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Decrypting the PAK4 transcriptome profile in mammary tumor forming cells using Next Generation Sequencing

Overview of attention for article published in Genomics, October 2017
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Article details
Title
Decrypting the PAK4 transcriptome profile in mammary tumor forming cells using Next Generation Sequencing
Published in
Genomics, October 2017
DOI 10.1016/j.ygeno.2017.10.004
Pubmed ID
Authors
Abstract

The p-21 Activated Kinase 4 (PAK4) protein kinase is implicated in many cancers, including breast cancer. Overexpression of PAK4 is sufficient to cause mouse mammary epithelial cells (iMMECs) to become tumorigenic. To gain insight into the long-term gene expression changes that occur downstream to PAK4, we performed Next Generation Sequencing of RNA collected from PAK4 overexpressing iMMECs and wild-type iMMECs. We identified a list of genes whose expression levels were altered in response to PAK4 overexpression in iMMECs. Some of these genes, including FoxC2 and ParvB, are consistent with a role for PAK4 in cancer. In addition, PAK4 regulates many genes that are frequently associated with the inflammatory response, raising the possibility that there is a connection between PAK4, inflammation, and the tumor microenvironment. This study delineates the PAK4 transcriptome profile in transformed mammary cells and can provide translational utility in other types of cancers as well.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Researcher 2 15%
Other 1 8%
Student > Bachelor 1 8%
Student > Master 1 8%
Other 1 8%
Unknown 4 31%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 38%
Agricultural and Biological Sciences 3 23%
Medicine and Dentistry 1 8%
Unknown 4 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 October 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Genomics
#5,277
of 5,923 outputs
Outputs of similar age
#245,993
of 336,554 outputs
Outputs of similar age from Genomics
#11
of 19 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,923 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 9th percentile – i.e., 9% 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 336,554 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.