A good internal control is critical in all quantitative analyses of gene expression. Levels of bet-actin, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and peptidylprolyl isomerase A (PPIA) were analyzed in 78 samples (data obtained from our laboratory and from a publicly available database at http://www.ncbi.nlm.nih.gov/SAGE/). These libraries included cell lines and tissues from brain, breast, colon, kidney, ovary, pancreas, prostate, skin, and vascular origin. The level of PPIA mRNA is the most constant among the three genes. Hence, our study suggests that PPIA is a better internal control than beta-actin or GAPDH, the two most commonly used internal controls.

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Prostate cancer is the most diagnosed cancer and the second leading cause of cancer death among men in the United States. Ability to detect this cancer early and availability of better prognostic markers are critical in order to decrease morbidity and mortality of prostate cancer. With the recent development in gene expression analysis methodology, expression profiles of thousands of genes can be generated in tissue samples and cell lines. Comparison of the global gene expression patterns between normal prostate and tumors at different stages may allow us to understand better the molecular mechanism of prostate tumorigenesis and progression. Different cancer cell lines and tissues appear to have different gene expression patterns that provide a new tool to classify tumors. Molecular classification of prostate cancer holds great promise for early detection and prognosis of this disease in the future. In this review, we summarize some of the recent mRNA and protein expression profiling studies performed in prostate cancer. Further, we discuss the potential benefits and limitations of current profiling technology.