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Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation

Overview of attention for article published in Genome Medicine, July 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)

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6 X users

Citations

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38 Dimensions

Readers on

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47 Mendeley
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1 CiteULike
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Title
Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation
Published in
Genome Medicine, July 2016
DOI 10.1186/s13073-016-0328-6
Pubmed ID
Authors

Daniel Savic, Ryne C. Ramaker, Brian S. Roberts, Emma C. Dean, Todd C. Burwell, Sarah K. Meadows, Sara J. Cooper, Michael J. Garabedian, Jason Gertz, Richard M. Myers

Abstract

The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking. To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns. Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points. Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic targets for the treatment of various cancers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 19%
Researcher 9 19%
Student > Master 5 11%
Student > Bachelor 4 9%
Professor 4 9%
Other 8 17%
Unknown 8 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 32%
Biochemistry, Genetics and Molecular Biology 14 30%
Chemistry 3 6%
Medicine and Dentistry 2 4%
Immunology and Microbiology 2 4%
Other 3 6%
Unknown 8 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 July 2016.
All research outputs
#7,841,338
of 25,116,143 outputs
Outputs from Genome Medicine
#1,194
of 1,548 outputs
Outputs of similar age
#121,207
of 363,240 outputs
Outputs of similar age from Genome Medicine
#23
of 27 outputs
Altmetric has tracked 25,116,143 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,548 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one is in the 22nd percentile – i.e., 22% 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 363,240 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 65% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.