IntroductionHyperthermia (HT) induces various cellular biological processes, such as repair impairment and direct HT cell killing. In this context, in-silico biophysical models that translate deviations in the treatment conditions into clinical outcome variations may be used to study the extent of such processes and their influence on combined hyperthermia plus radiotherapy (HT + RT) treatments under varying conditions.MethodsAn extended linear-quadratic model calibrated for SiHa and HeLa cell lines (cervical cancer) was used to theoretically study the impact of varying HT treatment conditions on radiosensitization and direct HT cell killing effect. Simulated patients were generated to compute the Tumor Control Probability (TCP) under different HT conditions (number of HT sessions, temperature and time interval), which were randomly selected within margins based on reported patient data.ResultsUnder the studied conditions, model-based simulations suggested a treatment improvement with a total CEM43 thermal dose of approximately 10 min. Additionally, for a given thermal dose, TCP increased with the number of HT sessions. Furthermore, in the simulations, we showed that the TCP dependence on the temperature/time interval is more correlated with the mean value than with the minimum/maximum value and that comparing the treatment outcome with the mean temperature can be an excellent strategy for studying the time interval effect.ConclusionThe use of thermoradiobiological models allows us to theoretically study the impact of varying thermal conditions on HT + RT treatment outcomes. This approach can be used to optimize HT treatments, design clinical trials, and interpret patient data.

Introduction Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics. Methods After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators’ efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data. Results SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair. Conclusions Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico . Keywords repair kinetics , dose-rate , radiobiological models

Introduction Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics. Methods After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators’ efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data. Results SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair. Conclusions Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico.

Hyperthermia (HT) is an accepted treatment for recurrent breast cancer which locally heats the tumor to 39–44 °C, and it is a very potent sensitizer for radiotherapy (RT) and chemotherapy. However, currently little is known about how HT with a distinct temperature, and particularly, how the sequence of HT and RT changes the immune phenotype of breast cancer cells. Therefore, human MDA-MB-231 and MCF-7 breast cancer cells were treated with HT of different temperatures (39, 41 and 44 °C), alone and in combination with RT (2 × 5 Gy) in different sequences, with either RT or HT first, followed by the other. Tumor cell death forms and the expression of immune checkpoint molecules (ICMs) were analyzed by multicolor flow cytometry. Human monocyte-derived dendritic cells (moDCs) were differentiated and co-cultured with the treated cancer cells. In both cell lines, RT was the main stressor for cell death induction, with apoptosis being the prominent cell death form in MCF-7 cells and both apoptosis and necrosis in MDA-MB-231 cells. Here, the sequence of the combined treatments, either RT or HT, did not have a significant impact on the final outcome. The expression of all of the three examined immune suppressive ICMs, namely PD-L1, PD-L2 and HVEM, was significantly increased on MCF-7 cells 120 h after the treatment of RT with HT of any temperature. Of special interest for MDA-MB-231 cells is that only combinations of RT with HT of both 41 and 44 °C induced a significantly increased expression of PD-L2 at all examined time points (24, 48, 72, and 120 h). Generally, high dynamics of ICM expression can be observed after combined RT and HT treatments. There was no significant difference between the different sequences of treatments (either HT + RT or RT + HT) in case of the upregulation of ICMs. Furthermore, the co-culture of moDCs with tumor cells of any treatment had no impact on the expression of activation markers. We conclude that the sequence of HT and RT does not strongly affect the immune phenotype of breast cancer cells. However, when HT is combined with RT, it results in an increased expression of distinct immune suppressive ICMs that should be considered by including immune checkpoint inhibitors in multimodal tumor treatments with RT and HT. Further, combined RT and HT affects the immune system in the effector phase rather than in the priming phase.

Artificial immune-tumor ecosystems can serve as models to explore the complex tumor-host-immune – interactions in silico. This may contribute to a better understanding of the conditions leading to anti-cancer immune response in patients during anti-cancer therapy. For model development, it is important to identify an appropriate model structure which is suitable to mimic the behavior of real biological systems. In this study, the influence of the number of antigens in an artificial adaptive immune system onto an immune-tumor ecosystem during and after radiation therapy (RT) is investigated. For antigen pattern recognition, a perceptron is used. The simulated scenarios with 4, 9 and 12 antigens exhibit differences in the immune response, but in all cases, perceptron weights for host tissue evolve after RT into negative values, leading to an immune-suppressive effect. This effect results from the evolution of the populations in the ecosystem and the training of the perceptron. In conclusion, the response of the proposed artificial immune system is strongly dependent on the ecosystem dynamics, which seems to be the case for the real biological systems as well.

Hyperthermia is clinically applied cancer treatment in conjunction with radio- and/or chemotherapy, in which the tumor volume is exposed to supraphysiological temperatures. Since cells can effectively counteract the effects of hyperthermia by protective measures that are commonly known as the heat stress response, the identification of cellular processes that are essential for surviving hyperthermia could lead to novel treatment strategies that improve its therapeutic effects. Here, we apply a meta-analytic approach to 18 datasets that capture hyperthermia-induced transcriptome alterations in nine different human cancer cell lines. We find, in line with previous reports, that hyperthermia affects multiple processes, including protein folding, cell cycle, mitosis, and cell death, and additionally uncover expression changes of genes involved in KRAS signaling, inflammatory responses, TNF-a signaling and epithelial-to-mesenchymal transition (EMT). Interestingly, however, we also find a considerable inter-study variability, and an apparent absence of a ‘universal’ heat stress response signature, which is likely caused by the differences in experimental conditions. Our results suggest that gene expression alterations after heat stress are driven, to a large extent, by the experimental context, and call for a more extensive, controlled study that examines the effects of key experimental parameters on global gene expression patterns.

There is some evidence that radiotherapy (RT) can trigger anti-tumor immune responses. In addition, hyperthermia (HT) is known to be a tumor cell radio-sensitizer. How HT could enhance the anti-tumor immune response produced by RT is still an open question. The aim of this study is the evaluation of potential dynamic effects regarding the adaptive immune response induced by different combinations of RT fractions with HT. The adaptive immune system is considered as a trainable unit (perceptron) which compares danger signals released by necrotic or apoptotic cell death with the presence of tumor- and host tissue cell population-specific molecular patterns (antigens). To mimic the changes produced by HT such as cell radio-sensitization or increase of the blood perfusion after hyperthermia, simplistic biophysical models were included. To study the effectiveness of the different RT+HT treatments, the Tumor Control Probability (TCP) was calculated. In the considered scenarios, the major effect of HT is related to the enhancement of the cell radio-sensitivity while perfusion or heat-based effects on the immune system seem to contribute less. Moreover, no tumor vaccination effect has been observed. In the presented scenarios, HT boosts the RT cell killing but it does not fundamentally change the anti-tumor immune response.

ELIMED has been developed and installed at ELI beamlines as a part of the ELIMAIA beamline to transport, monitor, and use laser-driven ion beams suitable for multidisciplinary applications, including biomedical ones. This paper aims to investigate the feasibility to perform radiobiological experiments using laser-accelerated proton beams with intermediate energies (up to 30 MeV). To reach this goal, we simulate a proton source based on experimental data like the ones expected to be available in the first phase of ELIMED commissioning by using the G4-ELIMED application (an application based on the Geant4 toolkit that simulates the full ELIMED beamline). This allows the study of transmission efficiency and the final characteristics of the proton beam at the sample irradiation point. The Energy Selector System is used as an active energy modulator to obtain the desired beam features in a relatively short irradiation time (around 6 min). Furthermore, we demonstrate the capability of the beamline to filter out other ion contaminants, typically co-accelerated in a laser-plasma environment. These results can be considered as a detailed feasibility study for the use of ELIMED for various user applications such as radiobiological experiments with ultrahigh dose rate proton beams.