A diagnostic test for prostate cancer from gene expression profiling data.

Purpose: Multiple recent studies show excellent classification accuracy using bioinformatics tools applied to expression profiling data on various tumors. However, the clinical applicability of these techniques remains unfulfilled because of difficulty in translating complex multigene mathematical algorithms into reproducible, platform independent tests. We recently developed a broadly applicable platform independent method based on simple ratios of gene expression to diagnose and predict outcome in cancer.