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Gene expression profiling of the human natural killer cell response to Fc receptor activation: unique enhancement in the presence of interleukin-12

Overview of attention for article published in BMC Medical Genomics, October 2015
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  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
Gene expression profiling of the human natural killer cell response to Fc receptor activation: unique enhancement in the presence of interleukin-12
Published in
BMC Medical Genomics, October 2015
DOI 10.1186/s12920-015-0142-9
Pubmed ID
Authors

Amanda R. Campbell, Kelly Regan, Neela Bhave, Arka Pattanayak, Robin Parihar, Andrew R. Stiff, Prashant Trikha, Steven D. Scoville, Sandya Liyanarachchi, Sri Vidya Kondadasula, Omkar Lele, Ramana Davuluri, Philip R. O. Payne, William E. Carson

Abstract

Traditionally, the CD56(dim)CD16(+) subset of Natural Killer (NK) cells has been thought to mediate cellular cytotoxicity with modest cytokine secretion capacity. However, studies have suggested that this subset may exert a more diverse array of immunological functions. There exists a lack of well-developed functional models to describe the behavior of activated NK cells, and the interactions between signaling pathways that facilitate effector functions are not well understood. In the present study, a combination of genome-wide microarray analyses and systems-level bioinformatics approaches were utilized to elucidate the transcriptional landscape of NK cells activated via interactions with antibody-coated targets in the presence of interleukin-12 (IL-12). We conducted differential gene expression analysis of CD56(dim)CD16(+) NK cells following FcR stimulation in the presence or absence of IL-12. Next, we functionally characterized gene sets according to patterns of gene expression and validated representative genes using RT-PCR. IPA was utilized for biological pathway analysis, and an enriched network of interacting genes was generated using GeneMANIA. Furthermore, PAJEK and the HITS algorithm were employed to identify important genes in the network according to betweeness centrality, hub, and authority node metrics. Analyses revealed that CD56(dim)CD16(+) NK cells co-stimulated via the Fc receptor (FcR) and IL-12R led to the expression of a unique set of genes, including genes encoding cytotoxicity receptors, apoptotic proteins, intracellular signaling molecules, and cytokines that may mediate enhanced cytotoxicity and interactions with other immune cells within inflammatory tissues. Network analyses identified a novel set of connected key players, BATF, IRF4, TBX21, and IFNG, within an integrated network composed of differentially expressed genes in NK cells stimulated by various conditions (immobilized IgG, IL-12, or the combination of IgG and IL-12). These results are the first to address the global mechanisms by which NK cells mediate their biological functions when encountering antibody-coated targets within inflammatory sites. Moreover, this study has identified a set of high-priority targets for subsequent investigation into strategies to combat cancer by enhancing the anti-tumor activity of CD56(dim)CD16(+) NK cells.

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X Demographics

The data shown below were collected from the profiles of 5 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 70 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 25%
Researcher 10 14%
Student > Bachelor 7 10%
Student > Master 6 8%
Other 5 7%
Other 7 10%
Unknown 18 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 21%
Agricultural and Biological Sciences 13 18%
Immunology and Microbiology 12 17%
Medicine and Dentistry 8 11%
Computer Science 2 3%
Other 4 6%
Unknown 17 24%
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 26 April 2016.
All research outputs
#12,743,645
of 22,830,751 outputs
Outputs from BMC Medical Genomics
#426
of 1,223 outputs
Outputs of similar age
#121,137
of 279,238 outputs
Outputs of similar age from BMC Medical Genomics
#8
of 19 outputs
Altmetric has tracked 22,830,751 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 1,223 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 63% 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 279,238 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 56% of its contemporaries.
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 has gotten more attention than average, scoring higher than 57% of its contemporaries.