Application of expression genomics in drug development and genomic medicine
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AbstractExpressed sequence tags and genome sequencing have virtually uncovered all the genes and transcripts in the human genome. Functional genomic analysis of these genes will undoubtedly reveal their physiological roles in cells in the near future. Coupled with the advent of DNA microarray, cellular response to perturbation can now be examined at genome-wide levels in a single analysis, yielding clues to the network of pathways and interacting pathways that underlie a comprehensive systems response to exposure to small molecule perturbants. This post-genomic information will be the foundation for knowledge-based in silico systems biology. It is envisioned that querying such relational databases will generate testable hypotheses as well as revealing information on networks of regulatory genes and pathways that could further fuel and shape molecular and drug target discovery, and ushering in a new era in genomic medicine. In this review, we will first discuss examples of laboratory results generated from high-throughput microarray analyses that illuminated previously unrecognized networks of regulatory genes and pathways that point to the mechanisms of action for the tumor promoter 12-O-tetradecanoyl-phorbol-13-acetate, and the green tea polyphenol, epi-gallocatechin gallate. We will then focus on the application of gene expression profiles in genomic medicine for predicting treatment response in cancer, using clinical specimens obtained from patients. These studies and others point to an increasing trend in modern biology in which high-throughput genome scale comprehensive biological information is incorporated into databases for constructing and reconstructing pathways and networks of interacting pathways that constitute a physiological response to environmental perturbation at the organism or systems levels. (C) 2004 Wiley-Liss, Inc.
All Author(s) ListChin KV, Selvanayagam ZE, Vittal R, Kita T, Kudoh K, Yang CS, Wong YF, Cheung TH, Yeo W, Chung TKH, Lin Y, Liao J, Shih JWC, Yap SF, Lin AW
Journal nameDrug Development Research
Volume Number62
Issue Number2
Pages124 - 133
LanguagesEnglish-United Kingdom
Keywordsgenomic medicine; microarray; personalized; predictive; systems biology
Web of Science Subject CategoriesChemistry, Medicinal; CHEMISTRY, MEDICINAL; Pharmacology & Pharmacy; PHARMACOLOGY & PHARMACY

Last updated on 2020-30-11 at 01:02