Bioinformatics approaches to cancer gene discovery.
The Cancer Gene Anatomy Project (CGAP) database of the National Cancer Institute has thousands of known and novel expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Data-mining the CGAP database led to the identification of ESTs that were predicted to be specific to select solid tumors. Two genes from these efforts were taken to proof of concept for diagnostic and therapeutics indications of cancer. Microarray technology was used in conjunction with bioinformatics to understand the mechanism of one of the targets discovered. These efforts provide an example of gene discovery by using bioinformatics approaches. The strengths and weaknesses of this approach are discussed in this review.
Narayanan
Ramaswamy
R
Center for Molecular Biology and Biotechnology, Department of Biology, Florida Atlantic University, Boca Raton, Fl, USA.
D051792:Basic Helix-Loop-Helix Proteins / Q000235:genetics; D003110:Colonic Neoplasms / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004314:Down Syndrome / Q000235:genetics; D020224:Expressed Sequence Tags; D052138:Genes, Neoplasm; D005819:Genetic Markers; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis
D051792:Basic Helix-Loop-Helix Proteins; D005819:Genetic Markers; C417032:SIM2 protein, human