ESTRO 36 Abstract Book

S244 ESTRO 36 2017 _______________________________________________________________________________________________

Recent studies highlight the relevance of DNA repair defects in genome instability and tumour development. Little is known about the impact of DNA repair aberrations on patient prognosis or treatment outcome. However, new targeted treatment options, such as PARP inhibitors, can exploit these repair defects if present. Here we tested whether gene expression analysis could identify DNA repair defects, with the ultimate aim to determine an association with clinical outcome and identify patients for Mitomycin C (MMC) or PARP inhibitor olaparib hypersensitivity is a hallmark of functional homologous recombination (HR) or Fanconi anaemia (FA) pathway DNA repair defects. We determined whole transcriptome expression and sensitivity to MMC and olaparib in a panel of 28 patient derived head and neck squamous cell carcinoma (HNSCC) cell lines. Based on their sensitivity (IC50 values), cell lines were classified as Normal (N) , hypersensitive to both drugs ( MOS ) or hypersensitive to mitomycin C but not olaparib ( MS ). To esta blish a “DNA repair defect” signature, relevant genes were extracted by differential expression analysis and used as input to various machine learning algorithms. Performance was evaluated using 20 repetitions of 5-fold int ernal cross validation. Probabilities of defects calculated by these m odels were used in a multivariate cox proportional hazard model to determine their prognostic capacity in a cohort of 84 HNSCC tumours, treated with chemo-radiation, and the TCGA HNSCC cohort. Results Expression analysis of the three groups yielded genes enriched for targets of transcription factors involved in DNA damage response, including p53, demonstrating its relevance to the system under study. The random forest model performed best, achieving a high sensitivity of 0.91 and specificity of 0.86. We validated our model in the Cancer Genome Project dataset of drug sensitivities in cell lines. The predicted repair defected groups had significantly lower IC50 values for DNA damage inducing agents, including cisplatin (MS: p=5.9e-05; MOS: p=0.042). Encouraged by this data, we used our model in the patient data sets. Increased probabilities of DNA repair defects were associated with increased mortality, recurrence and disease progression in chemo-radiated patients with advanced tumours in our cohort (shown in figure) and with survival in the TCGA HNSCC cohort. targeted treatments. Material and Methods

associated with poorer outcome in patients, possibly a result of the impact on genomic instability.

Proffered Papers: Highlights of proffered papers

OC-0464 Validation of a fully automatic real-time liver motion monitoring method on a conventional linac J. Bertholet 1 , R. Hansen 1 , E.S. Worm 1 , J. Toftegaard 1 , H. Wan 2 , P.J. Parikh 2 , M. Høyer 1 , P.R. Poulsen 1 1 Aarhus University Hospital, Department of oncology, Aarhus C, Denmark 2 Washington University- School of Medicine, Department of Radiation Oncology, St-Louis, USA Purpose or Objective Intrafraction motion is a challenge for accurate liver radiotherapy delivery. Real-time treatment adaptation (gating, tracking) may mitigate the detrimental effects of motion, but requires reliable target motion monitoring. In this study, we develop and validate a framework for fully automatic monitoring of thoracic and abdominal tumors on a conventional linac by combining real-time marker segmentation in kV images with internal position estimation by an external correlation model (ECM). The validation is based on experiments and simulations using known external and internal motion for 10 liver SBRT patients. Material and Methods A fully automatic real-time motion monitoring framework was developed. The framework combines auto- segmentation of arbitrarily shaped implanted fiducial markers in CBCT projections and intra-treatment kV images with simultaneous streaming of an external optical motion signal. Fig. A illustrates the workflow: A pre- treatment CBCT is acquired with simultaneous recording of the motion of an external block on the abdomen. The markers are segmented in every CBCT projection and a 3D voxel model of each marker is generated. The 3D marker motion is estimated from the observed 2D motion and used to optimize an ECM of the 3D internal marker motion INT(t) as a function of the external motion EXT(t). During treatment, INT(t) is estimated from EXT(t) at 20Hz, while MV-scatter-free kV images are acquired every 3s during beam pauses. The markers are segmented in real-time using the ECM to determine the search area and projections of the 3D voxel model as templates. The ECM is continuously updated with the latest estimated 3D marker position. The method was validated using Calypso- recorded internal motion and simultaneous camera- recorded external motion of 10 liver SBRT patients. The validation included both experiments with a programmable motion stage and simulations hereof for the first patient as well as simulations for the remaining patients. The real-time estimated 3D motion was compared to the known tumor motion. For comparison, the position estimation error was also calculated without ECM updates. Results The segmentation rate was 90% with a mean 2D segmentation error of 1.5pixels. Fig. B compares the estimated and actual target motion for a portion of the phantom experiment for Patient 1. The simulations agreed with the experimental root-mean-square error within 0.4mm (Table 1). For all patients, the mean 3D root-mean- square error was 1.74mm with ECM updates and 2.47mm without ECM updates (Table 1).

Conclusion We developed a model that exposes DNA repair defects as it predicts hypersensitivity to DNA crosslinking agents caused by such defects in vitro . The model successfully predicted sensitivity in an independent dataset. We found that increased probabilities of DNA repair defects were