ESTRO 36 Abstract Book

S58 ESTRO 36 2017 _______________________________________________________________________________________________

remained associated with rising PSA after salvage RT after backward selection. Conclusion The results of the central pathology analyses reveal concordant results for seminal vesicle invasion, extraprostatic extension, positive surgical margin but lower agreement for Gleason Score. Largest diameter of carcinoma was found to be a potential prognostic factor for rising PSA after salvage RT. OC-0126 A gene expression assay to predict the risk of distant metastases in localized prostate cancer. S. Jain 1 , C. Lyons 1 , S. Walker 2 , S. McQuaid 1 , S. Hynes 3 , D. Mitchell 4 , B. Pang 5 , G. Logan 2 , A. McCavigan 2 , D. O'Rourke 6 , C. Davidson 1 , L. Knight 2 , A. Sheriff 7 , V. Berge 8 , D. Neal 9 , H. Pandha 10 , R. Watson 11 , M. Mason 12 , E. Kay 13 , D. Harkin 1 , J. James 1 , M. Salto-Tellez 1 , R. Kennedy 1 , J. O'Sullivan 1 , D. Waugh 1 1 Queen's University Belfast, Centre for Cancer Research and Cell Biology, Belfast, United Kingdom 2 Almac Diagnostics, Almac Diagnostics, Craigavon, United Kingdom 3 University Hospital Galway, Department of Pathology, Galway, Ireland 4 Belfast City Hospital, Northern Ireland Cancer Centre, Belfast, United Kingdom 5 National University Cancer Institute- SIngapore, Department of Pathology, Singapore, Singapore 6 Belfast City Hospital, Department of Pathology, Belfast, United Kingdom 7 Umea University, Department of Surgical and Perioperative Sciences- Urology and Andrology, Umea, Sweden 8 Oslo University Hospital, Department of Urology, Oslo, Norway 9 Cambridge Research Group, Uro-oncology Research Goup, Cambridge, United Kingdom 10 University of Surrey, Department of Microbial Sciences, Guildford, United Kingdom 11 University College Dublin, Conway Institute, Dublin, Ireland 12 Cardiff University, Wales Cancer Bank, Cardiff, United Kingdom 13 Beaumont Hospital, Centre for Systems Medicine, Dublin, Ireland Purpose or Objective Approximately 20% of patients with organ confined prostate cancer (PCa) will develop disease recurrence following radical treatment (surgery or external beam radiotherapy (EBRT)). We hypothesized that a molecular subgroup of early PCa may have metastatic potential at presentation, resulting in disease recurrence. Material and Methods Using unsupervised hierarchical clustering of gene expression from a PCa dataset we identified a novel molecular subgroup with a transcriptional profile similar to metastatic disease. We developed a 70 gene expression assay to prospectively identify patients within the subgroup from formalin fixed and paraffin embedded tissue (FFPE). Initial assessment found the assay to be prognostic in three independent publicly available prostatectomy datasets. We therefore assessed the prognostic value of the assay in FFPE clinical samples collected from multiple international sites. FFPE tumor resections and tumor biopsy specimens were obtained from 322 surgical patients and 248 patients treated with EBRT. Regions of highest Gleason grade were identified for macrodissection, RNA extraction and gene expression analysis. Samples were dichotomized as metastatic biology assay positive or negative using a pre- specified cut-off. The association of assay results with biochemical failure (BF) and distant metastases (DM) was tested on multivariate (MVA). Results

The assay was significantly associated with BF on MVA (HR 1.67 [1.16-2.38]; p=0.0059), (HR 2.26 [1.26-4.04]; p=0.0062) and DM on MVA (HR 3.39 [1.88-6.12]; p=0.0001), (HR 3.26 [1.27-8.30]; p=0.0137) for surgery and EBRT cohorts respectively. Importantly, in a combined model, the assay demonstrated additional information to the commonly used CAPRA clinical tool for prediction of DM, HR 2.72 [2.10-3.51]; p<0.0001, and HR 2.72 [1.42-5.20]; p=0.0026 (Prostate Metastatic Assay combined with CAPRA-S and CAPRA respectively). Conclusion The metastatic biology assay predicts BF and DM in PCa patients treated with surgery or EBRT. The assay may help to select patients at risk of metastatic disease for additional treatment aimed at preventing disease recurrence. OC-0127 Individualized prediction of nodal involvement based on Sentinel-node dissection of prostate cancer A.C. Müller 1 , D. Zips 1 , A. Ernst 1 , R. Bares 2 , P. Martus 3 , D. Weckermann 4 , D. Schilling 5 , J. Bedke 5 , A. Stenzl 5 1 University Hospital Tübingen Eberhard Karls University Tübingen, Radiation Oncology, Tübingen, Germany 2 University Hospital Tübingen Eberhard Karls University Tübingen, Nuclear Medicine and Clinical Molecular Imaging, Tübingen, Germany 3 University Hospital Tübingen Eberhard Karls University Tübingen, Institute for Clinical Epidemiology and Applied Biometry, Tübingen, Germany 4 Klinikum Augsburg, Urology, Augsburg, Germany 5 University Hospital Tübingen Eberhard Karls University Tübingen, Urology, Tübingen, Germany Purpose or Objective The risk of nodal involvement in prostate cancer can be estimated by the Roach formula. However, this formula was criticized to overestimate nodal involvement and to be based on the lesser accurate standard lymph node dissection. The aim of this study was the development of a new formula overcoming these limitations and to individualize the decision of pelvic treatment using current surgical techniques. Therefore the prediction of nodal involvement was based on patients after sentinel node (SN) dissection which is comparable to extended node dissection. Material and Methods Clinical data of 433 prostate cancer patients (>93.5% with MRI or CT staging) was used to develop a formula for prediction of nodal involvement which received SN dissection in the course of prostatectomy or staging before radiotherapy. Clinical parameters comprised TNM, Gleason score, percentage of biopsies, PSA level, d’Amico and NCCN risk grouping. The validation cohort included 414 patients of an academic hospital using the same SN-procedure, cross-sectional imaging was restricted to selected high risk patients. Results Available predictive nomograms (Briganti, Oldenburg), the Partin and Gancarczyk tables, the Roach formula and the MSKCC calculator were compared using ROC-curves. The best available nomogram was the Briganti nomogram (AUC=0.853+/-0.036 standard error). The formula was derived by logistic regression and test of relevant variables (cT-stage, PSA-level, Gleason score, positive cores) by ROC curves. The formula needs two variables: T- stage and percentage of positive cores. The formula is given in Fig.1 and can be easily applied by a spreadsheet analysis sheet. The developed formula reached an AUC of 0.863+/-0.034 standard error, which was comparable with the Briganti nomogram (AUC=0.853+/-0.036). The formula was validated by an additional data set of 414 patients. The AUC values were 0.665 for Briganti and 0.637 for our model.