ESTRO 36 Abstract Book

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S58 ESTRO 36 2017
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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. Lyons1, S. Walker2, S. McQuaid 1, S. Hynes3, D.
Mitchell 4, B. Pang5, G. Logan2, A. McCavigan2, D.
O'Rourke6, C. Davidson1, L. Knight2, A. Sheriff7, V. Berge8,
D. Neal9, H. Pandha10 , R. Watson11, M. Mason12, E. Kay13,
D. Harkin1, J. James 1, M. Salto-Tellez 1, R. Kennedy1, J.
O'Sullivan1, D. Waugh1
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. Zips1, A. Ernst1, R. Bares 2, P. Martus3, D.
Weckermann4, D. Schilling5, J. Bedke5, A. Stenzl5
1University Hospital Tübingen Eberhard Karls University
Tübingen, Radiation Oncology, Tübingen, Germany
2University Hospital Tübingen Eberhard Karls University
Tübingen, Nuclear Medicine and Clinical Molecular
Imaging, Tübingen, Germany
3University Hospital Tübingen Eberhard Karls University
Tübingen, Institute for Clinical Epidemiology and
Applied Biometry, Tübingen, Germany
4Klinikum Augsburg, Urology, Augsburg, Germany
5University 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.