation. The Gly117Phe mutation operates differently, repacking aromatic side chains in the helix F–β-sheet A interface to induce a half-turn downward shift of the adjacent F helix. We have further characterised the effects of these two mutations in combination with the Z mutation in a eukaryotic cell model of disease. Both mutations increase the secretion of Z α1-antitrypsin in the native conformation, but the double mutants remain more polymerogenic than the wild-type (M) protein. Taken together, these data support different mechanisms by which the Thr114Phe and Gly117Phe mutations stabilise the native fold of α1-antitrypsin and increase secretion of monomeric protein in cell models of disease

    A chemical survey of exoplanets with ARIEL

    Get PDF
    Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

    Get PDF
    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

    Get PDF
    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN
    corecore