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4. DPKK Workshop in Bonn/Königswinter 1.-2.12.2006

4. DPKK Workshop in Bonn/Königswinter 1.-2.12.2006. Quantitative multi-gene expression analyses on paired prostate tissue samples from radical prostatectomies and on artificial prostate biopsies. Susanne Füssel & Susanne Unversucht

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4. DPKK Workshop in Bonn/Königswinter 1.-2.12.2006

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  1. 4. DPKK Workshop in Bonn/Königswinter 1.-2.12.2006 Quantitative multi-gene expression analyses on paired prostate tissue samples from radical prostatectomies and on artificial prostate biopsies Susanne Füssel & Susanne Unversucht Axel Meye, Michael Haase, Andrea Lohse, Silke Tomasetti, Michael Fröhner, Uta Schmidt, Rainer Koch, Gustavo Baretton, Manfred. P. Wirth Dept. of Urology & Institute of Medical Informatics and Biometry & Institute of Pathology Technical University of Dresden

  2. Objective • main problem: early identification of aggressive PCa for therapeutic decisions • need for new additional PCa-markers to improve diagnostic and prognostic power • quantification of transcript markers as promising tool • expression signatures more reliable than single markers

  3. Material & Methods • establishment of standardized QPCR-assays • 1. study: 9 PCa-related genes + 4 housekeeping genes • 2. study: 4 new PCa-related genes, TBP as reference gene • 169 paired tissue samples (Tu + Tf) from RPE explants • evaluation of single & combined markers (ROC-analyses) • mathematical models for PCa-specific transcript signatures • aim: prediction of PCa-presence and tumor extension using minimal tissue specimens (prostate biopsies)

  4. Evaluation of single markers: overexpression in PCa? PCA3 (=DD3), AMACR, PSGR, hepsin, TRPM8 & PSMA  most promising PCa transcript markers

  5. predicted probability of tumor AUC = 0.893 (95% CI 0.756 ... 1.000) 1- Specificity 1. Study: optimized 4-gene-model for PCa-prediction: EZH2 + PCA3 + prostein + TRPM8 • classification of relative expression levels of these 4 genes according optimized cut-offs  logit-value for each tissue sample (Tu and Tf) • logit-model 1: p = exp(logit)/[1+exp(logit)]  probability (p) of PCa presence in the analyzed tissue samples (Tf and Tu) median p Tu 0.81 Tf 0.21 ROC-analysis of the 4-gene-combination • correctly predicted: • with p0.7 for Tu : 70 % of Tu-samples • with p0.3 for Tf : 73 % of Tf-samples • sensitivity 79.3% & specificity 84.0%

  6. predicted probability of tumor AUC = 0.94 (95% CI 0.79 ... 1.00) 1- Specificity 2. Study: optimized 8-gene-model for PCa-prediction: AMACR + AR + EZH2 + hepsin + PCA3 + PDEF + prostein + TRPM8 • using log-transformed relative expression levelsof these 8 genes as continuous values  logit-value for each tissue sample (Tu and Tf) • 2. logit-model:p = exp(logit)/[1+exp(logit)] probability (p) of PCa presence in the analyzed tissue samples (Tf and Tu) median p Tu 0.93 Tf 0.07 ROC-analysis of the 8-gene-combination • correctly predicted: • with p0.7 for Tu : 78 % of Tu-samples • with p0.3 for Tf : 78 % of Tf-samples • sensitivity 89.3% & specificity 86.4%

  7. Dependence of marker expression on tumor stage: Discrimination between of organ-confined disease (OCD) and non- organ-confined disease (NOCD) for therapeutic decision? • comparison only of Tu-samples of OCD vs. NOCD or • comparison of TF-samples vs. Tu-samples of OCD vs. Tu-samples NOCD •  mathematical models for OCD-prediction in process

  8. Outlook • translation of the techniques to prostate biopsies •  additional diagnostic tools for better PCa-prediction? • correct prediction of tumor stage & aggressiveness •  RPE or not, adjuvant hormone therapy or CT or not • correlation of transcript signatures with outcome? •  follow-up needed for prognostic purposes • detection of PCa-specific transcripts in urine samples •  non-invasive tumor detection?

  9. Quantitative multi-gene expression analyses on artificial prostate needle core biopsies from radical prostatectomies • Aim: • transfer of techniques/ statistical models to artificial prostate biopsies from RPE explants •  additional diagnostic tools on minimal prostate • tissue samples •  11 selected PCa-related genes and TBP (reference) •  first results of application and validation of two • multi-gene-models for PCa prediction

  10. H&E-stained cuttings (PCa-patient: pT2a, pN0, pMx Gleason Score: 7 [3+4]) Tu-prostate tissue sample Tf-prostate tissue sample Artificial prostate needle core biopsies from radical prostatectomies • Material & methods: • artificial biopsies (11 patients): Tf/Tu from one RPE explant • snap-frozen in liquid nitrogen •  cryo-cuttings for RNA-isolation / pathological survey

  11. Artificial prostate needle core biopsies from radical prostatectomies Patient`s cohort: 11 patients with a primary PCa age: 51 to 71 years (median 66 years) serum PSA levels: 1.29 to 24.32 ng/ml (median 6.9 ng/ml) Histopathological examinations: (according to the UICC system) 7 patients (64%) with organ-confined disease (OCD; pT2) 4 patients (36%) with non organ-confined disease (NOCD; pT3/ pT4) Tumor grading: 2 patients with low grade (GS 2 to 6) 8 patients with intermediate grade (GS 7) and 1 patient with high grade (GS 8 to 10)

  12. Artificial prostate needle core biopsies from radical prostatectomies * n (Tu-specimens) = 25; n (Tf-specimens) = 10

  13. Artificial prostate needle core biopsies from radical prostatectomies Validation of two multi-gene models:

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