DNA damage response activated by anti-cancer agent, irofulven

The DNA damage response is a complex network of signals that coordinate to protect cells from accumulating mutations that lead to the development of cancer. Upon the introduction of DNA damage from either environmental or endogenous sources, the DNA damage response coordinates the control of cell cycle with DNA repair mechanisms to ensure genomic integrity within the cell. Mutations in proteins in this pathway lead to genomic instability and early onset of cancer. BRCA1 is a protein that plays a critical role in response to DNA damage caused by ionizing radiation and is responsible for approximately 50% of inherited breast and ovarian cancers. A key element in the response to DNA damage is the exact type of lesion produced. Irofulven represents a novel DNA damaging agent that may provide insight into specific signals involved. It also remains to be determined if tumors that have mutations in BRCA1 may be more or less sensitive to treatment with irofulven. The exact method by which irofulven kills cells also remains to be determined. Many chemotherapeutics are potent inducers of apoptosis and irofulven has been shown to activate elements of the apoptotic pathway. Previous work in our lab has shown the ability of irofulven to activate ATM and CHK2. Based on the fact that BRCA1 lies directly downstream in this pathway, we hypothesized that it plays a key role in the irofulven induced DNA damage response.;In our current study, we determined that BRCA1 plays a role in regulation of S and G2/M cell cycle checkpoints after irofulven exposure. We also demonstrated that DNA repair via homologous recombination plays a role in response to DNA damage induced by irofulven and that cells deficient in such repair are more sensitive to irofulven. Lastly, we demonstrated that the activation of apoptosis by irofulven is regulated by caspases 2 and 9, while caspase 8 seems to render cells resistant. Taken together, this study expanded our knowledge of signaling pathways activated by irofulven and provides a basis for targeted treatment in BRCA1 deficient breast and ovarian cancers

Impact of human CA8 on thermal antinociception in relation to morphine equivalence in mice

Recently, we showed that murine dorsal root ganglion (DRG) Car8 expression is a cis-regulated eQTL that determines analgesic responses. In this report, we show that transduction through sciatic nerve injection of DRG with human wild-type carbonic anhydrase-8 using adeno-associated virus viral particles (AAV8-V5-CA8WT) produces analgesia in naive male C57BL/6J mice and antihyperalgesia after carrageenan treatment. A peak mean increase of about 4 s in thermal hindpaw withdrawal latency equaled increases in thermal withdrawal latency produced by 10 mg/kg intraperitoneal morphine in these mice. Allometric conversion of this intraperitoneal morphine dose in mice equals an oral morphine dose of about 146 mg in a 60-kg adult. Our work quantifies for the first time analgesia and antihyperalgesia in an inflammatory pain model after DRG transduction by CA8 gene therapy

Cosmology Without Averaging

We construct cosmological models consisting of large numbers of identical, regularly spaced masses. These models do not rely on any averaging procedures, or on the existence of a global Friedmann-Robertson-Walker (FRW) background. They are solutions of Einstein's equations up to higher order corrections in a perturbative expansion, and have large-scale dynamics that are well modelled by the Friedmann equation. We find that the existence of arbitrarily large density contrasts does not change either the magnitude or scale of the background expansion, at least when masses are regularly arranged, and up to the prescribed level of accuracy. We also find that while the local space-time geometry inside each cell can be described as linearly perturbed FRW, one could argue that a more natural description is that of perturbed Minkowski space (in which case the scalar perturbations are simply Newtonian potentials). We expect these models to be of use for understanding and testing ideas about averaging in cosmology, as well as clarifying the relationship between global cosmological dynamics and the static space-times associated with isolated masses.Comment: 24 pages, 3 figures. Corrected and expande

Implementation of U.K. Earth system models for CMIP6

We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere-land-ocean-sea ice model HadGEM3-GC3.1 and the Earth system model UKESM1 which adds a carbon-nitrogen cycle and atmospheric chemistry to HadGEM3-GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions.We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3-GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation.We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility

The functional "KL-VS" variant of KLOTHO is not associated with type 2 diabetes in 5028 UK Caucasians

BACKGROUND: Klotho has an important role in insulin signalling and the development of ageing-like phenotypes in mice. The common functional "KL-VS" variant in the KLOTHO (KL) gene is associated with longevity in humans but its role in type 2 diabetes is not known. We performed a large case-control and family-based study to test the hypothesis that KL-VS is associated with type 2 diabetes in a UK Caucasian population. METHODS: We genotyped 1793 cases, 1619 controls and 1616 subjects from 509 families for the single nucleotide polymorphism (SNP) F352V (rs9536314) that defines the KL-VS variant. Allele and genotype frequencies were compared between cases and controls. Family-based analysis was used to test for over- or under-transmission of V352 to affected offspring. RESULTS: Despite good power to detect odds ratios of 1.2, there were no significant associations between alleles or genotypes and type 2 diabetes (V352 allele: odds ratio = 0.96 (0.84–1.09)). Additional analysis of quantitative trait data in 1177 healthy control subjects showed no association of the variant with fasting insulin, glucose, triglycerides, HDL- or LDL-cholesterol (all P > 0.05). However, the HDL-cholesterol levels observed across the genotype groups showed a similar, but non-significant, pattern to previously reported data. CONCLUSION: This is the first large-scale study to examine the association between common functional variation in KL and type 2 diabetes risk. We have found no evidence that the functional KL-VS variant is a risk factor for type 2 diabetes in a large UK Caucasian case-control and family-based study

Target product profiles: tests for tuberculosis treatment monitoring and optimization

The World Health Organization has developed target product profiles containing minimum and optimum targets for key characteristics for tests for tuberculosis treatment monitoring and optimization. Tuberculosis treatment optimization refers to initiating or switching to an effective tuberculosis treatment regimen that results in a high likelihood of a good treatment outcome. The target product profiles also cover tests of cure conducted at the end of treatment. The development of the target product profiles was informed by a stakeholder survey, a cost-effectiveness analysis and a patient-care pathway analysis. Additional feedback from stakeholders was obtained by means of a Delphi-like process, a technical consultation and a call for public comment on a draft document. A scientific development group agreed on the final targets in a consensus meeting. For characteristics rated of highest importance, the document lists: (i) high diagnostic accuracy (sensitivity and specificity); (ii) time to result of optimally ≤ 2 hours and no more than 1 day; (iii) required sample type to be minimally invasive, easily obtainable, such as urine, breath, or capillary blood, or a respiratory sample that goes beyond sputum; (iv) ideally the test could be placed at a peripheral-level health facility without a laboratory; and (v) the test should be affordable to low- and middle-income countries, and allow wide and equitable access and scale-up. Use of these target product profiles should facilitate the development of new tuberculosis treatment monitoring and optimization tests that are accurate and accessible for all people being treated for tuberculosis

Integrated Approach Reveals Role of Mitochondrial Germ-Line Mutation F18L in Respiratory Chain, Oxidative Alterations, Drug Sensitivity, and Patient Prognosis in Glioblastoma

Glioblastoma is the most common and malignant primary brain tumour in adults, with a dismal prognosis. This is partly due to considerable inter- and intra-tumour heterogeneity. Changes in the cellular energy-producing mitochondrial respiratory chain complex (MRC) activities are a hallmark of glioblastoma relative to the normal brain, and associate with differential survival outcomes. Targeting MRC complexes with drugs can also facilitate anti-glioblastoma activity. Whether mutations in the mitochondrial DNA (mtDNA) that encode several components of the MRC contribute to these phenomena remains underexplored. We identified a germ-line mtDNA mutation (m. 14798T > C), enriched in glioblastoma relative to healthy controls, that causes an amino acid substitution F18L within the core mtDNA-encoded cytochrome b subunit of MRC complex III. F18L is predicted to alter corresponding complex III activity, and sensitivity to complex III-targeting drugs. This could in turn alter reactive oxygen species (ROS) production, cell behaviour and, consequently, patient outcomes. Here we show that, despite a heterogeneous mitochondrial background in adult glioblastoma patient biopsy-derived cell cultures, the F18L substitution associates with alterations in individual MRC complex activities, in particular a 75% increase in MRC complex II_III activity, and a 34% reduction in CoQ10, the natural substrate for MRC complex III, levels. Downstream characterisation of an F18L-carrier revealed an 87% increase in intra-cellular ROS, an altered cellular distribution of mitochondrial-specific ROS, and a 64% increased sensitivity to clomipramine, a repurposed MRC complex III-targeting drug. In patients, F18L-carriers that received the current standard of care treatment had a poorer prognosis than non-carriers (373 days vs. 415 days, respectively). Single germ-line mitochondrial mutations could predispose individuals to differential prognoses, and sensitivity to mitochondrial targeted drugs. Thus, F18L, which is present in blood could serve as a useful non-invasive biomarker for the stratification of patients into prognostically relevant groups, one of which requires a lower dose of clomipramine to achieve clinical effect, thus minimising side-effects

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease