ESTRO 36 Abstract Book

S329 ESTRO 36 _______________________________________________________________________________________________

% and 64 % and I 5,30%

values between 22 % to 50 %.

functional impact, genes putatively regulated by the signature miRNAs were identified by correlation with global transcriptome data, followed by pathway analysis. Results We identified a prognostic 4-miRNA signature that was independent of MGMT promoter methylation status, age, and sex. A risk score was assigned to each patient that allowed defining two groups significantly differing in prognosis (p-value: 0.0001, median survival: 10.6 months and 15.1 months, hazard ratio = 3.8). The signature was technically validated by qRT-PCR and independently validated in an age- and sex-matched subset of standard- of-care treated patients of the TCGA GBM cohort (n=58). Pathway analysis suggested tumorigenesis-associated processes such as immune response, extracellular matrix organization, axon guidance, signalling by NGF, GPCR and Wnt. Conclusion In the present study, we describe the identification and independent validation of a 4-miRNA signature that allows stratification of GBM patients into different prognostic groups in combination with one defined threshold and set of coefficients. This miRNA signature could be utilized as diagnostic tool for the identification of GBM patients for improved and/or alternative treatment approaches. PO-0630 The role of mc4r gene polymorphisms in gbm patients treated with concomitant radio-chemotherapy M. Cantarella 1 , F. Pasqualetti 1 , A. Gonnelli 1 , P. Orlandi 2 , D. Giuliani 3 , D. Delishaj 1 , S. Montrone 1 , G. Coraggio 1 , E. Lombardo 1 , V. Simeon 4 , T. Di Desiderio 2 , A. Fioravanti 2 , M. Fabrini 1 , R. Danesi 2 , S. Guarini 3 , F. Paiar 1 , G. Bocci 2 1 Azienda Ospedaliero Universitaria Pisana, Radioterapia, Pisa, Italy 2 Azienda Ospedaliero Universitaria Pisana, Dipartimento di Medicina Clinica e Sperimentale Sezione di Farmacologia, Pisa, Italy 3 Università di Modena e Reggio Emilia, Dipartimento di Scienze Biomediche- Metaboliche e Neuroscienze Sezione di Farmacologia e Medicina Molecolare, Modena e Reggio Emilia, Italy 4 Istituto di Cura a Carattere Scientifico Basilicata, Laboratorio di ricerca preclinica e Traslazionale, Rionero in Vulture, Italy Purpose or Objective Melanocortins are peptides with well-recognized anti- inflammatory and neuroprotective activity. Melanocortin receptor-4 (MC4R) is present in astrocytes and it is expressed in the brain.. Given the association of MC4R with antiinflammatory activity, induction of neural stem/progenitor cell proliferation in brain hypoxia, and prevention of astrocyte apoptosis, the aim of this study was to evaluate the possible prognostic, predictive and therapeutic role of the MC4R SNPs on GBM patients. Material and Methods Sixty-one patients with a proven diagnosis of GBM, ECOG PS 0-2, age>18 years, and treated with radiotherapy and temozolomide according to Stupp protocol were enrolled. Genomic DNA was extracted and MC4R gene SNPs were analyzed; the allelic discrimination was performed using an ABI PRISM 7900 SDS (Applied Biosystems, Carlsbad, CA, USA) and with validated TaqMan ® SNP genotyping assays (Applied Biosystems). Kaplan Meier curves were performed for statistical association with genotypes. The study has been approved by the Comitato Etico di Area Vasta Nord Ovest prot. n. 17013. Results Fifty-six patients were clinically evaluated. The median progression-free survival (PFS) and median overall survival (OS) of these patients were 10.8 months and 23 months, respectively.. A relevant finding of our study was the identification of a MC4R genotype that was significantly associated with PFS: patients harbouring the rs489693 AA genotype had a median PFS of 3 months

Conclusion In this cohort, the comparison of GTV, GTV’ and V PET volumes suggests that 18 F-FDOPA PET images can be useful for predicting tumor recurrence areas in half of the patients with encouraging sensibility and sensitivity values. As a next step, ROC curves will be calculated to define the optimal SUV threshold for radiotherapy delineation purpose. The analysis of all post-treatment MR images will be conducted to better determine the starting points of the recurrence and correlate them to the 18 F- FDOPA PET information. PO-0629 A 4-miRNA signature predicts the therapeutic outcome of glioblastoma M. Niyazi 1,2,3 , A. Pitea 3,4 , M. Mittelbronn 5 , J. Steinbach 6 , C. Sticht 7 , F. Zehentmayr 1,8 , D. Piehlmaier 3,4 , H. Zitzelsberger 3,4 , K. Lauber 1,3 , U. Ganswindt 1,3 , C. Rödel 9 , C. Belka 1,2,3 , K. Unger 3,4 1 LMU Munich, Department of Radiation Oncology, Munich, Germany 2 German Cancer Research Center DKFZ, German Cancer Consortium DKTK, Heidelberg, Germany 3 Helmholtz Zentrum München, Clinical Cooperation Group Personalized Radiotherapy in Head and Neck Cancer, Munich, Germany 4 Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Research Unit Radiation Cytogenetics, Muenchen, Germany 5 Goethe-University Frankfurt, Institute of Neurology Edinger Institute, Frankfirt/Main, Germany 6 Klinikum der J.W. Goethe-Universität, Dr. Senckenbergisches Institut für Neuroonkologie, Frankfurt/Main, Germany 7 Medizinische Fakultät Mannheim, Zentrum für Medizinische Forschung, Mannheim, Germany 8 Paracelsus Medical University, Department of Radiation Oncology, Salzburg, Austria 9 University Hospital Frankfurt, Department of Radiation Oncology, Frankfurt/Main, Germany Purpose or Objective Inter-individual variability in terms of treatment outcome and benefit from standard of care treatment is a great challenge in the multimodal therapy of glioblastoma (GBM). In order to recognize patients with particularly poor prognosis a priori and assigning them to alternative treatment approaches, molecular signatures predicting outcome with higher accuracy would be helpful. In our study, we examined whether such a signature could be defined on the basis of miRNA expression analyses. Material and Methods FFPE sections of resected tumours from 36 standard-of- care treated GBM patients along with overall survival follow-up data were collected retrospectively and subjected to low-complexity signature identification from miRNA microarray data. Based on the expression of the signature miRNAs and cox-proportional hazard coefficients, a risk score was calculated and used for classification into higher- and lower-risk patients. The identified signature was validated in a miRNA array data set of a subset of the TCGA GBM cohort which was matched for sex, age and treatment. In order to assess the