Predominance of null mutations in ataxia-telangiectasia

Ataxia-telangiectasia (A-T) is an autosomal recessive disorder involving cerebellar degeneration, immunodeficiency, chromosomal instability, radiosensitivity and cancer predisposition. The responsible gene, ATM, was recently identified by positional cloning and found to encode a putative 350 kDa protein with a PI 3-kinase-like domain, presumably involved in mediating cell cycle arrest in response to radiation-induced DNA damage. The nature and location of A-T mutations should provide insight into the function of the ATM protein and the molecular basis of this pleiotropic disease. Of 44 A-T mutations identified by us to date, 39 (89%) are expected to inactivate the ATM protein by truncating it, by abolishing correct initiation or termination of translation, or by deleting large segments. Additional mutations are four smaller in-frame deletions and insertions, and one substitution of a highly conserved amino acid at the PI 3-kinase domain. The emerging profile of mutations causing A-T is thus dominated by those expected to completely inactivate the ATM protein. ATM mutations with milder effects may result in phenotypes related, but not identical, to A-T

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells

ATAD5 promotes replication restart by regulating RAD51 and PCNA in response to replication stress

Maintaining stability of replication forks is important for genomic integrity. However, it is not clear how replisome proteins contribute to fork stability under replication stress. Here, we report that ATAD5, a PCNA unloader, plays multiple functions at stalled forks including promoting its restart. ATAD5 depletion increases genomic instability upon hydroxyurea treatment in cultured cells and mice. ATAD5 recruits RAD51 to stalled forks in an ATR kinase-dependent manner by hydroxyurea-enhanced protein-protein interactions and timely removes PCNA from stalled forks for RAD51 recruitment. Consistent with the role of RAD51 in fork regression, ATAD5 depletion inhibits slowdown of fork progression and native 5-bromo-2??-deoxyuridine signal induced by hydroxyurea. Single-molecule FRET showed that PCNA itself acts as a mechanical barrier to fork regression. Consequently, DNA breaks required for fork restart are reduced by ATAD5 depletion. Collectively, our results suggest an important role of ATAD5 in maintaining genome integrity during replication stress

Biology of moderately halophilic aerobic bacteria

The moderately halophilic heterotrophic aerobic bacteria form a diverse group of microorganisms. The property of halophilism is widespread within the bacterial domain. Bacterial halophiles are abundant in environments such as salt lakes, saline soils, and salted food products. Most species keep their intracellular ionic concentrations at low levels while synthesizing or accumulating organic solutes to provide osmotic equilibrium of the cytoplasm with the surrounding medium. Complex mechanisms of adjustment of the intracellular environments and the properties of the cytoplasmic membrane enable rapid adaptation to changes in the salt concentration of the environment. Approaches to the study of genetic processes have recently been developed for several moderate halophiles, opening the way toward an understanding of haloadaptation at the molecular level. The new information obtained is also expected to contribute to the development of novel biotechnological uses for these organisms

Mining social mixing patterns for infectious disease models based on a two-day population survey in Belgium

<p>Abstract</p> <p>Background</p> <p>Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts.</p> <p>Methods</p> <p>Participants kept a paper diary with information on their contacts over two different days. A contact was defined as a two-way conversation of at least three words in each others proximity. The contact information included the age of the contact, gender, location, duration, frequency, and whether or not touching was involved.</p> <p>For data analysis, we used association rules and classification trees. Weighted generalized estimating equations were used to analyze contact frequency while accounting for the correlation between contacts reported on the two different days.</p> <p>A contact surface, expressing the average number of contacts between persons of different ages was obtained by a bivariate smoothing approach and the relation to the so-called next-generation matrix was established.</p> <p>Results</p> <p>People mostly mixed with people of similar age, or with their offspring, their parents and their grandparents. By imputing professional contacts, the average number of daily contacts increased from 11.84 to 15.70. The number of reported contacts depended heavily on the household size, class size for children and number of professional contacts for adults. Adults living with children had on average 2 daily contacts more than adults living without children. In the holiday period, the daily contact frequency for children and adolescents decreased with about 19% while a similar observation is made for adults in the weekend. These findings can be used to estimate the impact of school closure.</p> <p>Conclusion</p> <p>We conducted a diary based contact survey in Belgium to gain insights in social interactions relevant to the spread of infectious diseases. The resulting contact patterns are useful to improve estimating crucial parameters for infectious disease transmission models.</p

Bayesian fractional polynomials

This paper sets out to implement the Bayesian paradigm for fractional polynomial models under the assumption of normally distributed error terms. Fractional polynomials widen the class of ordinary polynomials and offer an additive and transportable modelling approach. The methodology is based on a Bayesian linear model with a quasi-default hyper-g prior and combines variable selection with parametric modelling of additive effects. A Markov chain Monte Carlo algorithm for the exploration of the model space is presented. This theoretically well-founded stochastic search constitutes a substantial improvement to ad hoc stepwise procedures for the fitting of fractional polynomial models. The method is applied to a data set on the relationship between ozone levels and meteorological parameters, previously analysed in the literature

Differential early onset of therapeutic response with risperidone vs conventional antipsychotics in patients with chronic schizophrenia

The present post-hoc analysis investigated the speed of onset of therapeutic effect of the atypical antipsychotic, risperidone, in direct comparison with conventional antipsychotics. Data were pooled from four double-blind active comparator-control led clinical trials involving 757 patients with schizophrenia treated for up to 8 weeks with either risperidone (4-6 mg/day) or a conventional antipsychotic such as haloperidol (110 or 20 mg/day), perphenazine (mean dose 28mg/day), or zuclopenthixol (mean dose 38 mg/day). Primary outcome was assessed using the Positive and Negative Syndrome Scale. A significantly greater proportion of patients treated with risperidone achieved >= 20% reduction from baseline Positive and Negative Syndrome Scale total score at weeks 1, 2, 6, and at end point (last observation carried forward: P <= 0.04). A significant difference exists in mean reduction from baseline to end point in Positive and Negative Syndrome Scale total scores in favor of patients treated with risperidone compared with those treated with conventional antipsychotics (-18.4 vs -13.5; P=0.0013). The mean time to response was 23.8 days with risperidone and 28.2 days with conventional drugs (hazard ratio 1.3; 95% confidence interval 1.1-1.5). These findings are clinically relevant because the faster onset of therapeutic effect with atypical antipsychotics can be important in the acute setting and have a considerable impact on healthcare systems

Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R: Order Restricted Analysis of Microarray Data

This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students

Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R: Order Restricted Analysis of Microarray Data

This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students