Representational fragment amplification: exponential amplification of fragmented cDNA enables multimillion-fold expression testing.

lack of prostate specificity and intercellular localiza-tion of its gene product make this gene a poor serum biomarker. FN1 (fibronectin 1) and VEGF (vascular endo-thelial growth factor) are associated with prostate cancer and encode secreted proteins; however, these genes lack prostate-specific tissue specificity (15–18). The lack of prostate tissue specificity in the expression of these 2 genes may be a major reason why they are not yet used clinically as prostate cancer serum biomarkers. We have developed a bioinformatics protocol for screening candidate serum biomarker sets to identify high-quality markers for experimental evaluation. The in silico secreted protein pipeline provides a rapid screen for identifying biomarkers found extracellularly and is likely to be detectable by serum assays. Tissue specificity profiling compliments secreted protein prediction by identifying the originating tissue components of a biomarker's serum signal and by allowing investigators to select candidate markers with a higher probability of having distinguishable signals. We hope that the use of intelligent bioinformatics analysis before costly experimental evaluation will accelerate the selection of candidate biomarkers that can be successfully translated into novel, clinically useful, assays. Predicting transmem-brane protein topology with a hidden Markov model: application to complete genomes. systematic method for selection of promising serum protein biomarkers to improve prostate cancer (PCa i) detection. Clin Chem2006. Page information to be filled inXXXXXXX 7. Pruitt KD, Tatusova T, Maglott DR. NCBI Reference Sequence (RefSeq): A curated non-redundant sequence database of genomes, transcripts and proteins. Comprehensive gene expression analysis of prostate cancer reveals distinct transcriptional programs associated with metastatic disease. factor gene-460 C/T polymorphism is a biomarker for prostate cancer. Microarray analysis, which enables the comprehensive examination of many thousands of genes in a single experiment, is a promising method for furthering understanding of disease states. Because of the large amounts of probe required, however, microarray analysis has not Table 1. Localization predictions and annotations of prostate cancer-associated proteins. Gene annotation Localization prediction SwissProt localization Tissue specificity KLK3 (PSA) Secreted Secreted protein Primarily prostate ACPP Secreted No annotation Primarily prostate VEGF Secreted Secreted protein Ubiquitous FN1 Secreted Secreted protein Ubiquitous ZWINT Not secreted Nucleus Moderate a AMACR Not secreted Peroxisome mitochondrion Ubiquitous HPN Not secreted Type II membrane Moderate a We analyzed 7 genes by the secretion and specificity prediction methods described above. KLK3 and ACPP (positive controls) possess the secretion and prostate specificity characteristics that we describe as key for serum biomarkers. Negative controls include …