Figure 1. Sandwich procedure developed for collection of specimens and direct comparison of morphological and molecular classification. doi:10.1371/journal.pone.0003617.g001 OAZ, ODC), using 3 neighbours and the correlation-based distance. This classification is statistically significant. In this work we paid the highest attention to realize the best possible quality of tissue sampling and characterization (Figure 1). This is absolutely required giving the high heterogeneity of a prostate cancer specimen. The combination of a ‘‘robust’’ and widely tested approach for statistical analysis of data with high quality specimen sampling allowed us to obtain the final validated result with a dataset of 66 specimens. The concordance between our gene signature classification and final pathological classification (CaP versus benign) obtained by the pathologist was (8065)%, with a sensitivity of (8166)% and a specificity of (7867)%. Tissue specimens that have been misclassified by the molecular method, with respect to pathological classification, are indicated in Table 1 (bold). We remark that in this case a Leave-One-Out cross validation has been considered, since with the N-fold procedure misclassifications of single samples may vary at each realization. With the same combination of genes we correctly sub-classified 84% of tumour specimens with regard of patient’s age, 71% with regard to final RP Gleason score and 42% with regard to PSA before RP (Table 2). The same signature did not perform well for classification with regard to TNM staging. Inter-laboratory validation methodology A second laboratory was participating in an inter-lab validation methodology. Each tissue specimen was analyzed individually, determinations were in duplicate wells and each experiment was run for 6 times in both independent laboratories, with Ct line set at the same value. Inter-laboratory variability was less than 1 cycle for each single determination. (data not shown). Such variability did not affect significantly final classification. Gene Signature Table 2. Final results of classification using the Nearest Neighbour (NN) classifier. DICHOTOMIES DISCRIMINATED % CORRECT CLASSIFICATION CaP vs Benign Age: #65 vs .65 Gleason score: ,7 vs $7 PSAtot (ng/mL): ,10 vs $10 ng/mL (8065) 84 71 42 The 10-fold cross validation procedure was used in order to estimate the mean performance of the signature and the confidence interval. CaP versus benign specimens were discriminated with (8065)% accuracy, (8166)% sensitivity and (7867)% specificity. The result is expressed as mean695% confidence interval, approximately corresponding to 2 standard deviations. doi:10.1371/journal.pone.0003617.t002 As little as 1 mg of cancer tissue within 20 mg of benign specimen was detected As shown in Table 1, the amount of cancer tissue was only 5% in 7/31 specimens (equal to 22.5% of total specimens; 6/7 have been correctly classified), and less than 15% in 13/31 specimens (equal to 42% of total specimens; 10/13 have been correctly classified). Therefore, the relative cancer tissue component accounted for only about 1–3 mg of tissue out of 20 mg total. Table 1 provides a complete list of the clinical cases from which each tissue specimen was obtained, also including clinical data, classification by the pathologist and percent of cancer cells present in the specimen, expressed as a mean value between the pre- and the post-RNA sections (see Figure 1). Discussion Identification of novel and accurate molecular biomarkers: the challenge The identification of novel and accurate biomarkers for reliable molecular diagnosis of CaP is a real challenge. Previous studies by DNA microarray have identified molecular signatures that significantly correlated with CaP progression [27] or grading [28], leading to identification of informative genes (sometimes with unknown functions) that are still awaiting further studies for elucidating their role in CaP progression [29]. Other successful studies resulted in molecular diagnosis of CaP, but they were only Figure 2. Relative gene expression (cancer versus benign) as a function of RP Gleason score. * p value,0.01 (t-test). White bars = Gleason score,7; Grey bars = Gleason score$7. Error bars represent the standard error of the mean. doi:10.1371/journal.pone.0003617.g002 PLoS ONE | www.plosone.org 4 October 2008 | Volume 3 | Issue 10 | e3617