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Cancer based pharmacogenomics network supported with scientific evidences: from the view of drug repurposing.


ABSTRACT:

Background

Pharmacogenomics (PGx) as an emerging field, is poised to change the way we practice medicine and deliver health care by customizing drug therapies on the basis of each patient's genetic makeup. A large volume of PGx data including information among drugs, genes, and single nucleotide polymorphisms (SNPs) has been accumulated. Normalized and integrated PGx information could facilitate revelation of hidden relationships among drug treatments, genomic variations, and phenotype traits to better support drug discovery and next generation of treatment.

Methods

In this study, we generated a normalized and scientific evidence supported cancer based PGx network (CPN) by integrating cancer related PGx information from multiple well-known PGx resources including the Pharmacogenomics Knowledge Base (PharmGKB), the FDA PGx Biomarkers in Drug Labeling, and the Catalog of Published Genome-Wide Association Studies (GWAS). We successfully demonstrated the capability of the CPN for drug repurposing by conducting two case studies.

Conclusions

The CPN established in this study offers comprehensive cancer based PGx information to support cancer orientated research, especially for drug repurposing.

SUBMITTER: Wang L 

PROVIDER: S-EPMC4345035 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Cancer based pharmacogenomics network supported with scientific evidences: from the view of drug repurposing.

Wang Liwei L   Liu Hongfang H   Chute Christopher G CG   Zhu Qian Q  

BioData mining 20150225


<h4>Background</h4>Pharmacogenomics (PGx) as an emerging field, is poised to change the way we practice medicine and deliver health care by customizing drug therapies on the basis of each patient's genetic makeup. A large volume of PGx data including information among drugs, genes, and single nucleotide polymorphisms (SNPs) has been accumulated. Normalized and integrated PGx information could facilitate revelation of hidden relationships among drug treatments, genomic variations, and phenotype t  ...[more]

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