Stochastic Predictions of Cell Kill During Stereotactic Ablative Radiation Therapy: Do Hypoxia and Reoxygenation Really Matter?

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.

In silico modeling of cellular probabilistic nanoparticle radiosensitization in head and neck cancers

Background: The use of gold nanoparticles (AuNPs) as radiosensitizers may offer a new approach in the treatment of head and neck cancers; minimizing treatment-associated toxicities and improving patient outcomes. AuNPs promote localized dose deposition; permitting improved local control and/or dose reduction. Aim: This work aimed to address the theoretical optimization of radiation doses, fractionation and nanoparticle injection schedules to maximize therapeutic benefits. Materials & methods: Probabilistic nanoparticle sensitization factors were incorporated into the individual cell-based HYP-RT computer model of tumor growth and radiotherapy. Results: Total dose outcomes across all radiation therapy treatment regimens were found to be significantly reduced with the presence of AuNPs, with bi-weekly injections showing the most decrease. Conclusion: Outcomes suggest the need for regular AuNP administration to permit effective radiosensitization.

Stochastic multicellular modeling of x-ray irradiation, DNA damage induction, DNA free-end misrejoining and cell death

The repair or misrepair of DNA double-strand breaks (DSBs) largely determines whether a cell will survive radiation insult or die. A new computational model of multicellular, track structure-based and pO₂-dependent radiation-induced cell death was developed and used to investigate the contribution to cell killing by the mechanism of DNA free-end misrejoining for low-LET radiation. A simulated tumor of 1224 squamous cells was irradiated with 6 MV x-rays using the Monte Carlo toolkit Geant4 with low-energy Geant4-DNA physics and chemistry modules up to a uniform dose of 1 Gy. DNA damage including DSBs were simulated from ionizations, excitations and hydroxyl radical interactions along track segments through cell nuclei, with a higher cellular pO₂ enhancing the conversion of DNA radicals to strand breaks. DNA free-ends produced by complex DSBs (cDSBs) were able to misrejoin and produce exchange-type chromosome aberrations, some of which were asymmetric and lethal. A sensitivity analysis was performed and conditions of full oxia and anoxia were simulated. The linear component of cell killing from misrejoining was consistently small compared to values in the literature for the linear component of cell killing for head and neck squamous cell carcinoma (HNSCC). This indicated that misrejoinings involving DSBs from the same x-ray (including all associated secondary electrons) were rare and that other mechanisms (e.g. unrejoined ends) may be important. Ignoring the contribution by the indirect effect toward DNA damage caused the DSB yield to drop to a third of its original value and the cDSB yield to drop to a tenth of its original value. Track structure-based cell killing was simulated in all 135306 viable cells of a 1 mm³ hypoxic HNSCC tumor for a uniform dose of 1 Gy.

Approaches to combat hypoxia in cancer therapy and the potential for in silico models in their evaluation

AIM

The negative impact of tumour hypoxia on cancer treatment outcome has been long-known, yet there has been little success combating it. This paper investigates the potential role of in silico modelling to help test emerging hypoxia-targeting treatments in cancer therapy.

METHODS

A Medline search was undertaken on the current landscape of in silico models that simulate cancer therapy and evaluate their ability to test hypoxia-targeting treatments. Techniques and treatments to combat tumour hypoxia and their current challenges are also presented.

RESULTS

Hypoxia-targeting treatments include tumour reoxygenation, hypoxic cell radiosensitization with nitroimidazoles, hypoxia-activated prodrugs and molecular targeting. Their main challenges are toxicity and not achieving adequate delivery to hypoxic regions of the tumour. There is promising research toward combining two or more of these techniques. Different types of in silico therapy models have been developed ranging from temporal to spatial and from stochastic to deterministic models. Numerous models have compared the effectiveness of different radiotherapy fractionation schedules for controlling hypoxic tumours. Similarly, models could help identify and optimize new treatments for overcoming hypoxia that utilize novel hypoxia-targeting technology.

CONCLUSION

Current therapy models should attempt to incorporate more sophisticated modelling of tumour angiogenesis/vasculature and vessel perfusion in order to become more useful for testing hypoxia-targeting treatments, which typically rely upon the tumour vasculature for delivery of additional oxygen, (pro)drugs and nanoparticles.