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

Database (Oxford). 2015 Mar 27:2015:bav015. doi: 10.1093/database/bav015. Print 2015.

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.

Publication types

  • Dataset
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents / chemistry*
  • Antineoplastic Agents / pharmacokinetics
  • Antineoplastic Agents / pharmacology
  • Colorectal Neoplasms / drug therapy
  • Colorectal Neoplasms / genetics
  • Colorectal Neoplasms / metabolism
  • Databases, Factual*
  • Drug Delivery Systems*
  • Drug Design*
  • Humans
  • Neoplasm Proteins* / genetics
  • Neoplasm Proteins* / metabolism

Substances

  • Antineoplastic Agents
  • Neoplasm Proteins