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Assessing the activity of nonsense-mediated mRNA decay in lung cancer

Overview of attention for article published in BMC Medical Genomics, September 2017
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1 tweeter

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Title
Assessing the activity of nonsense-mediated mRNA decay in lung cancer
Published in
BMC Medical Genomics, September 2017
DOI 10.1186/s12920-017-0292-z
Pubmed ID
Authors

Meng Wang, Peiwei Zhang, Yufei Zhu, Xiangyin Kong, Zhenguo Zhang, Landian Hu, Meng Wang, Peiwei Zhang, Yufei Zhu, Xiangyin Kong, Zhenguo Zhang, Landian Hu

Abstract

Inhibition of nonsense-mediated mRNA decay (NMD) in tumor cells can suppress tumor growth through expressing new antigens whose mRNAs otherwise are degraded by NMD. Thus NMD inhibition is a promising approach for developing cancer therapies. Apparently, the success of this approach relies on the basal NMD activity in cancer cells. If NMD is already strongly inhibited in tumors, the approach would not work. Therefore, it is crucial to assess NMD activity in cancers to forecast the efficacy of NMD-inhibition based therapy. Here we develop three metrics using RNA-seq data to measure NMD activity, and apply them to a dataset consisting of 72 lung cancer (adenocarcinoma) patients. We show that these metrics have good correlations, and that the NMD activities in adenocarcinoma samples vary among patients: some cancerous samples show significantly stronger NMD activities than the normal tissues while some others show the opposite pattern. The variation of NMD activities among these samples may be partly explained by the varying expression of NMD effectors. In sum, NMD activity varies among lung cancerous samples, which forecasts varying efficacies of NMD-inhibition based therapy. The developed metrics can be further used in other cancer types to assess NMD activity.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 4 17%
Student > Bachelor 2 8%
Student > Doctoral Student 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 6 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 46%
Agricultural and Biological Sciences 2 8%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Unspecified 1 4%
Medicine and Dentistry 1 4%
Other 0 0%
Unknown 8 33%

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 07 September 2017.
All research outputs
#9,374,379
of 11,727,438 outputs
Outputs from BMC Medical Genomics
#428
of 537 outputs
Outputs of similar age
#193,350
of 263,887 outputs
Outputs of similar age from BMC Medical Genomics
#8
of 9 outputs
Altmetric has tracked 11,727,438 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 537 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.