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Integrating subpathway analysis to identify candidate agents for hepatocellular carcinoma

Overview of attention for article published in OncoTargets and therapy, March 2016
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Title
Integrating subpathway analysis to identify candidate agents for hepatocellular carcinoma
Published in
OncoTargets and therapy, March 2016
DOI 10.2147/ott.s97211
Pubmed ID
Authors

Jiye Wang, Mi Li, Yun Wang, Xiaoping Liu

Abstract

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-associated death worldwide, characterized by a high invasiveness and resistance to normal anticancer treatments. The need to develop new therapeutic agents for HCC is urgent. Here, we developed a bioinformatics method to identify potential novel drugs for HCC by integrating HCC-related and drug-affected subpathways. By using the RNA-seq data from the TCGA (The Cancer Genome Atlas) database, we first identified 1,763 differentially expressed genes between HCC and normal samples. Next, we identified 104 significant HCC-related subpathways. We also identified the subpathways associated with small molecular drugs in the CMap database. Finally, by integrating HCC-related and drug-affected subpathways, we identified 40 novel small molecular drugs capable of targeting these HCC-involved subpathways. In addition to previously reported agents (ie, calmidazolium), our method also identified potentially novel agents for targeting HCC. We experimentally verified that one of these novel agents, prenylamine, induced HCC cell apoptosis using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, an acridine orange/ethidium bromide stain, and electron microscopy. In addition, we found that prenylamine not only affected several classic apoptosis-related proteins, including Bax, Bcl-2, and cytochrome c, but also increased caspase-3 activity. These candidate small molecular drugs identified by us may provide insights into novel therapeutic approaches for HCC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 33%
Student > Doctoral Student 1 11%
Lecturer 1 11%
Student > Master 1 11%
Student > Ph. D. Student 1 11%
Other 0 0%
Unknown 2 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 33%
Pharmacology, Toxicology and Pharmaceutical Science 1 11%
Agricultural and Biological Sciences 1 11%
Immunology and Microbiology 1 11%
Medicine and Dentistry 1 11%
Other 0 0%
Unknown 2 22%
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 30 March 2016.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from OncoTargets and therapy
#2,078
of 3,016 outputs
Outputs of similar age
#269,142
of 312,604 outputs
Outputs of similar age from OncoTargets and therapy
#75
of 108 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,016 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 108 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.