ESTRO 36 Abstract Book

S538 ESTRO 36 _______________________________________________________________________________________________

Results Among the 14 cell lines analyzed, strong differences in clonogenic survival were observed. Using the linear- quadratic model, very high goodness-of-fit levels were obtained (R 2 ≥0.98). However, obvious differences in radiosensitivity between several cell lines were not revealed by the respective α/β values which failed to reflect the overall steepness of survival curves. Data reduction by PCA allowed the extraction of radioresistance scores. Notably, more than 70% of the variance in the dataset was covered by the first PC. Correlation of radioresistance scores with mRNA expression levels of DDR regulators identified potential predictors of radioresistance. Target validation using RNA interference and selection of suitable pharmacological inhibitors are ongoing. Conclusion Dimensionality reduction by PCA is a suitable method to extract scores of radioresistance from clonogenic survival datasets which can be correlated with other types of data, such as mRNA expression levels. This approach facilitates the identification of DDR regulators which may be further validated as potential biomarkers of radioresistance and/or targets for radiosensitization. PO-0974 Biomarkers of radiosensitivity for patient stratification and personalized radiotherapy treatment E. Palumbo 1 , C. Piotto 1 , L. Baggio 1 , E. Groff 1 , E. Calura 2 , F. Busato 1 , B. El Khouzai 1 , E. Fasanaro 1 , M. Rigo 1 , L. Loreggian 1 , C. Romualdi 2 , A. Russo 3 , M. Mognato 2 , D. Zafiropoulos 4 , L. Corti 1 1 Istituto Oncologico Veneto IOV-IRCCS, UOC of Radiotherapy, Padua, Italy 2 University of Padua, Department of Biology, Padova, Italy 3 University of Padua, Department of Molecular Medicine, Padova, Italy 4 National Laboratories of Legnaro- Italian Institute of Nuclear Physics, LNL-INFN, Padua, Italy Purpose or Objective The personalization of radiotherapy (RT) represents the goal of future clinical radiation trials. A screening tool able to classify each patient according to his/her own sensitivity to ionizing radiation (IR) before the administration of RT would be essential to set personalized dosing schedules, effective in improving RT outcomes and in reducing side effects. Genetic variation is a likely source for the normal tissue radiosensitivity variation observed among individuals. Mutations in key genes of the DNA-Damage Response (DDR) pathway, or the individual modulation of DDR gene expression after IR- exposure, may underlie these differences. This study aims at defining a genetic signature useful to discriminate patients undergoing RT as radiosensitive, normal and radioresistant and to predict the likelihood of a late IR- toxicity. In this frame, gene expression data concerning DDR pathway, obtained from blood samples of breast and head-neck cancer patients, are overlaid with the individual in vitro radiosensitivity index and the in vivo tissue radiosensitivity detected during the follow-up. We expect to identify a 5-10 gene network determining the individual radiophenotype. Material and Methods 1. Criteria for patient enrolling: breast or head-neck cancer diagnosis; exclusion of congenital syndromes predisposing to radiosensitivity; patients not previously treated with chemo-radiotherapy; age > 18 years; patient agreement to undergo follow-up; informed consent. 2. G2- assay for the prediction of radiosensitivity: an individual radiosensitivity index (IRS) is calculated according to the G2-chromosomal radiosensitivity and the G2 checkpoint efficiency. Details of the protocol are in 1 . 3. Gene expression analysis: Gene expression analysis is performed by quantitative real-time PCR (qRT-PCR) on total RNA

Conclusion Our preliminary results suggest that the use of FFF beams does not influence cancer cell survival rate when compared with standard flattened beams. The effects of higher dose per fraction have to be further investigated. PO-0973 Dimensionality reduction of clonogenic survival data to identify candidates for radiosensitization N. Brix 1 , R. Hennel 1 , C. Belka 1 , K. Lauber 1 1 LMU University Hospital Grosshadern, Department of Radiation Oncology, Munich, Germany Purpose or Objective With approximately 70,000 new cases per year in Germany, breast cancer is the most common malignancy in women. Together with surgery and chemotherapy, the majority of patients is undergoing radiotherapy. While stratification by clinicopathological parameters – such as hormone receptor and Her2 expression – is part of the clinical routine, biomarkers for tumor radioresistance and targets for radiosensitization are currently not available. The colony formation assay represents a versatile tool to analyze cellular radiosensitivity in vitro making it indispensable for the identification of factors involved in tumor cell radioresistance. As an alternative to the linear- quadratic model, we propose a novel approach of dimensionality reduction to fully exploit the information obtained from clonogenic survival assays which allows, for instance, correlation with gene expression data. Material and Methods Clonogenic survival of 13 breast cancer cell lines and normal human mammary epithelial cells upon irradiation with 0-8 Gy was analyzed in colony formation assays. The data derived thereof were subjected to linear-quadratic fitting and principal component analysis (PCA) to extract scores of radioresistance for each cell line. Next, mRNA expression levels of more than 40 DNA damage response (DDR) regulators were measured by qRT- PCR. In order to identify predictors of radioresistance and potential targets for radiosensitization, mRNA expression levels were correlated with the PCA-derived radioresistance scores.