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Record W2167532631 · doi:10.1038/nature11284

Dissecting the genomic complexity underlying medulloblastoma

2012· article· en· W2167532631 on OpenAlexaff
David Jones, Natalie Jäger, Marcel Kool, Thomas Zichner, Barbara Hutter, Marc Sultan, Yoon‐Jae Cho, Trevor J. Pugh, Volker Hovestadt, Adrian M. Stütz, Tobias Rausch, Hans-Jörg Warnatz, Marina Ryzhova, Sebastian Bender, Dominik Sturm, Sabrina Pleier, Huriye Cin, Elke Pfaff, Laura Sieber, Andrea Wittmann, Marc Remke, Hendrik Witt, Sonja Hutter, Theophilos Tzaridis, Joachim Weischenfeldt, Benjamin Raeder, Meryem Avci, Vyacheslav Amstislavskiy, Marc Zapatka, Ursula Weber, Qi Wang, Bärbel Lasitschka, Cynthia C. Bartholomae, Manfred Schmidt, Christof von Kalle, Volker Ast, Chris Lawerenz, Rolf Kabbe, Vladimı́r Beneš, Peter van Sluis, Jan Köster, Richard Volckmann, David Shih, Matthew J. Betts, Robert B. Russell, Simona Coco, Gian Paolo Tonini, Ulrich Schüller, Volkmar Hans, Norbert Graf, Yoo-Jin Kim, Camelia Monoranu, Wolfgang Roggendorf, Andreas Unterberg, Christel Herold‐Mende, Till Milde, Andreas E. Kulozik, Andreas von Deimling, Olaf Witt, Jochen Rößler, Martin Ebinger, Martin U. Schuhmann, Michael C. Frühwald, Martin Hasselblatt, Nada Jabado, Stefan Rutkowski, André O. von Bueren, Dan Williamson, Steven C. Clifford, Martin G. McCabe, V. Peter Collins, Stephan Wolf, Stefan Wiemann, Hans Lehrach, Benedikt Brors, Wolfram Scheurlen, Jörg Felsberg, Guido Reifenberger, Paul A. Northcott, Michael D. Taylor, Matthew Meyerson, Scott L. Pomeroy, Marie‐Laure Yaspo, Jan O. Korbel, Andrey Korshunov, Roland Eils, Stefan M. Pfister, Peter Lichter

Bibliographic record

VenueNature · 2012
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreSickKids FoundationHospital for Sick Children
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentHeidelberger Zentrum für Personalisierte Onkologie Deutsches Krebsforschungszentrum In Der Helmholtz-GemeinschaftDeutsche KrebshilfeNational Cancer InstituteCancer Research UKChildren's Cancer and Leukaemia GroupMax-Planck-GesellschaftDeutsches KrebsforschungszentrumBrain Tumour CharityBundesministerium für Bildung und ForschungPediatric Brain Tumor Foundation
KeywordsMedulloblastomaBiologyWnt signaling pathwayPTCH1Sonic hedgehogHedgehogCancer researchGeneGenetics

Abstract

fetched live from OpenAlex

Medulloblastoma is the most common brain tumour in children; using whole-genome sequencing of tumour samples the authors show that the clinically challenging Group 3 and 4 tumours can be tetraploid, and reveal the expression of the first medulloblastoma fusion genes identified. Medulloblastoma is the most common malignant brain tumour in children. Four papers published in the 2 August 2012 issue of Nature use whole-genome and other sequencing techniques to produce a detailed picture of the genetics and genomics of this condition. Notable findings include the identification of recurrent mutations in genes not previously implicated in medulloblastoma, with significant genetic differences associated with the four biologically distinct subgroups and clinical outcomes in each. Potential avenues for therapy are suggested by the identification of targetable somatic copy-number alterations, including recurrent events targeting TGFβ signalling in Group 3, and NF-κB signalling in Group 4 medulloblastomas. 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 shows 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 identified2,3. WNT tumours, showing 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 and 4 tumours are molecularly less well characterized, 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, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 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 what are, to our knowledge, the first medulloblastoma fusion genes identified. 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 and 4 patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.338
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations876
Published2012
Admission routes1
Has abstractyes

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