↓ Skip to main content

Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits

Overview of attention for article published in Epigenetics & Chromatin, November 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
50 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Identification of activated enhancers and linked transcription factors in breast, prostate, and kidney tumors by tracing enhancer networks using epigenetic traits
Published in
Epigenetics & Chromatin, November 2016
DOI 10.1186/s13072-016-0102-4
Pubmed ID
Authors

Suhn Kyong Rhie, Yu Guo, Yu Gyoung Tak, Lijing Yao, Hui Shen, Gerhard A. Coetzee, Peter W. Laird, Peggy J. Farnham

Abstract

Although technological advances now allow increased tumor profiling, a detailed understanding of the mechanisms leading to the development of different cancers remains elusive. Our approach toward understanding the molecular events that lead to cancer is to characterize changes in transcriptional regulatory networks between normal and tumor tissue. Because enhancer activity is thought to be critical in regulating cell fate decisions, we have focused our studies on distal regulatory elements and transcription factors that bind to these elements. Using DNA methylation data, we identified more than 25,000 enhancers that are differentially activated in breast, prostate, and kidney tumor tissues, as compared to normal tissues. We then developed an analytical approach called Tracing Enhancer Networks using Epigenetic Traits that correlates DNA methylation levels at enhancers with gene expression to identify more than 800,000 genome-wide links from enhancers to genes and from genes to enhancers. We found more than 1200 transcription factors to be involved in these tumor-specific enhancer networks. We further characterized several transcription factors linked to a large number of enhancers in each tumor type, including GATA3 in non-basal breast tumors, HOXC6 and DLX1 in prostate tumors, and ZNF395 in kidney tumors. We showed that HOXC6 and DLX1 are associated with different clusters of prostate tumor-specific enhancers and confer distinct transcriptomic changes upon knockdown in C42B prostate cancer cells. We also discovered de novo motifs enriched in enhancers linked to ZNF395 in kidney tumors. Our studies characterized tumor-specific enhancers and revealed key transcription factors involved in enhancer networks for specific tumor types and subgroups. Our findings, which include a large set of identified enhancers and transcription factors linked to those enhancers in breast, prostate, and kidney cancers, will facilitate understanding of enhancer networks and mechanisms leading to the development of these cancers.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Student > Bachelor 8 16%
Student > Doctoral Student 6 12%
Student > Master 6 12%
Researcher 4 8%
Other 4 8%
Unknown 11 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 34%
Agricultural and Biological Sciences 12 24%
Nursing and Health Professions 2 4%
Medicine and Dentistry 2 4%
Immunology and Microbiology 1 2%
Other 4 8%
Unknown 12 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 12 November 2016.
All research outputs
#9,400,690
of 15,357,253 outputs
Outputs from Epigenetics & Chromatin
#341
of 447 outputs
Outputs of similar age
#157,885
of 291,320 outputs
Outputs of similar age from Epigenetics & Chromatin
#57
of 58 outputs
Altmetric has tracked 15,357,253 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 447 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 20th percentile – i.e., 20% 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 291,320 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.