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      Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design

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      1 , 2 , 3 , 2 , 3 , 4 , 1 , 4 , 5 , 6 , 1 , 7 , 8 , 2 , 1 , 9 , 2 , 2 , 3 , 1 , 8 , 1 , 1 , 2 , 2 , 10 , 11 , 11 , 10 , 10 , 10 , 10 , 10 , 10 , 12 , 13 , 2 , 3 , 14 , 15 , 16 , 15 , 16 , 15 , 16 , 15 , 16 , 15 , 16 , 15 , 16 , 15 , 16 , 17 , 18 , 18 , 18 , 19 , 19 , 19 , 19 , 4 , 4 , 20 , 1 , 1 , 1 , 1 , 21 , 22 , 23 , 24 , 9 , 1 , 2 , 25 , 6 , 6 , 26 , 19 , 27 , 28 , 29 , 20 , 15 , 16 , 30 , 31 , 11 , 18 , 18 , 32 , 13 , 2 , 3 , 4 , 1 , 33 , *
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          SUMMARY

          Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)—many of which are refractory to current standard-of-care treatments—from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer.

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          In Brief

          Rokita et. al provide an extensively annotated genomic dataset of somatic oncogenic regulation across 37 distinct pediatric malignancies. The 261 patient-derived xenograft models are available to the scientific community, and the genomic annotations will enable rational preclinical agent prioritization and acceleration of therapeutic targets for early-phase pediatric oncology clinical trials.

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          Most cited references43

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          An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation

          Gene set enrichment analysis is a widely used tool for analyzing gene expression data. However, current implementations are slow due to a large number of required samples for the analysis to have a good statistical power. In this paper we present a novel algorithm, that efficiently reuses one sample multiple times and thus speeds up the analysis. We show that it is possible to make hundreds of thousands permutations in a few minutes, which leads to very accurate p-values. This, in turn, allows applying standard FDR correction procedures, which are more accurate than the ones currently used. The method is implemented in a form of an R package and is freely available at \url{https://github.com/ctlab/fgsea}.
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            Integrated Molecular Meta-Analysis of 1,000 Pediatric High-Grade and Diffuse Intrinsic Pontine Glioma

            Summary We collated data from 157 unpublished cases of pediatric high-grade glioma and diffuse intrinsic pontine glioma and 20 publicly available datasets in an integrated analysis of >1,000 cases. We identified co-segregating mutations in histone-mutant subgroups including loss of FBXW7 in H3.3G34R/V, TOP3A rearrangements in H3.3K27M, and BCOR mutations in H3.1K27M. Histone wild-type subgroups are refined by the presence of key oncogenic events or methylation profiles more closely resembling lower-grade tumors. Genomic aberrations increase with age, highlighting the infant population as biologically and clinically distinct. Uncommon pathway dysregulation is seen in small subsets of tumors, further defining the molecular diversity of the disease, opening up avenues for biological study and providing a basis for functionally defined future treatment stratification.
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              Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes.

              Neuroblastoma is a childhood tumour of the peripheral sympathetic nervous system. The pathogenesis has for a long time been quite enigmatic, as only very few gene defects were identified in this often lethal tumour. Frequently detected gene alterations are limited to MYCN amplification (20%) and ALK activations (7%). Here we present a whole-genome sequence analysis of 87 neuroblastoma of all stages. Few recurrent amino-acid-changing mutations were found. In contrast, analysis of structural defects identified a local shredding of chromosomes, known as chromothripsis, in 18% of high-stage neuroblastoma. These tumours are associated with a poor outcome. Structural alterations recurrently affected ODZ3, PTPRD and CSMD1, which are involved in neuronal growth cone stabilization. In addition, ATRX, TIAM1 and a series of regulators of the Rac/Rho pathway were mutated, further implicating defects in neuritogenesis in neuroblastoma. Most tumours with defects in these genes were aggressive high-stage neuroblastomas, but did not carry MYCN amplifications. The genomic landscape of neuroblastoma therefore reveals two novel molecular defects, chromothripsis and neuritogenesis gene alterations, which frequently occur in high-risk tumours.
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                Author and article information

                Journal
                101573691
                39703
                Cell Rep
                Cell Rep
                Cell reports
                2211-1247
                20 November 2019
                05 November 2019
                27 November 2019
                : 29
                : 6
                : 1675-1689.e9
                Affiliations
                [1 ]Division of Oncology, Children’s Hospital of Philadelphia, and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104-4318, USA
                [2 ]Department of Bioinformatics and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [3 ]Center for Data-Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [4 ]Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
                [5 ]Guardian Forensic Sciences, Abington, PA 19001, USA
                [6 ]UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
                [7 ]Cell and Molecular Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
                [8 ]Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
                [9 ]Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
                [10 ]Children’s Cancer Institute, School of Women’s and Children’s Health, UNSW Sydney, Sydney, NSW, Australia
                [11 ]Cancer Center, Texas Tech University Health Sciences Center School of Medicine, Lubbock, TX 79430, USA
                [12 ]Sydney Children’s Hospital, Sydney, NSW, Australia
                [13 ]Children’s Cancer Institute, Kensington, NSW, Australia
                [14 ]Texas Children’s Cancer and Hematology Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
                [15 ]Preclinical Neurooncology Research Program, Texas Children’s Cancer Research Center, Texas Children’s Hospital, Houston, TX 77030, USA
                [16 ]Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
                [17 ]Department of Surgery, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
                [18 ]Greehey Children’s Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX 78229, USA
                [19 ]The Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA
                [20 ]Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
                [21 ]Department of Global Health Technologies, RTI International, Research Triangle Park, NC 27709, USA
                [22 ]Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
                [23 ]Norris Cotton Cancer Center, Lebanon, NH 03766, USA
                [24 ]Childhood Cancer Data Lab, Alex’s Lemonade Stand Foundation, Philadelphia, PA 19102, USA
                [25 ]Department of Molecular, Cell and Developmental Biology, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
                [26 ]Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
                [27 ]The Ohio State University College of Medicine, Departments of Pathology and Pediatrics, Columbus, OH 43210, USA
                [28 ]Department of Pediatrics, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA 19107, USA
                [29 ]Nemours Center for Cancer and Blood Disorders, Nemours/Alfred I. duPont Hospital for Children, Wilmington, DE 19803, USA
                [30 ]Division of Hematology, Oncology, Neuro-oncology and Stem Cell Transplant, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL 60611, USA
                [31 ]Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
                [32 ]National Cancer Institute, NIH, Bethesda, MD 20814, USA
                [33 ]Lead Contact
                Author notes

                AUTHOR CONTRIBUTIONS

                Conceptualization, J.M.M., D.A.W., J.L.R., M.A.S., P.J.H., R.T.K., X.-N.L., R.B.L., R.G., and M.H.; Methodology, D.A.W., J.L.R., J.P., G.P.W., and K.S.R.; Software, K.S.R., M.F.C., A.F., J.L.R., G.P.W., K.P., and J.P.; Validation, C.P.R., J.L.R., K.P., K.L.C., K.A.U., K.M., J.N., F.K.B., and K.S.G.; Formal Analysis, D.A.W., J.L.R., K.S.R., M.F.C., J.P., L.E.E., N.M.K., G.P.W., C. Mayoh, K.S.G., and P.R.; Investigation, J.L.R., J.P., K.S.R., K.A.U., K.L.C., G.P.W., K.L.C., and J.N.; Resources, J.M.G.-F., J.B., K.M.L., S.E.C., A.C.B., J.M.M., K. Krytska, Y.P.M., R.B.L., C.S.G., P.J.H., X.-N.L., R.T.K., H.V.D., Z.M., J.J., K.M., J.N., C. Morton, D.K., K.E., H.M., J.W.B., K.B., F.K.B., L.Q., Y.D., H.Z., H.B.L., S.Z., J.S., and P.B.; Data Curation, D.A.W., M.F.C., J.L.R., K.S.R., K.A.U., K. Kalletla, G.I.S., C. Mayoh, K.E., H.M., K.B., J.W.B., and E.R.B.; Writing - Original Draft, J.L.R., J.M.M., D.A.W., J.J., K.S.R., G.P.W., J.P., N.M.K., L.E.E., and K.A.U.; Writing - Review & Editing, J.L.R., M.A.S., J.M.M., C.S.G., C. Mayoh, R.B.L., Y.S., S.Z., and K. Krytska; Visualization, J.L.R., K.S.R., J.P., N.M.K., K.P., L.E.E., G.L., and A.M.; Supervision, J.M.M., D.A.W., J.L.R., M.A.S., D.H., C.P.R., S.J.D., O.M.V., and Z.V.; Project Administration, J.M.M., J.M.G.-F., J.B., K.M.L., M.A.S., and G.J.G.; Funding Acquisition, J.M.M., J.M.G.-F., D.A.W., C.P.R., R.B.L., J.L.R., M.H., G.M.M.,V.T., Y.S., R.G., P.J.H., and G.J.G.

                [* ]Correspondence: maris@ 123456email.chop.edu
                Article
                NIHMS1542708
                10.1016/j.celrep.2019.09.071
                6880934
                31693904
                77813c81-4fc6-4702-ad57-2602c9d2039e

                This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/).

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