Colorectal cancer drug target prediction using ontology-based inference and network analysis

Cui Tao, Jingchun Sun, W. Jim Zheng, Junjie Chen, Hua Xu

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Identification of novel drug targets is a critical step in drug development. Many recent studies have produced multiple types of data, which provides an opportunity to mine the relationships among them to predict drug targets. In this study, we present a novel integrative approach that combines ontology reasoning with network-assisted gene ranking to predict new drug targets. We utilized colorectal cancer (CRC) as a proof-of-concept use case to illustrate the approach. Starting from FDA-approved CRC drugs and the relationships among disease, drug, gene, pathway, and SNP in an ontology representing PharmGKB data, we inferred 113 potential CRC drug targets. We further prioritized these genes based on their relationships with CRC disease genes in the context of human protein-protein interaction networks. Thus, among the 113 potential drug targets, 15 were selected as the promising drug targets, including some genes that are supported by previous studies. Among them, EGFR, TOP1 and VEGFA are known targets of FDA-approved drugs. Additionally, CCND1 (cyclin D1), and PTGS2 (prostaglandin-endoperoxide synthase 2) have reported to be relevant to CRC or as potential drug targets based on the literature search. These results indicate that our approach is promising for drug target prediction for CRC treatment, which might be useful for other cancer therapeutics.

Original languageEnglish (US)
Article numberbav015
JournalDatabase : the journal of biological databases and curation
Volume2015
DOIs
StatePublished - 2015
Externally publishedYes

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Electric network analysis
colorectal neoplasms
Ontology
Colorectal Neoplasms
Genes
drugs
prediction
Pharmaceutical Preparations
Proteins
Oncology
genes
Protein Interaction Maps
neoplasms
new drugs
cyclins
protein-protein interactions
prostaglandin synthase
Gene Regulatory Networks
Neoplasm Genes
Cyclin D1

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Information Systems

Cite this

Colorectal cancer drug target prediction using ontology-based inference and network analysis. / Tao, Cui; Sun, Jingchun; Zheng, W. Jim; Chen, Junjie; Xu, Hua.

In: Database : the journal of biological databases and curation, Vol. 2015, bav015, 2015.

Research output: Contribution to journalArticle

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