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Sleeping Beauty mutagenesis in a mouse medulloblastoma model defines networks that discriminate between human molecular subgroups

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, October 2013
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
twitter
2 X users

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
88 Mendeley
citeulike
2 CiteULike
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Title
Sleeping Beauty mutagenesis in a mouse medulloblastoma model defines networks that discriminate between human molecular subgroups
Published in
Proceedings of the National Academy of Sciences of the United States of America, October 2013
DOI 10.1073/pnas.1318639110
Pubmed ID
Authors

Laura A. Genovesi, Ching Ging Ng, Melissa J. Davis, Marc Remke, Michael D. Taylor, David J. Adams, Alistair G. Rust, Jerrold M. Ward, Kenneth H. Ban, Nancy A. Jenkins, Neal G. Copeland, Brandon J. Wainwright

Abstract

The Sleeping Beauty (SB) transposon mutagenesis screen is a powerful tool to facilitate the discovery of cancer genes that drive tumorigenesis in mouse models. In this study, we sought to identify genes that functionally cooperate with sonic hedgehog signaling to initiate medulloblastoma (MB), a tumor of the cerebellum. By combining SB mutagenesis with Patched1 heterozygous mice (Ptch1(lacZ/+)), we observed an increased frequency of MB and decreased tumor-free survival compared with Ptch1(lacZ/+) controls. From an analysis of 85 tumors, we identified 77 common insertion sites that map to 56 genes potentially driving increased tumorigenesis. The common insertion site genes identified in the mutagenesis screen were mapped to human orthologs, which were used to select probes and corresponding expression data from an independent set of previously described human MB samples, and surprisingly were capable of accurately clustering known molecular subgroups of MB, thereby defining common regulatory networks underlying all forms of MB irrespective of subgroup. We performed a network analysis to discover the likely mechanisms of action of subnetworks and used an in vivo model to confirm a role for a highly ranked candidate gene, Nfia, in promoting MB formation. Our analysis implicates candidate cancer genes in the deregulation of apoptosis and translational elongation, and reveals a strong signature of transcriptional regulation that will have broad impact on expression programs in MB. These networks provide functional insights into the complex biology of human MB and identify potential avenues for intervention common to all clinical subgroups.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 2%
Czechia 1 1%
Unknown 85 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 33%
Researcher 21 24%
Student > Bachelor 9 10%
Student > Master 7 8%
Student > Doctoral Student 5 6%
Other 5 6%
Unknown 12 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 36%
Medicine and Dentistry 16 18%
Biochemistry, Genetics and Molecular Biology 12 14%
Computer Science 4 5%
Neuroscience 4 5%
Other 8 9%
Unknown 12 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 46. 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 August 2014.
All research outputs
#861,231
of 24,625,114 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#13,865
of 101,438 outputs
Outputs of similar age
#7,759
of 218,725 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#176
of 948 outputs
Altmetric has tracked 24,625,114 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 101,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.8. This one has done well, scoring higher than 86% 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 218,725 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 948 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.