Targeting the survival kinase DYRK1B: A novel approach to overcome radiotherapy-related treatment resistance

BACKGROUND Cancer cell survival under stress conditions is a prerequisite for the development of treatment resistance. The survival kinase DYRK1B is a key regulator of stress survival pathways and might thereby also contribute to radiation resistance. Here we investigate the strategy of targeting DYRK1B in combination with ionizing radiation (IR) to enhance tumor cell killing under stress conditions. METHODS DYRK1B expression, ROS formation and DNA damage were investigated under serum-starvation (0.1% FBS), hypoxia (0.2%, 1% O$_{2}$) and IR. The combined treatment modality of IR and DYRK1B inhibition was investigated in 2D and in spheroids derived from the colorectal cancer cell line SW620, and in primary patient-derived colorectal carcinoma (CRC) organoids. RESULTS Expression of DYRK1B was upregulated under starvation and hypoxia, but not in response to IR. The small molecule DYRK1B inhibitor AZ191 and shRNA-mediated DYRK1B knockdown significantly reduced proliferative activity and clonogenicity of SW620 tumor cells alone and in combination with IR under serum-starved conditions, which correlated with increased ROS levels and DNA damage. Furthermore, AZ191 successfully targeted the hypoxic core of tumor spheroids while IR preferentially targeted normoxic cells in the rim of the spheroids. A combined treatment effect was also observed in CRC-organoids but not in healthy tissue-derived organoids. CONCLUSION Combined treatment with the DYRK1B inhibitor AZ191 and IR resulted in (supra-) additive tumor cell killing in colorectal tumor cell systems and in primary CRC organoids. Mechanistic investigations support the rational to target the stress-enhanced survival kinase DYRK1B in combination with irradiation to overcome hypoxia- and starvation-induced treatment resistances

MPI tracer interactions and their effect on signal stability

Nanoparticles tend to agglomerate following their in vivo or in vitro application. This leads to particle interaction and, for magnetic particle imaging (MPI) tracers, to magnetic coupling phenomena. Here, we investigate these effects and their influence on magnetic particle spectroscopy (MPS) and MPI signal stability. Highly magnetic flame-made Zn-ferrites with controlled interparticle distance are suggested as a stable MPI tracer system. Due to their pre-aggregated morphology, additional agglomeration does not substantially alter their magnetic response. This is in strong contrast to frequently investigated polymer-coated iron oxide nanoparticles, which show a massive MPS signal loss in a biologically relevant dispersion medium compared to water. This effect is also shown during MPI and renders these tracers inapplicable to further applications. Our flame-made Zn-ferrites, on the other hand, show sufficient signal stability, which allows their detailed quantification via MPI

Particle interactions and their effect on magnetic particle spectroscopy and imaging

Signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions altering the signal. Here, we investigate the influence of such magnetic coupling phenomena on the MPI signal. We prepared Zn0.4Fe2.6O4 nanoparticles by flame spray synthesis and controlled their inter-particle distance by varying SiO2 coating thickness. The silica shell affected the magnetic properties indicating stronger particle interactions for a smaller inter-particle distance. The SiO2-coated Zn0.4Fe2.6O4 outperformed the bare sample in magnetic particle spectroscopy (MPS) in terms of signal/noise, however, the shell thickness itself only weakly influenced the MPS signal. To investigate the importance of magnetic coupling effects in more detail, we benchmarked the MPS signal of the bare and SiO2-coated Zn-ferrites against commercially available PVP-coated Fe3O4 nanoparticles in water and PBS. PBS is known to destabilize nanoparticle colloids mimicking in vivo-like agglomeration. The bare and coated Zn-ferrites showed excellent signal stability, despite their agglomeration in PBS. We attribute this to their process-intrinsic aggregated morphology formed during their flame-synthesis, which generates an MPS signal only little affected by PBS. On the other hand, the MPS signal of commercial PVP-coated Fe3O4 strongly decreased in PBS compared to water, indicating strongly changed particle interactions. The relevance of this effect was further investigated in a human cell model. For PVP-coated Fe3O4, we detected a strong discrepancy between the particle concentration obtained from the MPS signal and the actual concentration determined via ICP-MS. The same trend was observed during their MPI analysis; while SiO2-coated Zn-ferrites could be precisely located in water and PBS, PVP-coated Fe3O4 could not be detected in PBS at all. This drastically limits the sensitivity and also general applicability of these commercial tracers for MPI and illustrates the advantages of our flame-made Zn-ferrites concerning signal stability and ultimately diagnostic accuracy.ISSN:2040-3364ISSN:2040-337

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation