Cancer gene discovery using digital differential display

Abstract

The Cancer Gene Anatomy Project database of the National Cancer Institute has thousands of expressed sequences, both known and novel, in the form of expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Using a data-mining tool called Digital Differential Display (DDD) from the Cancer Gene Anatomy Project database, ESTs from six different solid tumor types (breast, colon, lung, ovary, pancreas, and prostate) were analyzed for differential expression. An electronic expression profile and chromosomal map position of these hits were generated from the Unigene database. The hits were categorized into major classes of genes including ribosomal proteins, enzymes, cell surface molecules, secretory proteins, adhesion molecules, and immunoglobulins and were found to be differentially expressed in these tumorderived libraries. Genes known to be up-regulated in prostate, breast, and pancreatic carcinomas were discovered by DDD, demonstrating the utility of this technique. Two hundred known genes and 500 novel sequences were discovered to be differentially expressed in these select tumor-derived libraries. Test genes were validated for expression specificity by reverse transcription-PCR, providing a proof of concept for gene discovery by DDD. A comprehensive database of hits can be accessed at http:// www.fau.edu/cmbb/publications/cancergenes. htm. This solid tumor DDD database should facilitate target identification for cancer diagnostics and therapeutics.