In silico identification of cancer genes by high throughput analyses / 西安交通大学学报(医学版)

ABSTRACT

Objective To identify potential candidate genes related to the cancerous phenotype by analyzing databases publicly available. Methods Using a data-mining tool called Digital Differential Display (DDD) from the Cancer Gene Anatomy Project database, ESTs from 17 different tumor types were analyzed for differential expression. Results We obtained 130 up-regulated and 159 down-regulated genes, most of which are related to cytoskeleton, ribosomal subunit, substance metabolism, cell cycle, signal conduction, transcription and translation. These genes appear most frequently on chromosome 12 but rarely on chromosome 21 and Y. Conclusion In silico identification is a high-throughput screening strategy. Our study may lay a foundation for identification of future caner markers and provide a new thought for screening strategy of cancer markers.