TY  - JOUR
A1  - Hardcastle, Nicholas
A1  - Tomé, Wolfgang A.
A1  - Cannon, Donald M.
A1  - Brouwer, Charlotte L.
A1  - Wittendorp, Paul W. H.
A1  - Dogan, Nesrin
A1  - Guckenberger, Matthias
A1  - Allaire, Stéphane
A1  - Mallya, Yogish
A1  - Kumar, Prashant
A1  - Oechsner, Markus
A1  - Richter, Anne
A1  - Song, Shiyu
A1  - Myers, Michael
A1  - Polat, Bülent
A1  - Bzdusek, Karl
T1  - A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy
JF  - Radiation Oncology
N2  - Background: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. 
Methods: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility. 
Results: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits. 
Conclusion: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.
KW  - intensity-modulated radiotherapy
KW  - megavoltage computed-tomography
KW  - cancer
KW  - variability
KW  - strategies
KW  - risk
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-134756
VL  - 7
IS  - 90
ER  - 
TY  - JOUR
A1  - Fischer, Thomas
A1  - Hartmann, Oliver
A1  - Reissland, Michaela
A1  - Prieto-Garcia, Cristian
A1  - Klann, Kevin
A1  - Pahor, Nikolett
A1  - Schülein-Völk, Christina
A1  - Baluapuri, Apoorva
A1  - Polat, Bülent
A1  - Abazari, Arya
A1  - Gerhard-Hartmann, Elena
A1  - Kopp, Hans-Georg
A1  - Essmann, Frank
A1  - Rosenfeldt, Mathias
A1  - Münch, Christian
A1  - Flentje, Michael
A1  - Diefenbacher, Markus E.
T1  - PTEN mutant non-small cell lung cancer require ATM to suppress pro-apoptotic signalling and evade radiotherapy
JF  - Cell & Bioscience
N2  - Background
Despite advances in treatment of patients with non-small cell lung cancer, carriers of certain genetic alterations are prone to failure. One such factor frequently mutated, is the tumor suppressor PTEN. These tumors are supposed to be more resistant to radiation, chemo- and immunotherapy.

Results
We demonstrate that loss of PTEN led to altered expression of transcriptional programs which directly regulate therapy resistance, resulting in establishment of radiation resistance. While PTEN-deficient tumor cells were not dependent on DNA-PK for IR resistance nor activated ATR during IR, they showed a significant dependence for the DNA damage kinase ATM. Pharmacologic inhibition of ATM, via KU-60019 and AZD1390 at non-toxic doses, restored and even synergized with IR in PTEN-deficient human and murine NSCLC cells as well in a multicellular organotypic ex vivo tumor model.

Conclusion
PTEN tumors are addicted to ATM to detect and repair radiation induced DNA damage. This creates an exploitable bottleneck. At least in cellulo and ex vivo we show that low concentration of ATM inhibitor is able to synergise with IR to treat PTEN-deficient tumors in genetically well-defined IR resistant lung cancer models.
KW  - PTEN
KW  - ATM
KW  - IR
KW  - NSCLC
KW  - radiotherapy
KW  - cancer
KW  - DNA-PK
KW  - PI3K
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-299865
SN  - 2045-3701
VL  - 12
ER  -