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Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment.
Tumour cells show a varying susceptibility to radiation damage as a function of the current cell cycle phase. While this sensitivity is averaged out in an unperturbed tumour due to unsynchronised cell cycle progression, external stimuli such as radiation or drug doses can induce a resynchronisation of the cell cycle and consequently induce a collective development of radiosensitivity in tumours. Although this effect has been regularly described in experiments it is currently not exploited in clinical practice and thus a large potential for optimisation is missed. We present an agent-based model for three-dimensional tumour spheroid growth which has been combined with an irradiation damage and kinetics model. We predict the dynamic response of the overall tumour radiosensitivity to delivered radiation doses and describe corresponding time windows of increased or decreased radiation sensitivity. The degree of cell cycle resynchronisation in response to radiation delivery was identified as a main determinant of the transient periods of low and high radiosensitivity enhancement. A range of selected clinical fractionation schemes is examined and new triggered schedules are tested which aim to maximise the effect of the radiation-induced sensitivity enhancement. We find that the cell cycle resynchronisation can yield a strong increase in therapy effectiveness, if employed correctly. While the individual timing of sensitive periods will depend on the exact cell and radiation types, enhancement is a universal effect which is present in every tumour and accordingly should be the target of experimental investigation. Experimental observables which can be assessed non-invasively and with high spatio-temporal resolution have to be connected to the radiosensitivity enhancement in order to allow for a possible tumour-specific design of highly efficient treatment schedules based on induced cell cycle synchronisation.
Author Summary: The sensitivity of a cell to a dose of radiation is largely affected by its current position within the cell cycle. While under normal circumstances progression through the cell cycle will be asynchronous in a tumour mass, external influences such as chemo- or radiotherapy can induce a synchronisation. Such a common progression of the inner clock of the cancer cells results in the critical dependence on the effectiveness of any drug or radiation dose on a suitable timing for its administration. We analyse the exact evolution of the radiosensitivity of a sample tumour spheroid in a computer model, which enables us to predict time windows of decreased or increased radiosensitivity. Fractionated radiotherapy schedules can be tailored in order to avoid periods of high resistance and exploit the induced radiosensitivity for an increase in therapy efficiency. We show that the cell cycle effects can drastically alter the outcome of fractionated irradiation schedules in a spheroid cell system. By using the correct observables and continuous monitoring, the cell cycle sensitivity effects have the potential to be integrated into treatment planing of the future and thus to be employed for a better outcome in clinical cancer therapies.
The central goal of this investigation is to describe the dynamic reaction of a multicellular tumour spheroid to treatment with radiotherapy. A focus will be on the triggered dynamic cell cycle reaction in the spheroid and how it can be employed within fractionated radiation schedules.
An agent-based model for cancer cells is employed which features inherent cell cycle progression and reactions to environmental conditions. Cells are represented spatially by a weighted, dynamic and kinetic Voronoi/Delaunay model which also provides for the identification of cells in contact within the multicellular aggregate. Force-based interaction between cells will lead to rearrangement in response to proliferation and can induce cell quiescence via a mechanism of pressure-induced contact inhibition. The evolution of glucose and oxygen concentration inside the tumour spheroid is tracked in a diffusion solver in correspondence to in vitro or in vivo boundary conditions and a corresponding local nutrient uptake by single cells.
Radiation effects are implemented based on the measured single cell survival in the linear-quadratic model. The survival probability will be affected by the radiosensitivity of the current cycle phase and the local oxygen concentration. Quiescent cells will reduce the effective dose they receive as a consequence of their increased radioresistance. The radiation model includes a fast response to fatal DNA damage through cell apoptosis and a slow response via cell loss due to misrepair during the radiation-induced G2-block.
A simplified model for drug delivery in chemotherapy is implemented.
The model can describe the growth dynamics of spheroids in accordance to experimental data, including total number of cells, histological structure and cell cycle distribution. Investigations of possible mechanisms for growth saturation reveal a critical dependence of tumour growth on the shedding rate of cells from the surface.
In response to a dose of irradiation, a synchronisation of the cell cycle progression within the tumour is observed. This will lead to cyclic changes in the overall radiation sensitivity of the tumour which are quantified using an enhancement measure in comparison to the expected radiosensitivity of he tumour. A transient strong peak in radiosensitivity enhancement is observed after administration of irradiation. Mechanisms which influence the peak timing and development are systematically investigated, revealing quiescence and reactivation of cells to be a central mechanism for the enhancement.
Direct redistribution of cells due to different survival in cell cycle phases, re-activation of quiescent cells in response to radiation-induced cell death and blocking of DNA damaged cells at the G2/M checkpoint are identified as the main mechanisms which contribute to a synchronisation and determine the radiosensitivity increase. A typical time scale for the development of radiosensitivity and the relaxation of tumours to a steady-state after irradiation is identified, which is related to the typical total cell cycle time.
A range of clinical radiotherapy schedules is tested for their performance within the simulation and a systematic comparison with alternative delivery schedules is performed, in order to identify schedules which can most effectively employ the described transient enhancement effects. In response to high-dose schedules, a dissolution of the tumour spheroid into smaller aggregates can be observed which is a result of the loss of integrity in the spheroid that is associated with high cell death via apoptosis. Fractionated irradiation of spheroids with constant dose per time unit but different inter-fraction times clearly reveals optimal time-intervals for radiation, which are directly related to the enhancement response of the tumour.
In order to test the use of triggered enhancement effects in tumours, combinations of trigger- and effector doses are examined for their performance in specific treatment regimens. Furthermore, the automatic identification and triggering in response to high enhancement periods in the tumour is analysed.
While triggered schedules and automatic schedules both yield a higher treatment efficiency in comparison to conventional schedules, treatment optimisation is a revealed to be a global problem, which cannot be sufficiently solved using local optimisation only.
The spatio-temporal dynamics of hypoxia in the tumour are studied in response to irradiation. Microscopic, diffusion-induced reoxygenation dynamics are demonstrated to be on a typical time-scale which is in the order of fractionation intervals. Neoadjuvant chemotherapy with hydroxyurea can yield a drastic improvement of radiosensitivity via cell cycle synchronisation and specific toxicity against radioresistant S-phase cells.
The model makes clear predictions of radiation schedules which are especially effective as a result of triggered cell cycle-based radiosensitivity enhancement. Division of radiation into trigger and effector doses is highly effective and especially suited to be combined with adjuvant chemotherapy in order to limit regrowth of cells.
Malignant neoplasms are one of the top causes of death in all developed countries around the world and account for almost one quarter of all deaths. An individual cell based computational model with strong connections to the experimental data through lattice free, newtonian interaction could be used to validate experimental results and eventually make predictions guiding further experiments. This model was build as a part of the thesis and shall be extended to the modelling of the effects of ionic radition on the vascularised tumour as a possible treatment for inoperable tumours.