Excision of damaged bases from transcription intermediates by FPG/NEI superfamily DNA glycosylases

Oxidative lesions are abundant due to constant presence of reactive oxygen species in living cells. Repair of oxidative base lesions is initiated by DNA glycosylases. For example, bacterial Fpg and Nei DNA glycosylases excise oxidized purines and pyrimidines, respectively, from DNA. Their human homologs, NEIL1 and NEIL2, have been reported to show preference towards oxidized lesions in DNA bubbles. From these observations, it had been hypothesized that NEIL proteins may be involved in the repair of lesions in DNA bubbles generated during transcription. However, it is not presently clear how NEILs would behave on bubbles more closely resembling transcription intermediates (e. g., containing the RNA strand), and bacterial homologs Fpg and Nei had never been investigated with bubble substrates. We have studied excision of either 8-oxoguanine (8-oxoG) or 5,6-dihydrouracil (DHU) by E. coli Fpg and Nei and human NEIL1 and NEIL2 from single-strand oligonucleotides, perfect duplexes, bubbles with different number of unpaired bases (6 to 30), Dloops with DNA or RNA and from complexes with RNA polymerase. Fpg, NEIL1 and NEIL2 efficiently excised DHU located inside a bubble. Fpg and NEIL1 was generally more active than NEIL2 in excision of 8-oxoG from ssDNA and bubbles. Nei, on the other hand, was active only on DHU located in dsDNA (either perfect duplex or DNA/DNA D-loop). Fpg and NEIL1 also have shown activity in D-loops with RNA. The activity of Fpg was observed in pre-assembled transcriptional complexes with E. coli RNA polymerase and depended on the position of the lesion in the transcription bubble, possibly reflecting local accessibility of the lesion within the elongation complex

Dynamic and distributed adaptation of scalable multimedia content in a context-aware environment

C

Radiothérapie guidée par l'image du cancer de la prostate (vers l'intégration des déformations anatomiques)

Ce travail de thèse porte sur la quantification et la prise en compte des variations anatomiques en cours de radiothérapie guidée par l'image pour le cancer de la prostate. Nous proposons tout d'abord une approche basée population pour quantifier et analyser les incertitudes géométriques, notamment à travers des matrices de probabilité de présence de la cible en cours de traitement. Nous proposons ensuite une méthode d'optimisation des marges suivant des critères de couverture géométrique de la cible tumorale. Cette méthode permet d'obtenir des marges objectives associées aux différents types d'incertitudes géométriques et aux différentes modalités de repositionnement du patient. Dans un second temps, nous proposons une méthode d'estimation de la dose cumulée reçue localement par les tissus pendant un traitement de radiothérapie de la prostate. Cette méthode repose notamment sur une étape de recalage d'images de façon à estimer les déformations des organes entre les séances de traitement et la planification. Différentes méthodes de recalage sont proposées, suivant les informations disponibles (délinéations ou points homologues) pour contraindre la déformation estimée. De façon à évaluer les méthodes proposées au regard de l'objectif de cumul de dose, nous proposons ensuite la génération et l'utilisation d'un fantôme numérique reposant sur un modèle biomécanique des organes considérés. Les résultats de l'approche sont présentés sur ce fantôme numérique et sur données réelles. Nous montrons ainsi que l'apport de contraintes géométriques permet d'améliorer significativement la précision du cumul et que la méthode reposant sur la sélection de contraintes ponctuelles présente un bon compromis entre niveau d'interaction et précision du résultat. Enfin, nous abordons la question de l'analyse de données de populations de patients dans le but de mieux comprendre les relations entre dose délivrée localement et effets cliniques. Grâce au recalage déformable d'une population de patients sur une référence anatomique, les régions dont la dose est significativement liée aux événements de récidive sont identifiées. Il s'agit d'une étude exploratoire visant à terme à mieux exploiter l'information portée par l'intégralité de la distribution de dose, et ce en fonction du profil du cancer.This work deals with the quantification and the compensation of anatomical deformations during image-guided radiotherapy of prostate cancer. Firstly, we propose a population-based approach to quantify the geometrical uncertainties by means of coverage probability matrices of the target tumor during the treatment. We then propose a margins optimization method based on geometrical coverage criteria of the tumor target. This method provides rationnal margins models associated to the different geometrical uncertainties and patient repositioning protocols. Secondly, we propose a method to estimate the locally accumulated dose during the treatment. This method relies on a deformable image registration process in order to estimate the organ deformations between each treatment fraction and the planning. Different registration methods are proposed, using different level of user interactions (landmarks specification or delineations) to constrain the deformation estimation. In order to evaluate the performance of the proposed methods, we then describe the generation of a numerical phantom based on a biomechanical model. The results are presented for the numerical phantom and real clinical cases. We show that the benefit brought by the manual placement of some landmarks to constrain the registration represents a good compromise between the required interaction level and the dose estimation accuracy. Finally, we address the issue of the analysis of population data in order to better understand the relationship between the locally delivered dose and clinical effects. With deformable image registration of a population of patients on an anatomical template, regions whose dose is significantly associated with recurrence events are identified. This last part is an exploratory study aiming to better use the information carried by the entire distribution dose, and according to the cancer profile.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Dose Accumulation with CBCT Conversion in Head and Neck and Prostate

https://openworks.mdanderson.org/sumexp22/1052/thumbnail.jp

Quantification of the volumetric benefit of image-guided radiotherapy (IGRT) in prostate cancer: margins and presence probability map

International audiencePURPOSE: To quantify the prostate and seminal vesicles (SV) anatomic variations in order to choose appropriate margins including intrapelvic anatomic variations. To quantify volumetric benefit of image-guided radiotherapy (IGRT). PATIENTS AND METHODS: Twenty patients, receiving a total dose of 70 Gy in the prostate, had a planning CT scan and eight weekly CT scans during treatment. Prostate and SV were manually contoured. Each weekly CT scan was registered to the planning CT scan according to three modalities: radiopaque skin marks, pelvis bone or prostate. For each patient, prostate and SV displacements were quantified. 3D maps of prostate and SV presence probability were established. Volumes including minimal presence probabilities were compared between the three modalities of registration. RESULTS: For the prostate intrapelvic displacements, systematic and random variations and maximal displacements for the entire population were: 5mm, 2.7 mm and 16.5mm in anteroposterior axis; 2.7 mm, 2.4mm and 11.4mm in superoinferior axis and 0.5mm, 0.8mm and 3.3mm laterally. Margins according to van Herk recipe (to cover the prostate for 90% of the patients with the 95% isodose) were: 8mm, 8.3mm and 1.9 mm, respectively. The 100% prostate presence probability volumes correspond to 37%, 50% and 61% according to the registration modality. For the SV, these volumes correspond to 8%, 14% and 18% of the SV volume. CONCLUSIONS: Without IGRT, 5mm prostate posterior margins are insufficient and should be at least 8mm, to account for intrapelvic anatomic variations. Prostate registration almost doubles the 100% presence probability volume compared to skin registration. Deformation of SV will require either to increase dramatically margins (simple) or new planning (not realistic)

Biomechanical Modeling of Brain Shift During Neurosurgery

https://openworks.mdanderson.org/sumexp22/1051/thumbnail.jp

Prediction of Liver Regeneration Post-Radiotherapy Using Machine Learning and Deep Learning Models

Department of Imaging Physics Radiation Oncology Interventional Radiologyhttps://openworks.mdanderson.org/sumexp22/1136/thumbnail.jp

Magnetic Resonance-based Response Assessment and Dose Adaptation in Human Papilloma Virus Positive Tumors of the Oropharynx treated with Radiotherapy (MR-ADAPTOR): An R-IDEAL stage 2a-2b/Bayesian phase II trial.

Background Current standard radiotherapy for oropharynx cancer (OPC) is associated with high rates of severe toxicities, shown to adversely impact patients' quality of life. Given excellent outcomes of human papilloma virus (HPV)-associated OPC and long-term survival of these typically young patients, treatment de-intensification aimed at improving survivorship while maintaining excellent disease control is now a central concern. The recent implementation of magnetic resonance image - guided radiotherapy (MRgRT) systems allows for individual tumor response assessment during treatment and offers possibility of personalized dose-reduction. In this 2-stage Bayesian phase II study, we propose to examine weekly radiotherapy dose-adaptation based on magnetic resonance imaging (MRI) evaluated tumor response. Individual patient's plan will be designed to optimize dose reduction to organs at risk and minimize locoregional failure probability based on serial MRI during RT. Our primary aim is to assess the non-inferiority of MRgRT dose adaptation for patients with low risk HPV-associated OPC compared to historical control, as measured by Bayesian posterior probability of locoregional control (LRC).Methods Patients with T1-2 N0-2b (as per AJCC 7th Edition) HPV-positive OPC, with lymph node <3 cm and <10 pack-year smoking history planned for curative radiotherapy alone to a dose of 70 Gy in 33 fractions will be eligible. All patients will undergo pre-treatment MRI and at least weekly intra-treatment MRI. Patients undergoing MRgRT will have weekly adaptation of high dose planning target volume based on gross tumor volume response. The stage 1 of this study will enroll 15 patients to MRgRT dose adaptation. If LRC at 6 months with MRgRT dose adaptation is found sufficiently safe as per the Bayesian model, stage 2 of the protocol will expand enrollment to an additional 60 patients, randomized to either MRgRT or standard IMRT.Discussion Multiple methods for safe treatment de-escalation in patients with HPV-positive OPC are currently being studied. By leveraging the ability of advanced MRI techniques to visualize tumor and soft tissues through the course of treatment, this protocol proposes a workflow for safe personalized radiation dose-reduction in good responders with radiosensitive tumors, while ensuring tumoricidal dose to more radioresistant tumors. MRgRT dose adaptation could translate in reduced long term radiation toxicities and improved survivorship while maintaining excellent LRC outcomes in favorable OPC.Trial registration ClinicalTrials.gov ID: NCT03224000; Registration date: 07/21/2017