211 research outputs found

    "Imagine All the People, Sharing..." or A (Not So) Modest Proposal Made on the Eve of IDEA Reauthorization

    Get PDF

    Prenatal origin of childhood AML occurs less frequently than in childhood ALL

    Get PDF
    Background While there is enough convincing evidence in childhood acute lymphoblastic leukemia (ALL), the data on the pre-natal origin in childhood acute myeloid leukemia (AML) are less comprehensive. Our study aimed to screen Guthrie cards (neonatal blood spots) of non-infant childhood AML and ALL patients for the presence of their respective leukemic markers. Methods We analysed Guthrie cards of 12 ALL patients aged 2–6 years using immunoglobulin (Ig) and T-cell receptor (TCR) gene rearrangements (n = 15) and/or intronic breakpoints of TEL/AML1 fusion gene (n = 3). In AML patients (n = 13, age 1–14 years) PML/RARalpha (n = 4), CBFbeta/MYH11 (n = 3), AML1/ETO (n = 2), MLL/AF6 (n = 1), MLL/AF9 (n = 1) and MLL/AF10 (n = 1) fusion genes and/or internal tandem duplication of FLT3 gene (FLT3/ITD) (n = 2) were used as clonotypic markers. Assay sensitivity determined using serial dilutions of patient DNA into the DNA of a healthy donor allowed us to detect the pre-leukemic clone in Guthrie card providing 1–3 positive cells were present in the neonatal blood spot. Results In 3 patients with ALL (25%) we reproducibly detected their leukemic markers (Ig/TCR n = 2; TEL/AML1 n = 1) in the Guthrie card. We did not find patient-specific molecular markers in any patient with AML. Conclusion In the largest cohort examined so far we used identical approach for the backtracking of non-infant childhood ALL and AML. Our data suggest that either the prenatal origin of AML is less frequent or the load of pre-leukemic cells is significantly lower at birth in AML compared to ALL cases

    RISK ANALYSIS IN DEVELOPING HORIZONTAL TO VERTICAL HOUSING USING SEVERITY INDEX METHOD (CASE STUDY: RUMAH SUSUN PALDAM, BANDUNG)

    Get PDF
    Currently the gap between the demands with the supply of livable homes is relatively large. From various national figures, it is noted that this challenge requires a structured, systematic and massive handling / management effort, with no exception in the Capital of West Java Province, Bandung City. To fulfill the community's need for housing, the government has financial constraints due to the limited State Budget, so the government needs the help from business entities to meet the housing needs, as know as PPP. In this case, the construction is on land that is inhabited by the retired TNI community, so it is a separate and risky challenge. In general, any infrastructure development has a risk that needs to be mitigated. Therefore, it is necessary to carry out further and in-depth studies on what risks are affected and the allocation of risks so that management can be prepared. This paper aims to determine the risks posed in the construction of the Paldam Flats in Bandung. The analytical method used is the Severity Index Method. The analysis phase is carried out by starting with a preliminary survey of the parties concerned, then identifying risks. From the main survey results, this data will be processed with a risk probability matrix and risk impact, so it can be seen that the variables are included in the high category. From the results of data analysis, the risk that gives the greatest influence is the increase in construction costs and commercial revenues

    Human Papillomavirus 16 E5 Induces Bi-Nucleated Cell Formation By Cell-Cell Fusion

    Get PDF
    Human Papillomaviruses (HPV) 16 is a DNA virus encoding three oncogenes – E5, E6, and E7. The E6 and E7 proteins have well-established roles as inhibitors of tumor suppression, but the contribution of E5 to malignant transformation is controversial. Using spontaneously immortalized human keratinocytes (HaCaT cells), we demonstrate that expression of HPV16 E5 is necessary and sufficient for the formation of bi-nucleated cells, a common characteristic of precancerous cervical lesions. Expression of E5 from non-carcinogenic HPV6b does not produce bi-nucleate cells. Video microscopy and biochemical analyses reveal that bi-nucleates arise through cell-cell fusion. Although most E5-induced bi-nucleates fail to propagate, co-expression of HPV16 E6/E7 enhances the proliferation of these cells. Expression of HPV16 E6/E7 also increases bi-nucleated cell colony formation. These findings identify a new role for HPV16 E5 and support a model in which complementary roles of the HPV16 oncogenes lead to the induction of carcinogenesis

    Human MLL/KMT2A gene exhibits a second breakpoint cluster region for recurrent MLL–USP2 fusions

    Get PDF
    Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq: PQ-2017#305529/2017-0Deutsche Forschungsgemeinschaft, DFG: MA 1876/12-1Alexander von Humboldt-Stiftung: 88881.136091/2017-01RVO-VFN64165, 26/203.214/20172018.070.1Associazione Italiana per la Ricerca sul Cancro, AIRC: IG2015, 17593Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPESCancer Australia: PdCCRS1128727CancerfondenBarncancerfondenVetenskapsrÃ¥det, VRCrafoordska StiftelsenKnut och Alice Wallenbergs StiftelseLund University Medical Faculty FoundationXiamen University, XMU2014S0617-74-30019C7838/A15733Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNSF: 31003A_140913CNIBInstitut National Du Cancer, INCaR01 NCI CA167824National Institutes of Health, NIH: S10OD0185222016/2017, 02R/2016AU 525/1-1Deutschen Konsortium für Translationale Krebsforschung, DKTK70112951Smithsonian Institution, SIIsrael Science Foundation, ISFAustrian Science Fund, FWF: W1212SFB-F06107, SFB-F06105Acknowledgements BAL received a fellowship provided by CAPES and the Alexander von Humboldt Foundation (#88881.136091/2017-01). ME is supported by CNPq (PQ-2017#305529/2017-0) and FAPERJ-JCNE (#26/203.214/2017) research scholarships, and ZZ by grant RVO-VFN64165. GC is supported by the AIRC Investigator grant IG2015 grant no. 17593 and RS by Cancer Australia grant PdCCRS1128727. This work was supported by grants to RM from the “Georg und Franziska Speyer’sche Hochsschulstiftung”, the “Wilhelm Sander foundation” (grant 2018.070.1) and DFG grant MA 1876/12-1.Acknowledgements This work was supported by The Swedish Childhood Cancer Foundation, The Swedish Cancer Society, The Swedish Research Council, The Knut and Alice Wallenberg Foundation, BioCARE, The Crafoord Foundation, The Per-Eric and Ulla Schyberg Foundation, The Nilsson-Ehle Donations, The Wiberg Foundation, and Governmental Funding of Clinical Research within the National Health Service. Work performed at the Center for Translational Genomics, Lund University has been funded by Medical Faculty Lund University, Region Skåne and Science for Life Laboratory, Sweden.Acknowledgements This work was supported by the Fujian Provincial Natural Science Foundation 2016S016 China and Putian city Natural Science Foundation 2014S06(2), Fujian Province, China. Alexey Ste-panov and Alexander Gabibov were supported by Russian Scientific Foundation project No. 17-74-30019. Jinqi Huang was supported by a doctoral fellowship from Xiamen University, China.Acknowledgments This work was supported by the Swiss National Science Foundation (grant 31003A_140913; OH) and the Cancer Research UK Experimental Cancer Medicine Centre Network, Cardiff ECMCI, grant C7838/A15733. We thank N. Carpino for the Sts-1/2 double-KO mice.Acknowledgements This work was supported by the French National Cancer Institute (INCA) and the Fondation Française pour la Recherche contre le Myélome et les Gammapathies (FFMRG), the Intergroupe Francophone du Myélome (IFM), NCI R01 NCI CA167824 and a generous donation from Matthew Bell. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors thank the Association des Malades du Myélome Multiple (AF3M) for their continued support and participation. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization.We are indebted to all members of our groups for useful discussions and for their critical reading of the manuscript. Special thanks go to Silke Furlan, Friederike Opitz and Bianca Killing. F.A. is supported by the Deutsche For-schungsgemeinschaft (DFG, AU 525/1-1). J.H. has been supported by the German Children’s Cancer Foundation (Translational Oncology Program 70112951), the German Carreras Foundation (DJCLS 02R/2016), Kinderkrebsstiftung (2016/2017) and ERA PerMed GEPARD. Support by Israel Science Foundation, ERA-NET and Science Ministry (SI). A. B. is supported by the German Consortium of Translational Cancer Research, DKTK. We are grateful to the Jülich Supercomputing Centre at the Forschungszemtrum Jülich for granting computing time on the supercomputer JURECA (NIC project ID HKF7) and to the “Zentrum für Informations-und Medientechnologie” (ZIM) at the Heinrich Heine University Düsseldorf for providing computational support to H. G. The study was performed in the framework of COST action CA16223 “LEGEND”.Funding The work was supported by the Austrian Science Fund FWF grant SFB-F06105 to RM and SFB-F06107 to VS and FWF grant W1212 to VS

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

    Get PDF
    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    The KMT2A recombinome of acute leukemias in 2023

    Get PDF
    Chromosomal rearrangements of the human KMT2A/MLL gene are associated with de novo as well as therapy-induced infant, pediatric, and adult acute leukemias. Here, we present the data obtained from 3401 acute leukemia patients that have been analyzed between 2003 and 2022. Genomic breakpoints within the KMT2A gene and the involved translocation partner genes (TPGs) and KMT2A-partial tandem duplications (PTDs) were determined. Including the published data from the literature, a total of 107 in-frame KMT2A gene fusions have been identified so far. Further 16 rearrangements were out-of-frame fusions, 18 patients had no partner gene fused to 5'-KMT2A, two patients had a 5'-KMT2A deletion, and one ETV6::RUNX1 patient had an KMT2A insertion at the breakpoint. The seven most frequent TPGs and PTDs account for more than 90% of all recombinations of the KMT2A, 37 occur recurrently and 63 were identified so far only once. This study provides a comprehensive analysis of the KMT2A recombinome in acute leukemia patients. Besides the scientific gain of information, genomic breakpoint sequences of these patients were used to monitor minimal residual disease (MRD). Thus, this work may be directly translated from the bench to the bedside of patients and meet the clinical needs to improve patient survival
    corecore