Narayanan Ramaswamy
Center for Molecular Biology and Biotechnology, Department of Biology, Florida Atlantic University, Boca Raton, Fl, USA.
Methods Mol Biol. 2007;360:13-31. doi: 10.1385/1-59745-165-7:13.
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.
美国国立癌症研究所的癌症基因解剖计划(CGAP)数据库拥有数千个已知和新的表达序列标签(EST)。这些EST来源于各种正常和肿瘤cDNA文库,为癌症基因发现提供了一个有吸引力的起点。对CGAP数据库进行数据挖掘,从而识别出预计对特定实体瘤具有特异性的EST。从这些研究中选取了两个基因,用于癌症诊断和治疗指征的概念验证。微阵列技术与生物信息学结合使用,以了解所发现的其中一个靶点的机制。这些研究提供了一个利用生物信息学方法进行基因发现的实例。本综述讨论了这种方法的优缺点。