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A roadmap of constitutive NF-κB activity in Hodgkin lymphoma: Dominant roles of p50 and p52 revealed by genome-wide analyses

Overview of attention for article published in Genome Medicine, March 2016
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  • Above-average Attention Score compared to outputs of the same age (54th percentile)

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Title
A roadmap of constitutive NF-κB activity in Hodgkin lymphoma: Dominant roles of p50 and p52 revealed by genome-wide analyses
Published in
Genome Medicine, March 2016
DOI 10.1186/s13073-016-0280-5
Pubmed ID
Authors

Kivia A. P. de Oliveira, Eva Kaergel, Matthias Heinig, Jean-Fred Fontaine, Giannino Patone, Enrique M. Muro, Stephan Mathas, Michael Hummel, Miguel A. Andrade-Navarro, Norbert Hübner, Claus Scheidereit

Abstract

NF-κB is widely involved in lymphoid malignancies; however, the functional roles and specific transcriptomes of NF-κB dimers with distinct subunit compositions have been unclear. Using combined ChIP-sequencing and microarray analyses, we determined the cistromes and target gene signatures of canonical and non-canonical NF-κB species in Hodgkin lymphoma (HL) cells. We found that the various NF-κB subunits are recruited to regions with redundant κB motifs in a large number of genes. Yet canonical and non-canonical NF-κB dimers up- and downregulate gene sets that are both distinct and overlapping, and are associated with diverse biological functions. p50 and p52 are formed through NIK-dependent p105 and p100 precursor processing in HL cells and are the predominant DNA binding subunits. Logistic regression analyses of combinations of the p50, p52, RelA, and RelB subunits in binding regions that have been assigned to genes they regulate reveal a cross-contribution of p52 and p50 to canonical and non-canonical transcriptomes. These analyses also indicate that the subunit occupancy pattern of NF-κB binding regions and their distance from the genes they regulate are determinants of gene activation versus repression. The pathway-specific signatures of activated and repressed genes distinguish HL from other NF-κB-associated lymphoid malignancies and inversely correlate with gene expression patterns in normal germinal center B cells, which are presumed to be the precursors of HL cells. We provide insights that are relevant for lymphomas with constitutive NF-κB activation and generally for the decoding of the mechanisms of differential gene regulation through canonical and non-canonical NF-κB signaling.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 1%
Germany 1 1%
Unknown 68 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 19%
Student > Bachelor 8 11%
Student > Doctoral Student 7 10%
Researcher 7 10%
Student > Master 7 10%
Other 9 13%
Unknown 19 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 34%
Immunology and Microbiology 7 10%
Agricultural and Biological Sciences 7 10%
Medicine and Dentistry 4 6%
Nursing and Health Professions 3 4%
Other 5 7%
Unknown 20 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 March 2016.
All research outputs
#13,173,409
of 23,577,654 outputs
Outputs from Genome Medicine
#1,208
of 1,466 outputs
Outputs of similar age
#147,757
of 328,610 outputs
Outputs of similar age from Genome Medicine
#31
of 33 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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 328,610 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.