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1.  Recurrent somatic alterations of FGFR1 and NTRK2 in pilocytic astrocytoma 
Jones, David T.W. | Hutter, Barbara | Jäger, Natalie | Korshunov, Andrey | Kool, Marcel | Warnatz, Hans-Jörg | Zichner, Thomas | Lambert, Sally R. | Ryzhova, Marina | Quang, Dong Anh Khuong | Fontebasso, Adam M. | Stütz, Adrian M. | Hutter, Sonja | Zuckermann, Marc | Sturm, Dominik | Gronych, Jan | Lasitschka, Bärbel | Schmidt, Sabine | Şeker-Cin, Huriye | Witt, Hendrik | Sultan, Marc | Ralser, Meryem | Northcott, Paul A. | Hovestadt, Volker | Bender, Sebastian | Pfaff, Elke | Stark, Sebastian | Faury, Damien | Schwartzentruber, Jeremy | Majewski, Jacek | Weber, Ursula D. | Zapatka, Marc | Raeder, Benjamin | Schlesner, Matthias | Worth, Catherine L. | Bartholomae, Cynthia C. | von Kalle, Christof | Imbusch, Charles D. | Radomski, Sylwester | Lawerenz, Chris | van Sluis, Peter | Koster, Jan | Volckmann, Richard | Versteeg, Rogier | Lehrach, Hans | Monoranu, Camelia | Winkler, Beate | Unterberg, Andreas | Herold-Mende, Christel | Milde, Till | Kulozik, Andreas E. | Ebinger, Martin | Schuhmann, Martin U. | Cho, Yoon-Jae | Pomeroy, Scott L. | von Deimling, Andreas | Witt, Olaf | Taylor, Michael D. | Wolf, Stephan | Karajannis, Matthias A. | Eberhart, Charles G. | Scheurlen, Wolfram | Hasselblatt, Martin | Ligon, Keith L. | Kieran, Mark W. | Korbel, Jan O. | Yaspo, Marie-Laure | Brors, Benedikt | Felsberg, Jörg | Reifenberger, Guido | Collins, V. Peter | Jabado, Nada | Eils, Roland | Lichter, Peter | Pfister, Stefan M.
Nature genetics  2013;45(8):927-932.
Pilocytic astrocytoma, the most common childhood brain tumor1, is typically associated with mitogen-activated protein kinase (MAPK) pathway alterations2. Surgically inaccessible midline tumors are therapeutically challenging, showing sustained tendency for progression3 and often becoming a chronic disease with substantial morbidities4.
Here we describe whole-genome sequencing of 96 pilocytic astrocytomas, with matched RNA sequencing (n=73), conducted by the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. We identified recurrent activating mutations in FGFR1 and PTPN11 and novel NTRK2 fusion genes in non-cerebellar tumors. New BRAF activating changes were also observed. MAPK pathway alterations affected 100% of tumors analyzed, with no other significant mutations, indicating pilocytic astrocytoma as predominantly a single-pathway disease.
Notably, we identified the same FGFR1 mutations in a subset of H3F3A-mutated pediatric glioblastoma with additional alterations in NF15. Our findings thus identify new potential therapeutic targets in distinct subsets of pilocytic astrocytoma and childhood glioblastoma.
doi:10.1038/ng.2682
PMCID: PMC3951336  PMID: 23817572
2.  Signatures of mutational processes in human cancer 
Alexandrov, Ludmil B. | Nik-Zainal, Serena | Wedge, David C. | Aparicio, Samuel A.J.R. | Behjati, Sam | Biankin, Andrew V. | Bignell, Graham R. | Bolli, Niccolo | Borg, Ake | Børresen-Dale, Anne-Lise | Boyault, Sandrine | Burkhardt, Birgit | Butler, Adam P. | Caldas, Carlos | Davies, Helen R. | Desmedt, Christine | Eils, Roland | Eyfjörd, Jórunn Erla | Foekens, John A. | Greaves, Mel | Hosoda, Fumie | Hutter, Barbara | Ilicic, Tomislav | Imbeaud, Sandrine | Imielinsk, Marcin | Jäger, Natalie | Jones, David T.W. | Jones, David | Knappskog, Stian | Kool, Marcel | Lakhani, Sunil R. | López-Otín, Carlos | Martin, Sancha | Munshi, Nikhil C. | Nakamura, Hiromi | Northcott, Paul A. | Pajic, Marina | Papaemmanuil, Elli | Paradiso, Angelo | Pearson, John V. | Puente, Xose S. | Raine, Keiran | Ramakrishna, Manasa | Richardson, Andrea L. | Richter, Julia | Rosenstiel, Philip | Schlesner, Matthias | Schumacher, Ton N. | Span, Paul N. | Teague, Jon W. | Totoki, Yasushi | Tutt, Andrew N.J. | Valdés-Mas, Rafael | van Buuren, Marit M. | van ’t Veer, Laura | Vincent-Salomon, Anne | Waddell, Nicola | Yates, Lucy R. | Zucman-Rossi, Jessica | Futreal, P. Andrew | McDermott, Ultan | Lichter, Peter | Meyerson, Matthew | Grimmond, Sean M. | Siebert, Reiner | Campo, Elías | Shibata, Tatsuhiro | Pfister, Stefan M. | Campbell, Peter J. | Stratton, Michael R.
Nature  2013;500(7463):415-421.
All cancers are caused by somatic mutations. However, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here, we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, kataegis, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer with potential implications for understanding of cancer etiology, prevention and therapy.
doi:10.1038/nature12477
PMCID: PMC3776390  PMID: 23945592
3.  Hypermutation of the Inactive X Chromosome Is a Frequent Event in Cancer 
Cell  2013;155(3):567-581.
Summary
Mutation is a fundamental process in tumorigenesis. However, the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. Here, we performed a cross-cancer comparison of 402 whole genomes comprising a diverse set of childhood and adult tumors, including both solid and hematopoietic malignancies. Surprisingly, we found that the inactive X chromosome of many female cancer genomes accumulates on average twice and up to four times as many somatic mutations per megabase, as compared to the individual autosomes. Whole-genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals and a premalignant myelodysplastic syndrome (MDS) sample revealed no X chromosome hypermutation. Our data suggest that hypermutation of the inactive X chromosome is an early and frequent feature of tumorigenesis resulting from DNA replication stress in aberrantly proliferating cells.
Graphical Abstract
Highlights
•X chromosome has up to 4× more mutations than the autosomes in female cancer genomes•Hypermutations only affect the inactive X chromosome•X hypermutation involves somatic point mutations and indels, but not germline mutations•No X hypermutation is found in clonal expansions of normal or premalignant cells
A comparison of 402 cancer genomes identifies a surprisingly high level of somatic mutations in the inactive X chromosome of female cancer genomes. As hypermutability of the inactive X was not observed in clonal hematopoietic progenitor or preleukemic samples, it is likely that it may be a contributing factor to tumorigenesis.
doi:10.1016/j.cell.2013.09.042
PMCID: PMC3898475  PMID: 24139898
4.  Coverage Bias and Sensitivity of Variant Calling for Four Whole-genome Sequencing Technologies 
PLoS ONE  2013;8(6):e66621.
The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illumina’s HiSeq2000, Life Technologies’ SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics’ technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies’ platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes.
doi:10.1371/journal.pone.0066621
PMCID: PMC3679043  PMID: 23776689
5.  ICGC PedBrain: Dissecting the genomic complexity underlying medulloblastoma 
Jones, David TW | Jäger, Natalie | Kool, Marcel | Zichner, Thomas | Hutter, Barbara | Sultan, Marc | Cho, Yoon-Jae | Pugh, Trevor J | Hovestadt, Volker | Stütz, Adrian M | Rausch, Tobias | Warnatz, Hans-Jörg | Ryzhova, Marina | Bender, Sebastian | Sturm, Dominik | Pleier, Sabrina | Cin, Huriye | Pfaff, Elke | Sieber, Laura | Wittmann, Andrea | Remke, Marc | Witt, Hendrik | Hutter, Sonja | Tzaridis, Theophilos | Weischenfeldt, Joachim | Raeder, Benjamin | Avci, Meryem | Amstislavskiy, Vyacheslav | Zapatka, Marc | Weber, Ursula D | Wang, Qi | Lasitschka, Bärbel | Bartholomae, Cynthia C | Schmidt, Manfred | von Kalle, Christof | Ast, Volker | Lawerenz, Chris | Eils, Jürgen | Kabbe, Rolf | Benes, Vladimir | van Sluis, Peter | Koster, Jan | Volckmann, Richard | Shih, David | Betts, Matthew J | Russell, Robert B | Coco, Simona | Tonini, Gian Paolo | Schüller, Ulrich | Hans, Volkmar | Graf, Norbert | Kim, Yoo-Jin | Monoranu, Camelia | Roggendorf, Wolfgang | Unterberg, Andreas | Herold-Mende, Christel | Milde, Till | Kulozik, Andreas E | von Deimling, Andreas | Witt, Olaf | Maass, Eberhard | Rössler, Jochen | Ebinger, Martin | Schuhmann, Martin U | Frühwald, Michael C | Hasselblatt, Martin | Jabado, Nada | Rutkowski, Stefan | von Bueren, André O | Williamson, Dan | Clifford, Steven C | McCabe, Martin G | Collins, V. Peter | Wolf, Stephan | Wiemann, Stefan | Lehrach, Hans | Brors, Benedikt | Scheurlen, Wolfram | Felsberg, Jörg | Reifenberger, Guido | Northcott, Paul A | Taylor, Michael D | Meyerson, Matthew | Pomeroy, Scott L | Yaspo, Marie-Laure | Korbel, Jan O | Korshunov, Andrey | Eils, Roland | Pfister, Stefan M | Lichter, Peter
Nature  2012;488(7409):100-105.
Summary
Medulloblastoma is an aggressively-growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and displays tremendous biological and clinical heterogeneity1. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life.
Four tumour subgroups with distinct clinical, biological and genetic profiles are currently discriminated2,3. WNT tumours, displaying activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens4. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis2. Group 3 & 4 tumours are molecularly less well-characterised, and also present the greatest clinical challenges2,3,5. The full repertoire of genetic events driving this distinction, however, remains unclear.
Here we describe an integrative deep-sequencing analysis of 125 tumour-normal pairs. Tetraploidy was identified as a frequent early event in Group 3 & 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA-sequencing confirmed these alterations, and revealed the expression of the first medulloblastoma fusion genes. Chromatin modifiers were frequently altered across all subgroups.
These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 & 4 patients.
doi:10.1038/nature11284
PMCID: PMC3662966  PMID: 22832583
6.  MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATIONS 
Nature  2012;488(7409):106-110.
Medulloblastomas are the most common malignant brain tumors in children1. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles2–5. Here, we utilized whole exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, novel findings in medulloblastoma. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma.
doi:10.1038/nature11329
PMCID: PMC3413789  PMID: 22820256
7.  Genome Sequencing of Pediatric Medulloblastoma Links Catastrophic DNA Rearrangements with TP53 Mutations 
Cell  2012;148(1-2):59-71.
SUMMARY
Genomic rearrangements are thought to occur progressively during tumor development. Recent findings, however, suggest an alternative mechanism, involving massive chromosome rearrangements in a one-step catastrophic event termed chromothripsis. We report the whole-genome sequencing-based analysis of a Sonic-Hedgehog medulloblastoma (SHH-MB) brain tumor from a patient with a germline TP53 mutation (Li-Fraumeni syndrome), uncovering massive, complex chromosome rearrangements. Integrating TP53 status with microarray and deep sequencing-based DNA rearrangement data in additional patients reveals a striking association between TP53 mutation and chromothripsis in SHH-MBs. Analysis of additional tumor entities substantiates a link between TP53 mutation and chromothripsis, and indicates a context-specific role for p53 in catastrophic DNA rearrangements. Among these, we observed a strong association between somatic TP53 mutations and chromothripsis in acute myeloid leukemia. These findings connect p53 status and chromothripsis in specific tumor types, providing a genetic basis for understanding particularly aggressive subtypes of cancer.
doi:10.1016/j.cell.2011.12.013
PMCID: PMC3332216  PMID: 22265402
9.  Lung stem cell self-renewal relies on Bmi1-dependent control of expression at imprinted loci 
Cell stem cell  2011;9(3):272-281.
Summary
Bmi1 is required for the self-renewal of stem cells in many tissues including the lung epithelial stem cells, Bronchioalveolar Stem Cells (BASCs). Imprinted genes, which exhibit expression from only the maternally- or paternally-inherited allele, are known to regulate developmental processes but their role in adult cells remains a fundamental question. Many imprinted genes were de-repressed in Bmi1 knockout mice, and knockdown of Cdkn1c (p57) and other imprinted genes partially rescued the self-renewal defect of Bmi1 mutant lung cells. Expression of p57 and other imprinted genes was required for lung cell self-renewal in culture and correlated with repair of lung epithelial cell injury in vivo. Our data suggest that Bmi1-dependent regulation of expressed alleles at imprinted loci, distinct from imprinting per se, is required for control of lung stem cells. We anticipate that the regulation and function of imprinted genes is crucial for self-renewal in diverse adult tissue-specific stem cells.
doi:10.1016/j.stem.2011.07.007
PMCID: PMC3167236  PMID: 21885022
10.  Genome-wide mapping of DNA methylation: a quantitative technology comparison 
Nature biotechnology  2010;28(10):1106-1114.
DNA methylation is a key component of mammalian gene regulation and the most classical example of an epigenetic mark. DNA methylation patterns are mitotically heritable and stable over time, but they undergo considerable changes in response to cell differentiation, diseases and environmental influences. Several methods have been developed for DNA methylation profiling on a genomic scale. Here, we benchmark four of these methods on two sample pairs, comparing their accuracy and power to detect DNA methylation differences. The results show that all evaluated methods (MeDIP-seq: methylated DNA immunoprecipitation, MethylCap-seq: methylated DNA capture by affinity purification, RRBS: reduced representation bisulfite sequencing, and the Infinium HumanMethylation27 assay) produce accurate DNA methylation data. However, these methods differ in their ability to detect differentially methylated regions between pairs of samples. We highlight strengths and weaknesses of the four methods and give practical recommendations for the design of epigenomic case-control studies.
doi:10.1038/nbt.1681
PMCID: PMC3066564  PMID: 20852634
Epigenome profiling; epigenetics; sequencing; differentially methylated regions; molecular diagnostics; biomarker discovery; cancer
11.  Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution 
Nature methods  2010;7(2):133-136.
Bisulfite sequencing measures absolute levels of DNA methylation at single-nucleotide resolution, providing a robust platform for molecular diagnostics. Here, we optimize bisulfite sequencing for genome-scale analysis of clinical samples. Specifically, we outline how restriction digestion targets bisulfite sequencing to hotspots of epigenetic regulation; we show that 30ng of DNA are sufficient for genome-scale analysis; we demonstrate that our protocol works well on formalin-fixed, paraffin-embedded (FFPE) samples; and we describe a statistical method for assessing significance of altered DNA methylation patterns.
doi:10.1038/nmeth.1414
PMCID: PMC2860480  PMID: 20062050
Epigenome profiling; epigenetics; bisulfite sequencing; human disease samples; cancer; biomarker development; molecular diagnostics; FFPE
12.  MHC I Stabilizing Potential of Computer-Designed Octapeptides 
Experimental results are presented for 180 in silico designed octapeptide sequences and their stabilizing effects on the major histocompatibility class I molecule H-2Kb. Peptide sequence design was accomplished by a combination of an ant colony optimization algorithm with artificial neural network classifiers. Experimental tests yielded nine H-2Kb stabilizing and 171 nonstabilizing peptides. 28 among the nonstabilizing octapeptides contain canonical motif residues known to be favorable for MHC I stabilization. For characterization of the area covered by stabilizing and non-stabilizing octapeptides in sequence space, we visualized the distribution of 100,603 octapeptides using a self-organizing map. The experimental results present evidence that the canonical sequence motives of the SYFPEITHI database on their own are insufficient for predicting MHC I protein stabilization.
doi:10.1155/2010/396847
PMCID: PMC2876253  PMID: 20508831

Results 1-12 (12)