113 research outputs found

    Solid-phase synthesis of duocarmycin analogues and the effect of C-terminal substitution on biological activity

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    YesThe duocarmycins are potent antitumour agents with potential in the development of antibody drug conjugates (ADCs) as well as being clinical candidates in their own right. In this paper, we describe the synthesis of a duocarmycin monomer (DSA) that is suitably protected for utilisation in solid phase synthesis. The synthesis was performed on a large scale and the resulting racemic protected Fmoc-DSA subunit was separated by supercritical fluid chromatography (SFC) into the single enantiomers. Application to solid phase synthesis methodology gave a series of monomeric and extended duocarmycin analogues with amino acid substituents. The DNA sequence selectivity was similar to previous reports for both the monomeric and extended compounds. The substitution at the C-terminus of the duocarmycin caused a decrease in antiproliferative activity for all of the compounds studied. An extended compound containing an alanine at the C-terminus was converted to the primary amide or to an extended structure containing a terminal tertiary amine but this had no beneficial effects on biological activity.MJS was funded by Novartis and UEA. We thank the EPSRC Mass Spectrometry Service, Swansea. We thank Richard Robinson and Julia Hatto at Novartis for help in the large scale synthesis

    Emergency admission predictive risk stratification models: assessment of implementation consequences (PRISMATIC 2): protocol for a mixed methods study.

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    Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of emergency hospital admission and can be used to support targeted approaches to improve care and reduce admissions. However, the impact of EARS is poorly understood and there may be unintended consequences. To assess effects, mechanisms, costs, and patient and healthcare professionals' views related to the introduction of EARS tools in England. Quasi-experimental mixed methods design using anonymised routine data and qualitative methods. We will apply multiple interrupted time series analysis to data, aggregated at former Clinical Commissioning Group level, to look at changes in emergency admission and other healthcare use following EARS introduction across England. We will investigate GP decision-making at practice level using linked general practice and secondary care data to compare case-mix, demographics, indicators of condition severity and frailty associated with emergency admissions before and after EARS introduction. We will undertake interviews ( ~48) with GPs and healthcare staff to understand how patient care may have changed. We will conduct focus groups ( =2) and interviews ( ~16) with patients to explore how they perceive that communication of individual risk scores might affect their experiences and health seeking behaviours. Findings will provide policymakers, healthcare professionals, and patients, with a better understanding of the effects, costs and stakeholder perspectives related to the introduction of EARS tools. [Abstract copyright: Copyright © 2024, The Authors.

    Structural analysis of pathogenic mutations in the DYRK1A gene in patients with developmental disorders.

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    Haploinsufficiency in DYRK1A is associated with a recognizable developmental syndrome, though the mechanism of action of pathogenic missense mutations is currently unclear. Here we present 19 de novo mutations in this gene, including five missense mutations, identified by the Deciphering Developmental Disorder study. Protein structural analysis reveals that the missense mutations are either close to the ATP or peptide binding-sites within the kinase domain, or are important for protein stability, suggesting they lead to a loss of the protein's function mechanism. Furthermore, there is some correlation between the magnitude of the change and the severity of the resultant phenotype. A comparison of the distribution of the pathogenic mutations along the length of DYRK1A with that of natural variants, as found in the ExAC database, confirms that mutations in the N-terminal end of the kinase domain are more disruptive of protein function. In particular, pathogenic mutations occur in significantly closer proximity to the ATP and the substrate peptide than the natural variants. Overall, we suggest that de novo dominant mutations in DYRK1A account for nearly 0.5% of severe developmental disorders due to substantially reduced kinase function

    Essential indicators for measuring site‐based conservation effectiveness in the post‐2020 global biodiversity framework

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    Abstract: Work on the post‐2020 global biodiversity framework is now well advanced and will outline a vision, goals, and targets for the next decade of biodiversity conservation and beyond. For the effectiveness of Protected areas and Other Effective area‐based Conservation Measures, an indicator has been proposed for “areas meeting their documented ecological objectives.” However, the Convention on Biological Diversity (CBD) has not identified or agreed on what data should inform this indicator. Here we draw on experiences from the assessment of protected area effectiveness in the CBD's previous strategic plan to provide recommendations on the essential elements related to biodiversity outcomes and management that need to be captured in this updated indicator as well as how this could be done. Our proposed protected area effectiveness indicators include a combination of remotely derived products for all protected areas, combined with data from monitoring of both protected area management and trends in species and ecosystems based on field observations. Additionally, we highlight the need for creating a digital infrastructure to operationalize national‐level data‐capture. We believe these steps are critical and urge the adoption of suitable protected area effectiveness indicators before the post‐2020 framework is agreed in 2021

    It could be a ‘Golden Goose’: a qualitative study of views in primary care on an emergency admission risk prediction tool prior to implementation

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    BACKGROUND: Rising demand for health care has prompted interest in new technologies to support a shift of care from hospital to community and primary care, which may require clinicians to undertake new working practices. A predictive risk stratification tool (Prism) was developed for use in primary care to estimate patients’ risk of an emergency hospital admission. As part of an evaluation of Prism, we aimed to understand what might be needed to bring Prism into effective use by exploring clinicians and practice managers’ attitudes and expectations about using it. We were informed by Normalisation Process Theory (NPT) which examines the work needed to bring an innovation into use. METHODS: We conducted 4 focus groups and 10 interviews with a total of 43 primary care doctors and colleagues from 32 general practices. All were recorded and transcribed. Analysis focussed in particular on the construct of ‘coherence’ within NPT, which examines how people understand an innovation and its purpose. RESULTS: Respondents were in agreement that Prism was a technological formalisation of existing practice, and that it would function as a support to clinical judgment, rather than replacing it. There was broad consensus about the role it might have in delivering new models of care based on active management, but there were doubts about the scope for making a difference to some patients and about whether Prism could identify at-risk patients not already known to the clinical team. Respondents did not expect using the tool to be onerous, but were concerned about the work which might follow in delivering care. Any potential value would not be of the tool in isolation, but would depend on the availability of support services. CONCLUSIONS: Policy imperatives and the pressure of rising demand meant respondents were open to trying out Prism, despite underlying uncertainty about what difference it could make. TRIAL REGISTRATION: Controlled Clinical Trials no. ISRCTN55538212

    Phenotypic spectrum and transcriptomic profile associated with germline variants in TRAF7

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    PURPOSE: Somatic variants in tumor necrosis factor receptor-associated factor 7 (TRAF7) cause meningioma, while germline variants have recently been identified in seven patients with developmental delay and cardiac, facial, and digital anomalies. We aimed to define the clinical and mutational spectrum associated with TRAF7 germline variants in a large series of patients, and to determine the molecular effects of the variants through transcriptomic analysis of patient fibroblasts. METHODS: We performed exome, targeted capture, and Sanger sequencing of patients with undiagnosed developmental disorders, in multiple independent diagnostic or research centers. Phenotypic and mutational comparisons were facilitated through data exchange platforms. Whole-transcriptome sequencing was performed on RNA from patient- and control-derived fibroblasts. RESULTS: We identified heterozygous missense variants in TRAF7 as the cause of a developmental delay-malformation syndrome in 45 patients. Major features include a recognizable facial gestalt (characterized in particular by blepharophimosis), short neck, pectus carinatum, digital deviations, and patent ductus arteriosus. Almost all variants occur in the WD40 repeats and most are recurrent. Several differentially expressed genes were identified in patient fibroblasts. CONCLUSION: We provide the first large-scale analysis of the clinical and mutational spectrum associated with the TRAF7 developmental syndrome, and we shed light on its molecular etiology through transcriptome studies

    Prevalence and architecture of de novo mutations in developmental disorders.

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    The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

    Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

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    Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype
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