ESTRO 37 Abstract book

S135

ESTRO 37

OC-0269 Comparison of tumour hypoxia measured by FMISO-PET and gene signatures for patients with HNSCC S. Löck 1,2,3 , A. Linge 1,2,3,4 , A. Seidlitz 1,2,4 , A. Bandurska- Luque 1,2,4 , M. Großer 5 , G. Baretton 3,4,5 , K. Zöphel 4,6 , D. Zips 7,8 , E. Troost 1,2,3,4,9 , M. Krause 1,2,3,4,9 , M. Baumann 1,2,3,10 1 OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden- Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany 2 Department of of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden, Dresden, Germany 3 German Cancer Consortium DKTK, partner site Dresden and German Cancer Research Center, Heidelberg, Germany 4 National Center for Tumor Diseases, partner site Dresden, Dresden, Germany 5 Institute of Pathology, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden, Dresden, Germany 6 Department of Nuclear Medicine, Faculty of Medicine and University Hospital Carl Gustav Carus- Technische Universität Dresden, Dresden, Germany 7 Department of Radiation Oncology, Eberhard Karls Universität Tübingen, Tübingen, Germany 8 German Cancer Consortium DKTK, partner site Tübingen and German Cancer Research Center, Heidelberg, Germany 9 Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology - OncoRay, Dresden, Germany 10 German Cancer Research Center, DKFZ, Heidelberg, Germany Purpose or Objective Tumour hypoxia is well known to increase radio- resistance of tumours. In a recent prospective biomarker imaging trial, hypoxia has been measured by [ 18 F]fluoromisonidazole positron emission tomography (FMISO-PET) scans [1,2]. Here, we compared hypoxia imaging with the expression of hypoxia-associated gene signatures for patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCHT). Material and Methods FMISO-PET imaging and gene expression analyses were performed on the cohort of 50 HNSCC patients [1,2]. For this study, the FMISO-PET parameters tumour-to- background ratio (TBR peak ) and hypoxic tumour volume (HV 1.6 ) analysed before RCHT were considered. Expressions of the 15-, 26- and 30-gene hypoxia- associated signatures [3-5] were analysed from formalin- fixed paraffin-embedded (FFPE) tumour biopsies obtained before RCHT using the GeneChip® Human Transcriptome Array 2.0 (Affymetrix) and nanoString analysis. Gene expressions were compared between the two methods using the Pearson correlation coefficient. Linear regression was applied to relate TBR peak and HV 1.6 to the mean expression of the gene signatures, including the interaction with tumour volume which was assessed on the planning CT by an experienced radiation oncologist. The association of FMISO-PET parameters and gene expressions to loco-regional control (LRC) and progression-free survival (PFS) was assessed by Cox regression. Results The mean expressions of all hypoxia-associated gene signatures were highly correlated between Affymetrix and nanoString analyses (R>0.5). While TBR peak and HV 1.6 were weakly correlated with the expression of hypoxia- associated genes alone, significant correlations were observed if the interaction term of gene expression and tumour volume was included (R>0.5). Both FMISO-PET parameters were significantly correlated with LRC and

PFS ( p <0.01), while the combination of hypoxia- associated gene expressions and their interaction with tumour volume showed a significant but weaker correlation for the 30-gene signature to LRC and for the 15- and 30-gene signature to PFS (p<0.05). The figure shows patient stratifications using HV 1.6 ( p =0.02), the 30- gene signature ( p =0.07) and their combination ( p <0.01). Conclusion Hypoxia imaging correlates with the expression of hypoxia-associated genes if the interaction of gene expression and tumour volume is included. Interestingly, both methods may complement each other, which may be of advantage for identifying patients who are at high risk of treatment failure and may benefit from dose escalation. While FMISO-PET directly measures hypoxia, the gene signatures are also associated with other radiobiologic phenomena such stemness of cancer cells.

[1] Zips et al. Radiother Oncol. 2012;105:21 [2] Löck et al. Radiother Oncol. 2017;124:533 [3] Toustrup et al. Cancer Res. 2011;71:5923 [4] Eustace et al. Clin Cancer Res. 2013;19:4879 [5] Lendahl et al. Nat Rev Genet. 2009;10:821

OC-0270 Imaging tumor hypoxia in prostate cancer patients by integration of multiparametric DW-MR images T. Hompland 1 , K. Hole 2 , H. Ragnum 1 , L. Vlatkovic 3 , T. Seierstad 2 , H. Lyng 1 1 Oslo University Hospital, Radiation Biology, Oslo, Norway 2 Oslo University Hospital, Department of Radiology and Nuclear Medicine, Oslo, Norway 3 Oslo University Hospital, Department of Pathology, Oslo, Norway Purpose or Objective In prostate cancer, tumor hypoxia has been ass ociated with resistance to both external radiation n and brachytherapy. A strategy to overcome the adverse effect of hypoxia could be to escalate radiation dose to the radioresistant hypoxic part of the tumor, termed hy poxia dose painting. However, no imaging tool to detect and display hypoxic tumor areas within the prostate is available for clinical use. In the present work, we propose a novel method to integrate images of oxygen consum ption and supply into a single hypoxia image. The method was developed on a cohort of prostate cancer patients based on diffusion weighted (DW)- magnetic resonance (MR) images acquired with different diffusion weighting (b-values). The hypoxia images were compared with immunostaining of the hypoxia marker pimonidazole in whole-mount sections of the prostate. Material and Methods Intermediate and high risk prostate cancer patients who were given pimonidazole 24 hours prior to prostatectomy were included. The DW-MR images were acquired on a 1.5T scanner using b-values from 0 to 1000 in steps of 10 0 and analyzed on a pixel-by-pixel basis with a modified bi-exponential intravoxel incoherent motion (IVIM) model. Two parameters were extracted, the fractional blood volume, fBV, and the apparent diffusion coefficient, ADC. To investigate the physiological background of the parameters, we quantified blood vessel density (BVD) and cell density (CD) by histological