The HYP-RT hypoxic tumour radiotherapy algorithm and accelerated repopulation dose per fraction study

Assessing the therapeutic response of tumors to hypoxia-targeted prodrugs with an in silico approach

Tumor hypoxia is commonly recognized as a condition stimulating the progress of the aggressive phenotype of tumor cells. Hypoxic tumor cells inhibit the delivery of cytotoxic drugs, causing hypoxic areas to receive insufficient amounts of anticancer agents, which results in adverse treatment responses. Being such an obstruction to conventional therapies for cancer, hypoxia might be considered a target to facilitate the efficacy of treatments in the resistive environment of tumor sites. In this regard, benefiting from prodrugs that selectively target hypoxic regions remains an effective approach. Additionally, combining hypoxia-activated prodrugs (HAPs) with conventional chemotherapeutic drugs has been used as a promising strategy to eradicate hypoxic cells. However, determining the appropriate sequencing and scheduling of the combination therapy is also of great importance in obtaining favorable results in anticancer therapy. Here, benefiting from a modeling approach, we study the efficacy of HAPs in combination with chemotherapeutic drugs on tumor growth and the treatment response. Different treatment schedules have been investigated to see the importance of determining the optimal schedule in combination therapy. The effectiveness of HAPs in varying hypoxic conditions has also been explored in the study. The model provides qualitative conclusions about the treatment response, as the maximal benefit is obtained from combination therapy with greater cell death for highly hypoxic tumors. It has also been observed that the antitumor effects of HAPs show a hypoxia-dependent profile.

Predictive modeling of hypoxic head and neck cancers during fractionated radiotherapy with gold nanoparticle radiosensitization

PURPOSE

Intrinsic radioresistance and increased proliferation rates in head and neck cancers (HNCs) are associated with negative radiotherapy (RT) treatment responses. The use of gold nanoparticles (AuNPs) as radiosensitizers could enable total radiation dose reduction and lowered radiation toxicity. AuNP radiosensitization may overcome hypoxia-induced radioresistance and treatment-induced accelerated repopulation of cancer cells in HNCs, improving radiotherapy outcomes.

METHODS

Tumor control was determined by considering individual cancer cell responses in probabilistic computational simulations using HYP-RT software for clinical radiotherapy doses and fractionation schedules along with three different nanoparticle administration schedules. Antagonistic tumor hypoxia and rapid tumor regrowth due to accelerated repopulation of cancers cells were taken into consideration.

RESULTS

Simulations indicate that tumors that are conventionally uncontrollable can be controlled with AuNP radiosensitization. In simulations where the absence of AuNPs required radiotherapy doses above standard clinical prescriptions, reoccurring AuNP administration allowed for radiation dose reductions below standard clinical dose prescriptions. For example, considering a 2 Gy per fraction radiotherapy schedule, tumor control was achieved with 57.2 ± 5.1 Gy (P = <0.0001) for weekly AuNP administration and 53.0 ± 4.0 Gy (P = <0.0001) for biweekly AuNP administration compared to 69.9 ± 5.8 Gy with no radiosensitization.

CONCLUSIONS

AuNPs decreased the predicted RT total doses required to achieve tumor control via total stem cell elimination, offering an optimistic prediction and method for which hypoxia-induced and rapidly growing radioresistant tumors are treated more effectively. Outcomes are also shown to be sensitive to the RT schedule with data for hyperfractionated RT indicating the greatest benefits from radiosensitization.

Combined radiation strategies for novel and enhanced cancer treatment

Numerous studies focus on cancer therapy worldwide, and although many advances have been recorded, the complexity of the disease dictates thinking out of the box to confront it. This study reviews some of the currently available ionizing (IR) and non-ionizing radiation (NIR)-based treatment methods and explores their possible combinations that lead to synergistic, multimodal approaches with promising therapeutic outcomes. Traditional techniques, like radiotherapy (RT) show decent results, although they cannot spare 100% the healthy tissues neighboring with the cancer ones. Targeted therapies, such as proton and photodynamic therapy (PT and PDT, respectively) present adequate outcomes, even though each one has its own drawbacks. To overcome these limitations, the combination of therapeutic modalities has been proposed and has already been showing promising results. At the same time, the recent advances in nanotechnology in the form of nanoparticles enhance cancer therapy, making multimodal treatments worthy of exploring and studying. The combination of RT and PDT has reached the level of clinical trials and is showing promising results. Moreover, in vitro and in vivo studies of nanoparticles with PDT have also provided beneficial results concerning enhanced radiation treatments. In any case, novel and multimodal approaches have to be adopted to achieve personalized, enhanced and effective cancer treatment.

Simulation of hypoxia PET-tracer uptake in tumours: Dependence of clinical uptake-values on transport parameters and arterial input function

Poor radiotherapy outcome is in many cases related to hypoxia, due to the increased radioresistance of hypoxic tumour cells. Positron emission tomography may be used to non-invasively assess the oxygenation status of the tumour using hypoxia-specific radiotracers. Quantification and interpretation of these images remains challenging, since radiotracer binding and oxygen tension are not uniquely related. Computer simulation is a useful tool to improve the understanding of tracer dynamics and its relation to clinical uptake parameters currently used to quantify hypoxia. In this study, a model for simulating oxygen and radiotracer distribution in tumours was implemented to analyse the impact of physiological transport parameters and of the arterial input function (AIF) on: oxygenation histograms, time-activity curves, tracer binding and clinical uptake-values (tissue-to-blood ratio, TBR, and a composed hypoxia-perfusion metric, FHP). Results were obtained for parallel and orthogonal vessel architectures and for vascular fractions (VFs) of 1% and 3%. The most sensitive parameters were the AIF and the maximum binding rate (K_max). TBR allowed discriminating VF for different AIF, and FHP for different K_max, but neither TBR nor FHP were unbiased in all cases. Biases may especially occur in the comparison of TBR- or FHP-values between different tumours, where the relation between measured and actual AIF may vary. Thus, these parameters represent only surrogates rather than absolute measurements of hypoxia in tumours.

A Model of Indirect Cell Death Caused by Tumor Vascular Damage after High-Dose Radiotherapy

There is increasing evidence that high doses of radiotherapy, like those delivered in stereotactic body radiotherapy (SBRT), trigger indirect mechanisms of cell death. Such effect seems to be two-fold. High doses may trigger an immune response and may cause vascular damage, leading to cell starvation and death. Development of mathematical response models, including indirect death, may help clinicians to design SBRT optimal schedules. Despite increasing experimental literature on indirect tumor cell death caused by vascular damage, efforts on modeling this effect have been limited. In this work, we present a biomathematical model of this effect. In our model, tumor oxygenation is obtained by solving the reaction-diffusion equation; radiotherapy kills tumor cells according to the linear-quadratic model, and also endothelial cells (EC), which can trigger loss of functionality of capillaries. Capillary death will affect tumor oxygenation, driving nearby tumor cells into severe hypoxia. Capillaries can recover functionality due to EC proliferation. Tumor cells entering a predetermined severe hypoxia status die according to a hypoxia-death model. This model fits recently published experimental data showing the effect of vascular damage on surviving fractions. It fits surviving fraction curves and qualitatively reproduces experimental values of percentages of functional capillaries 48 hours postirradiation, and hypoxic cells pre- and 48 hours postirradiation. This model is useful for exploring aspects of tumor and EC response to radiotherapy and constitutes a stepping stone toward modeling indirect tumor cell death caused by vascular damage and accounting for this effect during SBRT planning. SIGNIFICANCE: A novel biomathematical model of indirect tumor cell death caused by vascular radiation damage could potentially help clinicians interpret experimental data and design better radiotherapy schedules.

Impact of different biologically-adapted radiotherapy strategies on tumor control evaluated with a tumor response model

Motivated by the capabilities of modern radiotherapy techniques and by the recent developments of functional imaging techniques, dose painting by numbers (DPBN) was proposed to treat tumors with heterogeneous biological characteristics. This work studies different DPBN optimization techniques for virtual head and neck tumors assessing tumor response in terms of cell survival and tumor control probability with a previously published tumor response model (TRM). Uniform doses of 2 Gy are redistributed according to the microscopic oxygen distribution and the density distribution of tumor cells in four virtual tumors with different biological characteristics. In addition, two different optimization objective functions are investigated, which: i) minimize tumor cell survival (OF_surv) or; ii) maximize the homogeneity of the density of surviving tumor cells (OF_std). Several adaptive schemes, ranging from single to daily dose optimization, are studied and the treatment response is compared to that of the uniform dose. The results show that the benefit of DPBN treatments depends on the tumor reoxygenation capability, which strongly differed among the set of virtual tumors investigated. The difference between daily (fraction by fraction) and three weekly optimizations (at the beginning of weeks 1, 3 and 4) was found to be small, and higher benefit was observed for the treatments optimized using OF_surv. This in silico study corroborates the hypothesis that DPBN may be beneficial for treatments of tumors which show reoxygenation during treatment, and that a few optimizations may be sufficient to achieve this therapeutic benefit.

Simulation of head and neck cancer oxygenation and doubling time in a 4D cellular model with angiogenesis

Tumor oxygenation has been correlated with treatment outcome for radiotherapy. In this work, the dependence of tumor oxygenation on tumor vascularity and blood oxygenation was determined quantitatively in a 4D stochastic computational model of head and neck squamous cell carcinoma (HNSCC) tumor growth and angiogenesis. Additionally, the impacts of the tumor oxygenation and the cancer stem cell (CSC) symmetric division probability on the tumor volume doubling time and the proportion of CSCs in the tumor were also quantified. Clinically relevant vascularities and blood oxygenations for HNSCC yielded tumor oxygenations in agreement with clinical data for HNSCC. The doubling time varied by a factor of 3 from well oxygenated tumors to the most severely hypoxic tumors of HNSCC. To obtain the doubling times and CSC proportions clinically observed in HNSCC, the model predicts a CSC symmetric division probability of approximately 2% before treatment. To obtain the doubling times clinically observed during treatment when accelerated repopulation is occurring, the model predicts a CSC symmetric division probability of approximately 50%, which also results in CSC proportions of 30-35% during this time.

Development of an in silico stochastic 4D model of tumor growth with angiogenesis

PURPOSE

A stochastic computer model of tumour growth with spatial and temporal components that includes tumour angiogenesis was developed. In the current work it was used to simulate head and neck tumour growth. The model also provides the foundation for a 4D cellular radiotherapy simulation tool.

METHODS

The model, developed in Matlab, contains cell positions randomised in 3D space without overlap. Blood vessels are represented by strings of blood vessel units which branch outwards to achieve the desired tumour relative vascular volume. Hypoxic cells have an increased cell cycle time and become quiescent at oxygen tensions less than 1 mmHg. Necrotic cells are resorbed. A hierarchy of stem cells, transit cells and differentiated cells is considered along with differentiated cell loss. Model parameters include the relative vascular volume (2-10%), blood oxygenation (20-100 mmHg), distance from vessels to the onset of necrosis (80-300 μm) and probability for stem cells to undergo symmetric division (2%). Simulations were performed to observe the effects of hypoxia on tumour growth rate for head and neck cancers. Simulations were run on a supercomputer with eligible parts running in parallel on 12 cores.

RESULTS

Using biologically plausible model parameters for head and neck cancers, the tumour volume doubling time varied from 45 ± 5 days (n = 3) for well oxygenated tumours to 87 ± 5 days (n = 3) for severely hypoxic tumours.

CONCLUSIONS

The main achievements of the current model were randomised cell positions and the connected vasculature structure between the cells. These developments will also be beneficial when irradiating the simulated tumours using Monte Carlo track structure methods.

Tumour repopulation and the role of abortive division in squamous cell carcinomas during chemotherapy

OBJECTIVES

In head and neck cancers, tumour cell repopulation during chemotherapy is one reason for treatment failure. Some of the mechanisms responsible for this repopulation are cell recruitment and abortive division. Due to lack of quantitative data in the literature regarding these mechanisms, the aim of this study was to investigate the interplay between recruitment and abortive division during cisplatin chemotherapy and to quantify the impact of these mechanisms on tumour control.

MATERIALS AND METHODS

An in silico Monte Carlo tumour model was developed to simulate tumour behaviour during chemotherapy. The virtual tumour had the composition and kinetic properties of a biological tumour. Effect of cisplatin on cell cycle and repopulation mechanisms were simulated and interpreted.

RESULTS

Abortive division contributed to cell production within the tumour during chemotherapy. There was a strong relationship between recruitment and tumour growth due to abortive division. This observation was supported by the value of proliferative/stem ratio, which increased from 1.3 to 36, even when using small recruitment parameters.

CONCLUSIONS

While abortive division contributed towards tumour repopulation during chemotherapy, this mechanism could be controlled by daily doses of cisplatin. On the other hand, stem cells require an additional cytotoxic agent to overcome repopulation due to cell recruitment. Consequently, repopulation via abortive division during chemotherapy did not entail alterations in treatment schedule, nor dose escalation, to control the tumour.

Altered fractionation outcomes for hypoxic head and neck cancer using the HYP-RT Monte Carlo model

OBJECTIVE

Altered fractionation radiotherapy is simulated on a set of virtual tumours to assess the total doses required for tumour control compared with clinical head and neck data and the doses required to control hypoxic vs well-oxygenated tumours with different radiobiological properties.

METHODS

The HYP-RT model is utilised to explore the impact of tumour oxygenation and the onset times of accelerated repopulation (AR) and reoxygenation (ROx) during radiotherapy. A biological effective dose analysis is used to rank the schedules based on their relative normal tissue toxicities.

RESULTS

Altering the onset times of AR and ROx has a large impact on the doses required to achieve tumour control. Immediate onset of ROx and 2-week onset time of AR produce results closely predicting average human outcomes in terms of the total prescription doses in clinical trials. Modifying oxygen enhancement ratio curves based on dose/fraction significantly reduces the dose (5-10 Gy) required for tumour control for hyperfractionated schedules. HYP-RT predicts 10×1.1 Gy per week to be most beneficial, whereas the conventional schedule is predicted as beneficial for early toxicity but has average-poor late toxicity.

CONCLUSION

HYP-RT predicts that altered radiotherapy schedules increase the therapeutic ratio and may be used to make predictions about the prescription doses required to achieve tumour control for tumours with different oxygenation levels and treatment responses.

ADVANCES IN KNOWLEDGE

Oxic and hypoxic tumours have large differences in total radiation dose requirements, affected by AR and ROx onset times by up to 15-25 Gy for the same fractionation schedule.