134 research outputs found

    Defective mitochondrial peroxiredoxin-3 results in sensitivity to oxidative stress in Fanconi anemia

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    Cells from patients with Fanconi anemia (FA), an inherited disorder that includes bone marrow failure and cancer predisposition, have increased sensitivity to oxidative stress through an unknown mechanism. We demonstrate that the FA group G (FANCG) protein is found in mitochondria. Wild-type but not G546R mutant FANCG physically interacts with the mitochondrial peroxidase peroxiredoxin-3 (PRDX3). PRDX3 is deregulated in FA cells, including cleavage by a calpainlike cysteine protease and mislocalization. FA-G cells demonstrate distorted mitochondrial structures, and mitochondrial extracts have a sevenfold decrease in thioredoxin-dependent peroxidase activity. Transient overexpression of PRDX3 suppresses the sensitivity of FA-G cells to H2O2, and decreased PRDX3 expression increases sensitivity to mitomycin C. Cells from the FA-A and -C subtypes also have PRDX3 cleavage and decreased peroxidase activity. This study demonstrates a role for the FA proteins in mitochondria witsh sensitivity to oxidative stress resulting from diminished peroxidase activity. These defects may lead to apoptosis and the accumulation of oxidative DNA damage in bone marrow precursors

    Identifying gene disruptions in novel balanced de novo constitutional translocations in childhood cancer patients by whole-genome sequencing

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    PurposeWe applied whole genome sequencing to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations, to discover novel genic disruptions.MethodsWe applied SV calling programs CREST, Break Dancer, SV-STAT and CGAP-CNV, and developed an annotative filtering strategy to achieve nucleotide resolution at the translocations.ResultsWe identified the breakpoints for t(6;12) (p21.1;q24.31) disrupting HNF1A in a patient diagnosed with hepatic adenomas and Maturity Onset Diabetes of the Young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin’s lymphoma and subsequent low-grade glioma, we identified t(5;18) (q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma.ConclusionsThese examples suggest that implementing clinical whole genome sequencing in the diagnostic work-up of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype

    a report from the Children's Oncology Group and the Utah Population Database

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    Relatively little is known about the epidemiology and factors underlying susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case–control study of RMS and the Utah Population Database (UPDB). RMS cases (n = 322) were obtained from the Children's Oncology Group (COG). Population-based controls (n = 322) were pair-matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate the association between family history of cancer and childhood RMS. The results were validated using the UPDB, from which 130 RMS cases were identified and matched to controls (n = 1300) on sex and year of birth. The results were combined to generate summary odds ratios (ORs) and 95% confidence intervals (CI). Having a first-degree relative with a cancer history was more common in RMS cases than controls (ORs = 1.39, 95% CI: 0.97–1.98). Notably, this association was stronger among those with embryonal RMS (ORs = 2.44, 95% CI: 1.54–3.86). Moreover, having a first-degree relative who was younger at diagnosis of cancer (<30 years) was associated with a greater risk of RMS (ORs = 2.37, 95% CI: 1.34–4.18). In the largest analysis of its kind, we found that most children diagnosed with RMS did not have a family history of cancer. However, our results indicate an increased risk of RMS (particularly embryonal RMS) in children who have a first-degree relative with cancer, and among those whose relatives were diagnosed with cancer at <30 years of age

    MODEL PENGELOLAAN PASCA TANGKAP SEBAGAI UPAYA PENGENTASAN KEMISKINAN MASYARAKAT KAMPUNG NELAYAN DI PULAU ENGGANO

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    Relatively little is known about the epidemiology and factors underlying susceptibility to childhood rhabdomyosarcoma (RMS). To better characterize genetic susceptibility to childhood RMS, we evaluated the role of family history of cancer using data from the largest case-control study of RMS and the Utah Population Database (UPDB). RMS cases (n=322) were obtained from the Children's Oncology Group (COG). Population-based controls (n=322) were pair-matched to cases on race, sex, and age. Conditional logistic regression was used to evaluate the association between family history of cancer and childhood RMS. The results were validated using the UPDB, from which 130 RMS cases were identified and matched to controls (n=1300) on sex and year of birth. The results were combined to generate summary odds ratios (ORs) and 95% confidence intervals (CI). Having a first-degree relative with a cancer history was more common in RMS cases than controls (ORs=1.39, 95% CI: 0.97-1.98). Notably, this association was stronger among those with embryonal RMS (ORs=2.44, 95% CI: 1.54-3.86). Moreover, having a first-degree relative who was younger at diagnosis of cancer (&lt;30years) was associated with a greater risk of RMS (ORs=2.37, 95% CI: 1.34-4.18). In the largest analysis of its kind, we found that most children diagnosed with RMS did not have a family history of cancer. However, our results indicate an increased risk of RMS (particularly embryonal RMS) in children who have a first-degree relative with cancer, and among those whose relatives were diagnosed with cancer at &lt;30years of age

    A survey of informatics approaches to whole-exome and whole-genome clinical reporting in the electronic health record

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    Genome-scale clinical sequencing is being adopted more broadly in medical practice. The National Institutes of Health developed the Clinical Sequencing Exploratory Research (CSER) program to guide implementation and dissemination of best practices for the integration of sequencing into clinical care. This study describes and compares the state of the art of incorporating whole-exome and whole-genome sequencing results into the electronic health record, including approaches to decision support across the six current CSER sites

    Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource

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    Supplemental Data Supplemental Data include 65 figures and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2017.04.015. Supplemental Data Document S1. Figures S1–S65 Download Document S2. Article plus Supplemental Data Download Web Resources ClinGen, https://www.clinicalgenome.org/ ClinGen Gene Curation, https://www.clinicalgenome.org/working-groups/gene-curation/ ClinGen Gene Curation SOP, https://www.clinicalgenome.org/working-groups/gene-curation/projects-initiatives/gene-disease-clinical-validity-sop/ ClinGen Knowledge Base, https://search.clinicalgenome.org/kb/agents/sign_up OMIM, http://www.omim.org/ Orphanet, http://www.orpha.net/consor/cgi-bin/index.php With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: “Definitive,” “Strong,” “Moderate,” “Limited,” “No Reported Evidence,” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings

    Long-term risk of medical conditions associated with breast cancer treatment

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    Early and late effects of cancer treatment are of increasing concern with growing survivor populations, but relevant data are sparse. We sought to determine the prevalence and hazard ratio of such effects in breast cancer cases
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