IMPORTANCE New treatments are needed to improve the prognosis of patients with recurrent high-grade glioma.OBJECTIVE To compare overall survival for patients receiving tumor resection followed by vocimagene amiretrorepvec (Toca 511) with flucytosine (Toca FC) vs standard of care (SOC). DESIGN, SETTING, AND PARTICIPANTSA randomized, open-label phase 2/3 trial (TOCA 5) in 58 centers in the US, Canada, Israel, and South Korea, comparing posttumor resection treatment with Toca 511 followed by Toca FC vs a defined single choice of approved (SOC) therapies was conducted from November 30, 2015, to December 20, 2019. Patients received tumor resection for first or second recurrence of glioblastoma or anaplastic astrocytoma.INTERVENTIONS Patients were randomized 1:1 to receive Toca 511/FC (n = 201) or SOC control (n = 202). For the Toca 511/FC group, patients received Toca 511 injected into the resection cavity wall at the time of surgery, followed by cycles of oral Toca FC 6 weeks after surgery. For the SOC control group, patients received investigators' choice of single therapy: lomustine, temozolomide, or bevacizumab. MAIN OUTCOMES AND MEASURESThe primary outcome was overall survival (OS) in time from randomization date to death due to any cause. Secondary outcomes reported in this study included safety, durable response rate (DRR), duration of DRR, durable clinical benefit rate, OS and DRR by IDH1 variant status, and 12-month OS. RESULTSAll 403 randomized patients (median [SD] age: 56 [11.46] years; 62.5% [252] men) were included in the efficacy analysis, and 400 patients were included in the safety analysis (3 patients on the SOC group did not receive resection). Final analysis included 271 deaths (141 deaths in the Toca 511/FC group and 130 deaths in the SOC control group). The median follow-up was 22.8 months. The median OS was 11.10 months for the Toca 511/FC group and 12.22 months for the control group (hazard ratio, 1.06; 95% CI 0.83, 1.35; P = .62). The secondary end points did not demonstrate statistically significant differences. The rates of adverse events were similar in the Toca 511/FC group and the SOC control group.CONCLUSIONS AND RELEVANCE Among patients who underwent tumor resection for first or second recurrence of glioblastoma or anaplastic astrocytoma, administration of Toca 511 and Toca FC, compared with SOC, did not improve overall survival or other efficacy end points.

Bipolar disorder is a common, complex, and severe psychiatric disorder with cyclical disturbances of mood and a high suicide rate. Here, we describe a family with four siblings, three affected females and one unaffected male. The disease course was characterized by early-onset bipolar disorder and co-morbid anxiety spectrum disorders that followed the onset of bipolar disorder. Genetic risk factors were suggested by the early onset of the disease, the severe disease course, including multiple suicide attempts, and lack of adverse prenatal or early life events. In particular, drug and alcohol abuse did not contribute to the disease onset. Exome sequencing identified very rare, heterozygous, and likely protein-damaging variants in eight brain-expressed genes: IQUB, JMJD1C, GADD45A, GOLGB1, PLSCR5, VRK2, MESDC2, and FGGY. The variants were shared among all three affected family members but absent in the unaffected sibling and in more than 200 controls. The genes encode proteins with significant regulatory roles in the ERK/MAPK and CREB-regulated intracellular signaling pathways. These pathways are central to neuronal and synaptic plasticity, cognition, affect regulation and response to chronic stress. In addition, proteins in these pathways are the target of commonly used mood-stabilizing drugs, such as tricyclic antidepressants, lithium, and valproic acid. The combination of multiple rare, damaging mutations in these central pathways could lead to reduced resilience and increased vulnerability to stressful life events. Our results support a new model for psychiatric disorders, in which multiple rare, damaging mutations in genes functionally related to a common signaling pathway contribute to the manifestation of bipolar disorder.

High-throughput DNA sequencing has become a mainstay for the discovery of genomic variants that may cause disease or affect phenotype. A next-generation sequencing pipeline typically identifies thousands of variants in each sample. A particular challenge is the annotation of each variant in a way that is useful to downstream consumers of the data, such as clinical sequencing centers or researchers. These users may require that all data storage and analysis remain on secure local servers to protect patient confidentiality or intellectual property, may have unique and changing needs to draw on a variety of annotation data sets and may prefer not to rely on closed-source applications beyond their control. Here we describe scalable methods for using the plugin capability of the Ensembl Variant Effect Predictor to enrich its basic set of variant annotations with additional data on genes, function, conservation, expression, diseases, pathways and protein structure, and describe an extensible framework for easily adding additional custom data sets.

BackgroundWhen growing budding yeast under continuous, nutrient-limited conditions, over half of yeast genes exhibit periodic expression patterns. Periodicity can also be observed in respiration, in the timing of cell division, as well as in various metabolite levels. Knowing the transcription factors involved in the yeast metabolic cycle is helpful for determining the cascade of regulatory events that cause these patterns.ResultsTranscription factor activities were estimated by linear regression using time series and genome-wide transcription factor binding data. Time-translation matrices were estimated using least squares and were used to model the interactions between the most significant transcription factors. The top transcription factors have functions involving respiration, cell cycle events, amino acid metabolism and glycolysis. Key regulators of transitions between phases of the yeast metabolic cycle appear to be Hap1, Hap4, Gcn4, Msn4, Swi6 and Adr1.ConclusionsAnalysis of the phases at which transcription factor activities peak supports previous findings suggesting that the various cellular functions occur during specific phases of the yeast metabolic cycle.

BackgroundWith the expanding use of next-gen sequencing (NGS) to diagnose the thousands of rare Mendelian genetic diseases, it is critical to be able to interpret individual DNA variation. To calculate the significance of finding a rare protein-altering variant in a given gene, one must know the frequency of seeing a variant in the general population that is at least as damaging as the variant in question.MethodsWe developed a general method to better interpret the likelihood that a rare variant is disease causing if observed in a given gene or genic region mapping to a described protein domain, using genome-wide information from a large control sample. Based on data from 2504 individuals in the 1000 Genomes Project dataset, we calculated the number of individuals who have a rare variant in a given gene for numerous filtering threshold scenarios, which may be used for calculating the significance of an observed rare variant being causal for disease. Additionally, we calculated mutational burden data on the number of individuals with rare variants in genic regions mapping to protein domains.ResultsWe describe methods to use the mutational burden data for calculating the significance of observing rare variants in a given proportion of sequenced individuals. We present SORVA, an implementation of these methods as a web tool, and we demonstrate application to 20 relevant but diverse next-gen sequencing studies. Specifically, we calculate the statistical significance of findings involving multi-family studies with rare Mendelian disease and a large-scale study of a complex disorder, autism spectrum disorder. If we use the frequency counts to rank genes based on intolerance for variation, the ranking correlates well with pLI scores derived from the Exome Aggregation Consortium (ExAC) dataset (ρ = 0.515), with the benefit that the scores are directly interpretable.ConclusionsWe have presented a strategy that is useful for vetting candidate genes from NGS studies and allows researchers to calculate the significance of seeing a variant in a given gene or protein domain. This approach is an important step towards developing a quantitative, statistics-based approach for presenting clinical findings.Electronic supplementary materialThe online version of this article (10.1186/s12920-018-0371-9) contains supplementary material, which is available to authorized users.