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Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma

Overview of attention for article published in Nature, July 2011
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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 (97th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Readers on

mendeley
537 Mendeley
citeulike
12 CiteULike
connotea
1 Connotea
Title
Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma
Published in
Nature, July 2011
DOI 10.1038/nature10351
Pubmed ID
Authors

Ryan D. Morin, Maria Mendez-Lago, Andrew J. Mungall, Rodrigo Goya, Karen L. Mungall, Richard D. Corbett, Nathalie A. Johnson, Tesa M. Severson, Readman Chiu, Matthew Field, Shaun Jackman, Martin Krzywinski, David W. Scott, Diane L. Trinh, Jessica Tamura-Wells, Sa Li, Marlo R. Firme, Sanja Rogic, Malachi Griffith, Susanna Chan, Oleksandr Yakovenko, Irmtraud M. Meyer, Eric Y. Zhao, Duane Smailus, Michelle Moksa, Suganthi Chittaranjan, Lisa Rimsza, Angela Brooks-Wilson, John J. Spinelli, Susana Ben-Neriah, Barbara Meissner, Bruce Woolcock, Merrill Boyle, Helen McDonald, Angela Tam, Yongjun Zhao, Allen Delaney, Thomas Zeng, Kane Tse, Yaron Butterfield, Inanç Birol, Rob Holt, Jacqueline Schein, Douglas E. Horsman, Richard Moore, Steven J. M. Jones, Joseph M. Connors, Martin Hirst, Randy D. Gascoyne, Marco A. Marra, Morin RD, Mendez-Lago M, Mungall AJ, Goya R, Mungall KL, Corbett RD, Johnson NA, Severson TM, Chiu R, Field M, Jackman S, Krzywinski M, Scott DW, Trinh DL, Tamura-Wells J, Li S, Firme MR, Rogic S, Griffith M, Chan S, Yakovenko O, Meyer IM, Zhao EY, Smailus D, Moksa M, Chittaranjan S, Rimsza L, Brooks-Wilson A, Spinelli JJ, Ben-Neriah S, Meissner B, Woolcock B, Boyle M, McDonald H, Tam A, Zhao Y, Delaney A, Zeng T, Tse K, Butterfield Y, Birol I, Holt R, Schein J, Horsman DE, Moore R, Jones SJ, Connors JM, Hirst M, Gascoyne RD, Marra MA

Abstract

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis.

Twitter Demographics

The data shown below were collected from the profiles of 24 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 537 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 2%
United Kingdom 9 2%
Germany 8 1%
Canada 5 <1%
Netherlands 4 <1%
Denmark 3 <1%
China 3 <1%
France 2 <1%
Italy 2 <1%
Other 9 2%
Unknown 480 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 158 29%
Student > Ph. D. Student 142 26%
Student > Master 52 10%
Professor > Associate Professor 39 7%
Student > Bachelor 30 6%
Other 116 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 286 53%
Medicine and Dentistry 140 26%
Biochemistry, Genetics and Molecular Biology 66 12%
Computer Science 8 1%
Chemistry 8 1%
Other 29 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 38. 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 10 February 2017.
All research outputs
#248,221
of 8,454,018 outputs
Outputs from Nature
#14,196
of 48,191 outputs
Outputs of similar age
#1,917
of 73,391 outputs
Outputs of similar age from Nature
#262
of 885 outputs
Altmetric has tracked 8,454,018 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 48,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 75.1. This one has gotten more attention than average, scoring higher than 70% 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 73,391 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 97% of its contemporaries.
We're also able to compare this research output to 885 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 70% of its contemporaries.