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Background: To discover prostate cancer biomarkers, we profiled gene expression in benign and malignant cells laser capture microdissected (LCM) from prostate tissues and metastatic prostatic adenocarcinomas. Here we present methods developed, optimized, and validated to obtain high quality gene expression data. Results: RNase inhibitor was included in solutions used to stain frozen tissue sections for LCM, which improved RNA quality significantly. Quantitative PCR assays, requiring minimal amounts of LCM RNA, were developed to determine RNA quality and concentration. SuperScript IITM reverse transcriptase was replaced with SuperScript IIITM, and SpeedVac concentration was eliminated to optimize linear amplification. The GeneChip® IVT labeling kit was used rather than the Enzo BioArrayTM HighYieldTM RNA transcript labeling kit since side-by-side comparisons indicated highend signal saturation with the latter. We obtained 72 μg of labeled complementary RNA on average after linear amplification of about 2 ng of total RNA. Conclusion: Unsupervised clustering placed 5/5 normal and 2/2 benign prostatic hyperplasia cases in one group, 5/7 Gleason pattern 3 cases in another group, and the remaining 2/7 pattern 3 cases in a third group with 8/8 Gleason pattern 5 cases and 3/3 metastatic prostatic adenocarcinomas. Differential expression of alpha-methylacyl coenzyme A racemase (AMACR) and hepsin was confirmed using quantitative PCR. Background Gene expression was profiled in prostate cells to discover candidate biomarkers for early detection of prostate cancer and assessment of cancer aggressiveness. Specific populations of benign and malignant cells were collected from frozen prostate tissues using laser capture microdisPublished: 21 March 2007 BMC Molecular Biology 2007, 8:25 doi:10.1186/1471-2199-8-25 Received: 30 September 2006 Accepted: 21 March 2007 This article is available from: http://www.biomedcentral.com/1471-2199/8/25 © 2007 Kube et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.