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A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer

Overview of attention for article published in BMC Medical Genomics, July 2016
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Mentioned by

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3 tweeters

Citations

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33 Dimensions

Readers on

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58 Mendeley
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Title
A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer
Published in
BMC Medical Genomics, July 2016
DOI 10.1186/s12920-016-0212-7
Pubmed ID
Authors

Hsiao-Rong Chen, David H. Sherr, Zhenjun Hu, Charles DeLisi

Abstract

The high cost and the long time required to bring drugs into commerce is driving efforts to repurpose FDA approved drugs-to find new uses for which they weren't intended, and to thereby reduce the overall cost of commercialization, and shorten the lag between drug discovery and availability. We report on the development, testing and application of a promising new approach to repositioning. Our approach is based on mining a human functional linkage network for inversely correlated modules of drug and disease gene targets. The method takes account of multiple information sources, including gene mutation, gene expression, and functional connectivity and proximity of within module genes. The method was used to identify candidates for treating breast and prostate cancer. We found that (i) the recall rate for FDA approved drugs for breast (prostate) cancer is 20/20 (10/11), while the rates for drugs in clinical trials were 131/154 and 82/106; (ii) the ROC/AUC performance substantially exceeds that of comparable methods; (iii) preliminary in vitro studies indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. We briefly discuss the biological plausibility of the candidates at a molecular level in the context of the biological processes that they mediate. Our method appears to offer promise for the identification of multi-targeted drug candidates that can correct aberrant cellular functions. In particular the computational performance exceeded that of other CMap-based methods, and in vitro experiments indicate that 5/5 candidates have therapeutic indices superior to that of Doxorubicin in MCF7 and SUM149 cancer cell lines. The approach has the potential to provide a more efficient drug discovery pipeline.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 28%
Student > Bachelor 9 16%
Researcher 8 14%
Student > Master 7 12%
Student > Doctoral Student 3 5%
Other 7 12%
Unknown 8 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 22%
Agricultural and Biological Sciences 9 16%
Computer Science 6 10%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Medicine and Dentistry 4 7%
Other 14 24%
Unknown 8 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 August 2016.
All research outputs
#3,837,600
of 8,150,076 outputs
Outputs from BMC Medical Genomics
#223
of 432 outputs
Outputs of similar age
#119,025
of 257,747 outputs
Outputs of similar age from BMC Medical Genomics
#15
of 28 outputs
Altmetric has tracked 8,150,076 research outputs across all sources so far. This one has received more attention than most of these and is in the 50th percentile.
So far Altmetric has tracked 432 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 44th percentile – i.e., 44% 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 257,747 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 50% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.