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      Mechanisms and therapeutic implications of hypermutation in gliomas

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

          A high tumour mutational burden (hypermutation) is observed in some gliomas 15 ; however, the mechanisms by which hypermutation develops and whether it predicts the response to immunotherapy are poorly understood. Here we comprehensively analyse the molecular determinants of mutational burden and signatures in 10,294 gliomas. We delineate two main pathways to hypermutation: a de novo pathway associated with constitutional defects in DNA polymerase and mismatch repair (MMR) genes, and a more common post-treatment pathway, associated with acquired resistance driven by MMR defects in chemotherapy-sensitive gliomas that recur after treatment with the chemotherapy drug temozolomide. Experimentally, the mutational signature of post-treatment hypermutated gliomas was recapitulated by temozolomide-induced damage in cells with MMR deficiency. MMR-deficient gliomas were characterized by a lack of prominent T cell infiltrates, extensive intratumoral heterogeneity, poor patient survival and a low rate of response to PD-1 blockade. Moreover, although bulk analyses did not detect microsatellite instability in MMR-deficient gliomas, single-cell whole-genome sequencing analysis of post-treatment hypermutated glioma cells identified microsatellite mutations. These results show that chemotherapy can drive the acquisition of hypermutated populations without promoting a response to PD-1 blockade and supports the diagnostic use of mutational burden and signatures in cancer.

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          Most cited references66

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          The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

          Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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            Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma

            Glioblastoma, the most common primary brain tumor in adults, is usually rapidly fatal. The current standard of care for newly diagnosed glioblastoma is surgical resection to the extent feasible, followed by adjuvant radiotherapy. In this trial we compared radiotherapy alone with radiotherapy plus temozolomide, given concomitantly with and after radiotherapy, in terms of efficacy and safety. Patients with newly diagnosed, histologically confirmed glioblastoma were randomly assigned to receive radiotherapy alone (fractionated focal irradiation in daily fractions of 2 Gy given 5 days per week for 6 weeks, for a total of 60 Gy) or radiotherapy plus continuous daily temozolomide (75 mg per square meter of body-surface area per day, 7 days per week from the first to the last day of radiotherapy), followed by six cycles of adjuvant temozolomide (150 to 200 mg per square meter for 5 days during each 28-day cycle). The primary end point was overall survival. A total of 573 patients from 85 centers underwent randomization. The median age was 56 years, and 84 percent of patients had undergone debulking surgery. At a median follow-up of 28 months, the median survival was 14.6 months with radiotherapy plus temozolomide and 12.1 months with radiotherapy alone. The unadjusted hazard ratio for death in the radiotherapy-plus-temozolomide group was 0.63 (95 percent confidence interval, 0.52 to 0.75; P<0.001 by the log-rank test). The two-year survival rate was 26.5 percent with radiotherapy plus temozolomide and 10.4 percent with radiotherapy alone. Concomitant treatment with radiotherapy plus temozolomide resulted in grade 3 or 4 hematologic toxic effects in 7 percent of patients. The addition of temozolomide to radiotherapy for newly diagnosed glioblastoma resulted in a clinically meaningful and statistically significant survival benefit with minimal additional toxicity. Copyright 2005 Massachusetts Medical Society.
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              PD-1 Blockade in Tumors with Mismatch-Repair Deficiency.

              Somatic mutations have the potential to encode "non-self" immunogenic antigens. We hypothesized that tumors with a large number of somatic mutations due to mismatch-repair defects may be susceptible to immune checkpoint blockade.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                28 March 2020
                15 April 2020
                April 2020
                26 June 2021
                : 580
                : 7804
                : 517-523
                Affiliations
                [1 ]Department of Oncologic Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
                [2 ]Broad Institute of Harvard and MIT, Cambridge, MA, USA
                [3 ]Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Service de Neurologie 2-Mazarin, F-75013, Paris, France
                [4 ]Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
                [5 ]Department of Pathology, Brigham & Women’s Hospital, Boston, Harvard Medical School, MA, USA
                [6 ]Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
                [7 ]Bioinformatics and Integrative Genomics PhD Program, Harvard Medical School, Boston, MA, USA
                [8 ]European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
                [9 ]Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
                [10 ]Foundation Medicine Inc, Cambridge, MA, USA.
                [11 ]Wake Forest Comprehensive Cancer Center and Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC
                [12 ]Center for Patient Derived Models, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
                [13 ]Drug Development Department, Gustave Roussy, Villejuif, France
                [14 ]Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013, Paris, France
                [15 ]Unité fonctionnelle d’Oncogénétique et Angiogénétique Moleculaire, Département de génétique, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, F-75013, Paris, France
                [16 ]Department of Diagnostic Radiology, Gustave Roussy, Villejuif, France; IR4M (UMR8081), Université Paris-Sud, Centre National de la Recherche Scientifique, Orsay, France
                [17 ]AP-HP, Université Paris Descartes, Hôpital Cochin, Service d’Anatomie et Cytologie Pathologiques, Paris, France
                [18 ]Sorbonne Université, Inserm, CNRS, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, AP-HP, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Service de Neuropathologie Laboratoire Escourolle, F-75013, Paris, France
                [19 ]Sorbonne Université, Hôpitaux Universitaires La Pitié Salpêtrière - Charles Foix, Service de Neurochirurgie, F-75013, Paris, France
                [20 ]Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
                [21 ]Department of Radiation Oncology, Arthur G. James Hospital/Ohio State Comprehensive Cancer Center, Columbus, OH, USA
                [22 ]Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
                [23 ]Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
                [24 ]Department of Pathology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
                [25 ]Dana-Farber/Boston Children’s Cancer and Blood Disorders Center
                [26 ]Department of Pediatrics, Harvard Medical School
                [27 ]Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston Children’s Hospital, Boston, MA, USA
                [28 ]Department of Radiology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
                [29 ]Onconeurotek Tumor Bank, Institut du Cerveau et de la Moelle épinère, ICM, Paris, France
                [30 ]Ludwig Center at Harvard Medical School, Harvard Medical School, Boston, MA, USA
                [31 ]Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA
                [32 ]Sorbonne Universités, Inserm, UMR 938, Centre de Recherche Saint Antoine, Paris, France
                Author notes
                [§]

                Co-First Authors

                [†]

                Co-Senior Authors

                CONTRIBUTIONS

                M.T., R.B., P.B., F. Bielle and K.L.L. designed the study. M.T., Y.Y.L., R.B., P.B., F. Bielle and K.L.L. wrote the initial draft, with input from all authors. Y.Y.L. validated mutational signature analyses using TCGA data. M.T., Y.Y.L., L.F.S., R.S., D. Pavliak and L.A.A. performed TMB and mutational signature analyses of the DFCI-Profile, MSKCC-IMPACT and FMI datasets, and integrated TMB, signature and clinical data. L.F.S. developed the code for permutation tests. M.T., Y.Y.L., L.F.S. and R.S. performed and analysed the permutation tests. M.T., A.N.B., K.P., C. Bellamy, N.C., J.B., K.Q., P.H., S.M., L.T., R.B., P.B. and K.L.L. performed in vitro experiments in native and engineered models and analysed experimental data. M.T., K.P., J.B. and K.L.L. performed in vivo experiments in native models and analysed experimental data. M.T., F. Beuvon, K.M., S. Alexandrescu, D.M.M., S.S., F. Bielle, and K.L.L. reviewed histological and immunohistochemistry data on human samples. M.T. and J.B.I. performed survival analyses. M.T., Y.Y.L., C.L.B., I.C.-C., P.J.P., R.B., P.B. and K.L.L. performed single-cell sequencing experiments and analysed data. C.L.B., I.C.-C. and P.J.P. developed computational tools for the analysis of single-cell data. M.T., Y.Y.L., L.F.S., C.L.B., I.C.-C., S.H.R., F.D., A.S., R.S., D. Pavliak, L.A.A., E.G., G.M.F., F.C., A.D., A. Cherniack, P.J.P., R.B., P.B. and K.L.L. reviewed and analysed the bulk sequencing genomic data. M.T., J.B.I., C. Birzu, J.E.G., M.J.L.-F., R.J., N.Y., C. Baldini, E.G., S. Ammari, F. Beuvon, K.M., A.A., C.D., C.H., F.L.-D., D. Psimaras, E.Q.L., L.N., J.R.M.-F., A. Carpentier, P.C., L.C., B.M., J.S.B.-S., A. Chakravarti, W.L.B., E. A. Chiocca, K.P.F., S. Alexandrescu, S.C., D.H.-K., T.T.B., B.M.A., R.Y.H., A.H.L., F.C., J.-Y.D., K.H.-X., D.M.M., S.S., M.S., P.Y.W., D.A.R., A.M., A.I., R.B., P.B., F. Bielle, and K.L.L. abstracted and reviewed clinical and treatment response data. Y.Y.L., L.F.S., C.L.B., I.C.-C., R.S., L.A.A., G.M.F., A. Cherniack, and R.B. created bioinformatics tools and systems to support data analysis. R.B., P.B., F. Bielle, and K.L.L. acquired funding and supervised the study. All authors participated in data analysis and approved the final manuscript.

                Correspondence: Dr. Mehdi Touat, mehdi.touat@ 123456gmail.com , Dr. Rameen Beroukhim, rameen_beroukhim@ 123456dfci.harvard.edu , Dr. Pratiti Bandopadhayay, pratiti_bandopadhayay@ 123456dfci.harvard.edu , Dr. Franck Bielle, franck.bielle@ 123456aphp.fr , Dr. Keith L. Ligon, keith_ligon@ 123456dfci.harvard.edu
                Article
                NIHMS1572083
                10.1038/s41586-020-2209-9
                8235024
                32322066
                718c5b2e-25e2-4ea5-9341-cf4673189418

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