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Subgroup-specific structural variation across 1,000 medulloblastoma genomes

Overview of attention for article published in Nature, July 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

blogs
1 blog
twitter
18 tweeters
patent
2 patents
facebook
1 Facebook page
wikipedia
1 Wikipedia page
f1000
1 research highlight platform

Citations

dimensions_citation
543 Dimensions

Readers on

mendeley
530 Mendeley
citeulike
9 CiteULike
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Title
Subgroup-specific structural variation across 1,000 medulloblastoma genomes
Published in
Nature, July 2012
DOI 10.1038/nature11327
Pubmed ID
Authors

Paul A. Northcott, David J. H. Shih, John Peacock, Livia Garzia, A. Sorana Morrissy, Thomas Zichner, Adrian M. Stütz, Andrey Korshunov, Jüri Reimand, Steven E. Schumacher, Rameen Beroukhim, David W. Ellison, Christian R. Marshall, Anath C. Lionel, Stephen Mack, Adrian Dubuc, Yuan Yao, Vijay Ramaswamy, Betty Luu, Adi Rolider, Florence M. G. Cavalli, Xin Wang, Marc Remke, Xiaochong Wu, Readman Y. B. Chiu, Andy Chu, Eric Chuah, Richard D. Corbett, Gemma R. Hoad, Shaun D. Jackman, Yisu Li, Allan Lo, Karen L. Mungall, Ka Ming Nip, Jenny Q. Qian, Anthony G. J. Raymond, Nina Thiessen, Richard J. Varhol, Inanc Birol, Richard A. Moore, Andrew J. Mungall, Robert Holt, Daisuke Kawauchi, Martine F. Roussel, Marcel Kool, David T. W. Jones, Hendrick Witt, Africa Fernandez-L, Anna M. Kenney, Robert J. Wechsler-Reya, Peter Dirks, Tzvi Aviv, Wieslawa A. Grajkowska, Marta Perek-Polnik, Christine C. Haberler, Olivier Delattre, Stéphanie S. Reynaud, François F. Doz, Sarah S. Pernet-Fattet, Byung-Kyu Cho, Seung-Ki Kim, Kyu-Chang Wang, Wolfram Scheurlen, Charles G. Eberhart, Michelle Fèvre-Montange, Anne Jouvet, Ian F. Pollack, Xing Fan, Karin M. Muraszko, G. Yancey Gillespie, Concezio Di Rocco, Luca Massimi, Erna M. C. Michiels, Nanne K. Kloosterhof, Pim J. French, Johan M. Kros, James M. Olson, Richard G. Ellenbogen, Karel Zitterbart, Leos Kren, Reid C. Thompson, Michael K. Cooper, Boleslaw Lach, Roger E. McLendon, Darell D. Bigner, Adam Fontebasso, Steffen Albrecht, Nada Jabado, Janet C. Lindsey, Simon Bailey, Nalin Gupta, William A. Weiss, László Bognár, Almos Klekner, Timothy E. Van Meter, Toshihiro Kumabe, Teiji Tominaga, Samer K. Elbabaa, Jeffrey R. Leonard, Joshua B. Rubin, Linda M. Liau, Erwin G. Van Meir, Maryam Fouladi, Hideo Nakamura, Giuseppe Cinalli, Miklós Garami, Peter Hauser, Ali G. Saad, Achille Iolascon, Shin Jung, Carlos G. Carlotti, Rajeev Vibhakar, Young Shin Ra, Shenandoah Robinson, Massimo Zollo, Claudia C. Faria, Jennifer A. Chan, Michael L. Levy, Poul H. B. Sorensen, Matthew Meyerson, Scott L. Pomeroy, Yoon-Jae Cho, Gary D. Bader, Uri Tabori, Cynthia E. Hawkins, Eric Bouffet, Stephen W. Scherer, James T. Rutka, David Malkin, Steven C. Clifford, Steven J. M. Jones, Jan O. Korbel, Stefan M. Pfister, Marco A. Marra, Michael D. Taylor

Abstract

Medulloblastoma, the most common malignant paediatric brain tumour, is currently treated with nonspecific cytotoxic therapies including surgery, whole-brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, previous attempts to identify targets for therapy have been underpowered because of small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1,087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup-enriched. The most common region of focal copy number gain is a tandem duplication of SNCAIP, a gene associated with Parkinson's disease, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1, including PVT1-MYC and PVT1-NDRG1, that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGF-β signalling in Group 3, and NF-κB signalling in Group 4, suggest future avenues for rational, targeted therapy.

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 530 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 2%
United Kingdom 3 <1%
China 3 <1%
Canada 3 <1%
Germany 2 <1%
Netherlands 2 <1%
Mexico 1 <1%
Italy 1 <1%
Korea, Republic of 1 <1%
Other 7 1%
Unknown 496 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 124 23%
Student > Ph. D. Student 118 22%
Other 48 9%
Student > Master 46 9%
Student > Bachelor 44 8%
Other 111 21%
Unknown 39 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 182 34%
Medicine and Dentistry 136 26%
Biochemistry, Genetics and Molecular Biology 100 19%
Neuroscience 18 3%
Computer Science 16 3%
Other 29 5%
Unknown 49 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 30. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2019.
All research outputs
#706,834
of 15,624,646 outputs
Outputs from Nature
#25,425
of 75,271 outputs
Outputs of similar age
#4,875
of 127,869 outputs
Outputs of similar age from Nature
#455
of 943 outputs
Altmetric has tracked 15,624,646 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 75,271 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 84.6. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 127,869 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 943 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.