489 research outputs found

    Transverse momentum dependent parton distributions in a light-cone quark model

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    The leading twist transverse momentum dependent parton distributions (TMDs) are studied in a light-cone description of the nucleon where the Fock expansion is truncated to consider only valence quarks. General analytic expressions are derived in terms of the six amplitudes needed to describe the three-quark sector of the nucleon light-cone wave function. Numerical calculations for the T-even TMDs are presented in a light-cone constituent quark model, and the role of the so-called pretzelosity is investigated to produce a nonspherical shape of the nucleon.Comment: references added and typos corrected; version to appear in Phys. Rev.

    IKZF1 Deletions with COBL Breakpoints Are Not Driven by RAG-Mediated Recombination Events in Acute Lymphoblastic Leukemia

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    IKZF1 deletion (ΔIKZF1) is an important predictor of relapse in both childhood and adult B-cell precursor acute lymphoblastic leukemia (B-ALL). Previously, we revealed that COBL is a hotspot for breakpoints in leukemia and could promote IKZF1 deletions. Through an international collaboration, we provide a detailed genetic and clinical picture of B-ALL with COBL rearrangements (COBL-r). Patients with B-ALL and IKZF1 deletion (n = 133) were included. IKZF1 ∆1-8 were associated with large alterations within chromosome 7: monosomy 7 (18%), isochromosome 7q (10%), 7p loss (19%), and interstitial deletions (53%). The latter included COBL-r, which were found in 12% of the IKZF1 ∆1-8 cohort. Patients with COBL-r are mostly classified as intermediate cytogenetic risk and frequently harbor ETV6, PAX5, CDKN2A/B deletions. Overall, 56% of breakpoints were located within COBL intron 5. Cryptic recombination signal sequence motifs were broadly distributed within the sequence of COBL, and no enrichment for the breakpoint cluster region was found. In summary, a diverse spectrum of alterations characterizes ΔIKZF1 and they also include deletion breakpoints within COBL. We confirmed that COBL is a hotspot associated with ΔIKZF1, but these rearrangements are not driven by RAG-mediated recombination

    γ-Catenin-Dependent Signals Maintain BCR-ABL1<sup>+</sup> B Cell Acute Lymphoblastic Leukemia.

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    The BCR-ABL1 fusion protein is the cause of chronic myeloid leukemia (CML) and of a significant fraction of adult-onset B cell acute lymphoblastic leukemia (B-ALL) cases. Using mouse models and patient-derived samples, we identified an essential role for γ-catenin in the initiation and maintenance of BCR-ABL1 &lt;sup&gt;+&lt;/sup&gt; B-ALL but not CML. The selectivity was explained by a partial γ-catenin dependence of MYC expression together with the susceptibility of B-ALL, but not CML, to reduced MYC levels. MYC and γ-catenin enabled B-ALL maintenance by augmenting BIRC5 and enforced BIRC5 expression overcame γ-catenin loss. Since γ-catenin was dispensable for normal hematopoiesis, these lineage- and disease-specific features of canonical Wnt signaling identified a potential therapeutic target for the treatment of BCR-ABL1 &lt;sup&gt;+&lt;/sup&gt; B-ALL

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

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    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

    The KMT2A recombinome of acute leukemias in 2023

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    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

    Trends in modeling Biomedical Complex Systems

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    In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented
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