The Oncoprotein EVI1 and the DNA Methyltransferase Dnmt3 Co-Operate in Binding and De Novo Methylation of Target DNA

EVI1 has pleiotropic functions during murine embryogenesis and its targeted disruption leads to prenatal death by severely affecting the development of virtually all embryonic organs. However, its functions in adult tissues are still unclear. When inappropriately expressed, EVI1 becomes one of the most aggressive oncogenes associated with human hematopoietic and solid cancers. The mechanisms by which EVI1 transforms normal cells are unknown, but we showed recently that EVI1 indirectly upregulates self-renewal and cell-cycling genes by inappropriate methylation of CpG dinucleotides in the regulatory regions of microRNA-124-3 (miR-124-3), leading to the repression of this small gene that controls normal differentiation and cell cycling of somatic cells. We used the regulatory regions of miR-124-3 as a read-out system to investigate how EVI1 induces de novo methylation of DNA. Here we show that EVI1 physically interacts with DNA methyltransferases 3a and 3b (Dnmt3a/b), which are the only de novo DNA methyltransferases identified to date in mouse and man, and that it forms an enzymatically active protein complex that induces de novo DNA methylation in vitro. This protein complex targets and binds to a precise region of miR-124-3 that is necessary for repression of a reporter gene by EVI1. Based on our findings, we propose that in cooperation with Dnmt3a/b EVI1 regulates the methylation of DNA as a sequence-specific mediator of de novo DNA methylation and that inappropriate EVI1 expression contributes to carcinogenesis through improper DNA methylation

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.ABCFS: The Australian Breast Cancer Family Registry (ABCFR; 1992-1995) was supported by the Australian NHMRC, the New South Wales Cancer Council, and the Victorian Health Promotion Foundation (Australia), and by grant UM1CA164920 from the USA National Cancer Institute. The Genetic Epidemiology Laboratory at the University of Melbourne has also received generous support from Mr B. Hovey and Dr and Mrs R.W. Brown to whom we are most grateful. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Breast Cancer Susceptibility Variants and Mammographic Density 5 Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. BBCC: This study was funded in part by the ELAN-Program of the University Hospital Erlangen; Katharina Heusinger was funded by the ELAN program of the University Hospital Erlangen. BBCC was supported in part by the ELAN program of the Medical Faculty, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg. EPIC-Norfolk: This study was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. MCBCS: This study was supported by Public Health Service Grants P50 CA 116201, R01 CA 128931, R01 CA 128931-S01, R01 CA 122340, CCSG P30 CA15083, from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. MCCS: Melissa C. Southey is a National Health and Medical Research Council Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The study was supported by the Cancer Council of Victoria and by the Victorian Breast Cancer Research Consortium. MEC: National Cancer Institute: R37CA054281, R01CA063464, R01CA085265, R25CA090956, R01CA132839. MMHS: This work was supported by grants from the National Cancer Institute, National Institutes of Health, and Department of Health and Human Services. (R01 CA128931, R01 CA 128931-S01, R01 CA97396, P50 CA116201, and Cancer Center Support Grant P30 CA15083). Breast Cancer Susceptibility Variants and Mammographic Density 6 NBCS: This study has been supported with grants from Norwegian Research Council (#183621/S10 and #175240/S10), The Norwegian Cancer Society (PK80108002, PK60287003), and The Radium Hospital Foundation as well as S-02036 from South Eastern Norway Regional Health Authority. NHS: This study was supported by Public Health Service Grants CA131332, CA087969, CA089393, CA049449, CA98233, CA128931, CA 116201, CA 122340 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. OOA study was supported by CA122822 and X01 HG005954 from the NIH; Breast Cancer Research Fund; Elizabeth C. Crosby Research Award, Gladys E. Davis Endowed Fund, and the Office of the Vice President for Research at the University of Michigan. Genotyping services for the OOA study were provided by the Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096. OFBCR: This work was supported by grant UM1 CA164920 from the USA National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. SASBAC: The SASBAC study was supported by Märit and Hans Rausing’s Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Breast Cancer Susceptibility Variants and Mammographic Density 7 SIBS: SIBS was supported by program grant C1287/A10118 and project grants from Cancer Research UK (grant numbers C1287/8459). COGS grant: Collaborative Oncological Gene-environment Study (COGS) that enabled the genotyping for this study. Funding for the BCAC component is provided by grants from the EU FP7 programme (COGS) and from Cancer Research UK. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post- Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAMEON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.This is the author accepted manuscript. The final version is available via American Association for Cancer Research at http://cancerres.aacrjournals.org/content/early/2015/04/10/0008-5472.CAN-14-2012.abstract

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations

The uses of Chrysomya megacephala (Fabricius, 1794)(Diptera: Calliphoridae) in forensic entomology:

Chrysomya megacephala (Fabricius, 1794) occurs on every continent and is closely associated with carrion and decaying material in human environments. Its abilities to find dead bodies and carry pathogens give it a prominence in human affairs that may involve prosecution or litigation, and therefore forensic entomologists. The identification, geographical distribution and biology of the species are reviewed to provide a background for approaches that four branches of forensic entomology (urban, stored-product, medico-criminal and environmental) might take to investigations involving this fly

Treosulfan Exposure Predicts Thalassemia-free Survival In Patients With Beta Thalassemia Major (TM) Undergoing Allogeneic Hematopoietic Cell Transplantation

A toxicity-reduced conditioning regimen with Treosulfan, Fludarabine, and Thiotepa in patients with high-risk β- thalassemia major has significantly improved HCT outcomes. However, complications resulting from regimen-related toxicities (RRTs), mixed chimerism, and graft rejection remain a challenge. We evaluated the dose-exposure-response relationship of Treosulfan and its active metabolite S, S-EBDM, in a uniform cohort of patients with β-thalassemia major to identify whether therapeutic drug monitoring (TDM) and dose adjustment of Treosulfan is feasible. Plasma Treosulfan/S, S-EBDM levels were measured in seventy-seven patients using a validated LC-MS/MS method, and the PK parameters were estimated using nlmixr2. The influence of Treosulfan & S, S-EBDM exposure, and GSTA1/NQO1 polymorphisms on graft rejection, RRTs, chimerism status, and 1-year Overall Survival (OS), and Thalassemia Free Survival (TFS) were assessed. We observed that Treosulfan exposure was lower in patients with graft rejection than those without (1655 vs. 2037 mg*h/L, p=0.07). Pharmacodynamic modeling analysis to identify therapeutic cut-off revealed that Treosulfan exposure ≥1660 mg*hr/L was significantly associated with better 1-year TFS (97% vs. 81%, p=0.02) and a trend to better 1-year OS (90% vs. 69%, p=0.07). Further, multivariate analysis adjusting for known PreHCT risk factors also revealed Treosulfan exposure <1660mg*h/L (HR=3.23; 95% CI=1.12-9.34; p=0.03) and GSTA1*B variant genotype (HR=3.75; 95% CI=1.04-13.47; p=0.04) to be independent predictors for inferior 1-year TFS. We conclude that lower Treosulfan exposure increases the risk of graft rejection and early transplant-related mortality affecting TFS. As no RRTs were observed with increasing Treosulfan exposure, TDM-based dose adjustment could be feasible and beneficial