Prediction of gene function by genome-scale expression analysis: Prostate cancer-associated genes

We wish to identify genes associated with disease. To do so, we look for no vel genes whose expression patterns mimic those of known disease-associated genes, using a method we call Guilt-by-Association (CBA), on the basis of a combinatoric measure of association. Using GBA, we have examined the expr ession of 40,000 human genes in 522 cDNA libraries, and have discovered sev eral hundred previously unidentified genes associated with cancer, inflamma tion, steroid-synthesis, insulin-synthesis, neurotransmitter processing, ma trix remodeling, and other disease processes. The majority of the genes thu s discovered show no sequence similarity to known genes, and thus could not have been identified by homology searches. We present here an example of t he discovery of eight genes associated with prostate cancer. Of the 40,000 most-abundant human genes, these 8 are the most closely linked to the known diagnostic genes, and thus are prime targets for pharmaceutical research.