Description: Purpose: In many children with cancer and characteristics suggestive of a genetic predisposition syndrome, the genetic cause is still unknown. We studied the yield of pathogenic mutations by applying whole-exome sequencing on a selected cohort of children with cancer. Experimental Design: To identify mutations in known and novel cancer-predisposing genes, we performed trio-based whole-exome sequencing on germline DNA of 40 selected children and their parents. These children were diagnosed with cancer and had at least one of the following features: ( 1 ) intellectual disability and/or congenital anomalies, ( 2 ) multiple malignancies, ( 3 ) family history of cancer, or ( 4 ) an adult type of cancer. We first analyzed the sequence data for germline mutations in 146 known cancer-predisposing genes. If no causative mutation was found, the analysis was extended to the whole exome. Results: Four patients carried causative mutations in a known cancer-predisposing gene: TP53 and DICER1 ( n = 3). In another 4 patients, exome sequencing revealed mutations causing syndromes that might have contributed to the malignancy ( EP300 -based Rubinstein–Taybi syndrome, ARID1A -based Coffin–Siris syndrome, ACTB -based Baraitser–Winter syndrome, and EZH2 -based Weaver syndrome). In addition, we identified two genes, KDM3B and TYK2 , which are possibly involved in genetic cancer predisposition. Conclusions: In our selected cohort of patients, pathogenic germline mutations causative or likely causative of the cancer phenotype were found in 8 patients, and two possible novel cancer-predisposing genes were identified. Therewith, our study shows the added value of sequencing beyond a cancer gene panel in selected patients, to recognize childhood cancer predisposition. Clin Cancer Res; 24(7); 1594–603. ©2018 AACR .

Description: Molecular chaperones, also known as heat-shock proteins, refold misfolded proteins and help other proteins reach their native conformation. Thanks to these abilities, some chaperones, such as the Hsp90 protein or the chaperonin GroEL, can buffer the deleterious phenotypic effects of mutations that alter protein structure and function. Hsp70 chaperones use a chaperoning mechanism different from that of Hsp90 and GroEL, and it is not known whether they can also buffer mutations. Here, we show that they can. To this end, we performed a mutation accumulation experiment in Escherichia coli , followed by whole-genome resequencing. Overexpression of the Hsp70 chaperone DnaK helps cells cope with mutational load and completely avoid the extinctions we observe in lineages evolving without chaperone overproduction. Additionally, our sequence data show that DnaK overexpression increases mutational robustness, the tolerance of its clients to nonsynonymous nucleotide substitutions. We also show that this elevated mutational buffering translates into differences in evolutionary rates on intermediate and long evolutionary time scales. Specifically, we studied the evolutionary rates of DnaK clients using the genomes of E. coli , Salmonella enterica , and 83 other gamma-proteobacteria. We find that clients that interact strongly with DnaK evolve faster than weakly interacting clients. Our results imply that all three major chaperone classes can buffer mutations and affect protein evolution. They illustrate how an individual protein like a chaperone can have a disproportionate effect on the evolution of a proteome.

Description: The quasar mode of active galactic nuclei (AGN) in the high-redshift Universe is routinely observed in gas-rich galaxies together with large-scale AGN-driven winds. It is crucial to understand how photons emitted by the central AGN source couple to the ambient interstellar medium to trigger large-scale outflows. By means of radiation–hydrodynamical simulations of idealized galactic discs, we study the coupling of photons with the multiphase galactic gas, and how it varies with gas cloud sizes, and the radiation bands included in the simulations, which are ultraviolet, optical, and infrared (IR). We show how a quasar with a luminosity of 10 46 erg s – 1 can drive large-scale winds with velocities of $10^2\text{--}10^3 \, \rm km \, s^{-1}$ and mass outflow rates around 10 3 M yr – 1 for times of the order of a few million years. IR radiation is necessary to efficiently transfer momentum to the gas via multiscattering on dust in dense clouds. However, IR multiscattering, despite being extremely important at early times, quickly declines as the central gas cloud expands and breaks up, allowing the radiation to escape through low gas density channels. The typical number of multiscattering events for an IR photon is only about a quarter of the mean optical depth from the centre of the cloud. Our models account for the observed outflow rates of ~500–1000 M yr – 1 and high velocities of ~ 10 3 km s – 1 , favouring winds that are energy driven via extremely fast nuclear outflows, interpreted here as being IR radiatively driven winds.

Description: : A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data. Availability and implementation: VCF2Networks is available at https://bitbucket.org/dalloliogm/vcf2networks . Contact: giovanni.dallolio@kcl.ac.uk Supplementary information : Supplementary data are available at Bioinformatics online.

Description: For years, technological innovations have been the cause of controversy. In reaction to this, increasingly often the bodies responsible for implementing these innovations undertake social dialogue with stakeholders. An important environment for this is media discourse, which defines the problems and key actors and disseminates strategies for argumentation. Effective communication on public policies is one of the challenges in deliberative democracy. This paper aims to analyse the role of experts and knowledge in reference to the models of public communication on shale gas. Using a qualitative press analysis, an incoherence was observed in the understanding of knowledge and the profile of experts and the models of communication using them. The communication, which is rather oriented towards persuasion without legitimisation of scientific factual knowledge, fails. Reference in the discourse to the unknown or uncertain directs attention to the issues related to the strategic exploitation of nonknowledge.

Description: Background This investigator-initiated trial provided the justification for the phase III GRID study resulting in worldwide regulatory approval of regorafenib as a third-line therapy for patients with metastatic gastrointestinal stromal tumors (GIST). We report the genotype analyses, long-term safety, and activity results from this initial trial of regorafenib in GIST. Patients and methods The trial was conducted between February 2010 and January 2014, among adult patients with metastatic GIST, after failure of at least imatinib and sunitinib. Patients received regorafenib orally, 160 mg once daily, days 1–21 of a 28-day cycle. Clinical benefit rate (CBR), defined as complete or partial response (PR), or stable disease lasting ≥16 weeks per RECIST 1.1, progression-free survival (PFS), overall survival (OS), long-term safety data, and metabolic response by functional imaging were assessed. Results Thirty-three patients received at least one dose of regorafenib. The median follow-up was 41 months. CBR was documented in 25 of 33 patients [76%; 95% confidence interval (CI) 58% to 89%], including six PRs. The median PFS was 13.2 months (95% CI 9.2–18.3 months) including four patients who remained progression-free at study closure, each achieving clinical benefit for more than 3 years (range 36.8–43.5 months). The median OS was 25 months (95% CI 13.2–39.1 months). Patients whose tumors harbored a KIT exon 11 mutation demonstrated the longest median PFS (13.4 months), whereas patients with KIT/PDGFRA wild-type, non-SDH-deficient tumors experienced a median 1.6 months PFS ( P 〈 0.0001). Long-term safety profile is consistent with previous reports; hand–foot skin reaction and hypertension were the most common reasons for dose reduction. Notably, regorafenib induced objective responses and durable benefit in SDH-deficient GIST. Conclusions Long-term follow-up of patients with metastatic GIST treated with regorafenib suggests particular benefit among patients with primary KIT exon 11 mutations and those with SDH-deficient GIST. Dose modifications are frequently required to manage treatment-related toxicities. Clinical trial number NCT01068769.

Description: The Large Magellanic Cloud (LMC) harbours a rich and diverse system of star clusters, whose ages, chemical abundances and positions provide information about the LMC history of star formation. We use Science Verification imaging data from the Dark Energy Survey (DES) to increase the census of known star clusters in the outer LMC and to derive physical parameters for a large sample of such objects using a spatially and photometrically homogeneous data set. Our sample contains 255 visually identified cluster candidates, of which 109 were not listed in any previous catalogue. We quantify the crowding effect for the stellar sample produced by the DES Data Management pipeline and conclude that the stellar completeness is 〈10 per cent inside typical LMC cluster cores. We therefore reanalysed the DES co-add images around each candidate cluster and remeasured positions and magnitudes for their stars. We also implement a maximum-likelihood method to fit individual density profiles and colour–magnitude diagrams. For 117 (from a total of 255) of the cluster candidates (28 uncatalogued clusters), we obtain reliable ages, metallicities, distance moduli and structural parameters, confirming their nature as physical systems. The distribution of cluster metallicities shows a radial dependence, with no clusters more metal rich than [Fe/H] ~= –0.7 beyond 8 kpc from the LMC centre. The age distribution has two peaks at ~=1.2 and ~=2.7 Gyr.

Description: We present the results of 3D relativistic hydrodynamic simulations of interaction of active galactic nucleus jets with a dense turbulent two-phase interstellar medium, which would be typical of high-redshift galaxies. We describe the effect of the jet on the evolution of the density of the turbulent interstellar medium (ISM). The jet-driven energy bubble affects the gas to distances up to several kiloparsecs from the injection region. The shocks resulting from such interactions create a multiphase ISM and radial outflows. One of the striking result of this work is that low-power jets ( P jet 10 43 ergs –1 ), although less efficient in accelerating clouds, are trapped in the ISM for a longer time and hence affect the ISM over a larger volume. Jets of higher power drill through with relative ease. Although the relativistic jets launch strong outflows, there is little net mass ejection to very large distances, supporting a galactic fountain scenario for local feedback.

Description: The Drug–Gene Interaction Database (DGIdb, www.dgidb.org ) is a web resource that consolidates disparate data sources describing drug–gene interactions and gene druggability. It provides an intuitive graphical user interface and a documented application programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined information of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specifically, nine new sources of drug–gene interactions have been added, including seven resources specifically focused on interactions linked to clinical trials. These additions have more than doubled the overall count of drug–gene interactions. The total number of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Finally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search functionality. With these updates, DGIdb represents a comprehensive and user friendly tool for mining the druggable genome for precision medicine hypothesis generation.