Tumour control in ion beam radiotherapy with different ions in the presence of hypoxia: an oxygen enhancement ratio model based on the microdosimetric kinetic model

A perspective on tumor radiation resistance following high-LET radiation treatment

High-linear energy transfer (LET) radiation is a promising alternative to conventional low-LET radiation for therapeutic gain against cancer owing to its ability to induce complex and clustered DNA lesions. However, the development of radiation resistance poses a significant barrier. The potential molecular mechanisms that could confer resistance development are translesion synthesis (TLS), replication gap suppression (RGS) mechanisms, autophagy, epithelial-mesenchymal transition (EMT) activation, release of exosomes, and epigenetic changes. This article will discuss various types of complex clustered DNA damage, their repair mechanisms, mutagenic potential, and the development of radiation resistance strategies. Furthermore, it highlights the importance of careful consideration and patient selection when employing high-LET radiotherapy in clinical settings.

Modeling hypoxia-induced radiation resistance and the impact of radiation sources

Hypoxia contributes significantly to resistance in radiotherapy. Our research rigorously examines the influence of microvascular morphology on radiotherapy outcome, specifically focusing on how microvasculature shapes hypoxia within the microenvironment and affects resistance to a standard treatment regimen (30×2GyRBE). Our computational modeling extends to the effects of different radiation sources. For photons and protons, our analysis establishes a clear correlation between hypoxic volume distribution and treatment effectiveness, with vascular density and regularity playing a crucial role in treatment success. On the contrary, carbon ions exhibit distinct effectiveness, even in areas of intense hypoxia and poor vascularization. This finding points to the potential of carbon-based hadron therapy in overcoming hypoxia-induced resistance to RT. Considering that the spatial scale analyzed in this study is closely aligned with that of imaging data voxels, we also address the implications of these findings in a clinical context envisioning the possibility of detecting subvoxel hypoxia.

Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient-specific or population-based biological features

BACKGROUND

Escalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially-varying characteristics of the disease.

PURPOSE

To examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient-specific and population-based spatial maps of tumor biological features.

METHOD

High-resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient-specific "maps" and a population-based "atlas" of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population-based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo-fractionation (EH), moderate hypo-fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions.

RESULTS

TCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population-based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population-based atlas and tumor probability maps did not differ significantly from those using patient-specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate.

CONCLUSION

Heterogeneous dose prescriptions generated via biologically-optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient-specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions.

Alpha Particle-Emitting Radiopharmaceuticals as Cancer Therapy: Biological Basis, Current Status, and Future Outlook for Therapeutics Discovery

Critical advances in radionuclide therapy have led to encouraging new options for cancer treatment through the pairing of clinically useful radiation-emitting radionuclides and innovative pharmaceutical discovery. Of the various subatomic particles used in therapeutic radiopharmaceuticals, alpha (α) particles show great promise owing to their relatively large size, delivered energy, finite pathlength, and resulting ionization density. This review discusses the therapeutic benefits of α-emitting radiopharmaceuticals and their pairing with appropriate diagnostics, resulting in innovative "theranostic" platforms. Herein, the current landscape of α particle-emitting radionuclides is described with an emphasis on their use in theranostic development for cancer treatment. Commonly studied radionuclides are introduced and recent efforts towards their production for research and clinical use are described. The growing popularity of these radionuclides is explained through summarizing the biological effects of α radiation on cancer cells, which include DNA damage, activation of discrete cell death programs, and downstream immune responses. Examples of efficient α-theranostic design are described with an emphasis on strategies that lead to cellular internalization and the targeting of proteins involved in therapeutic resistance. Historical barriers to the clinical deployment of α-theranostic radiopharmaceuticals are also discussed. Recent progress towards addressing these challenges is presented along with examples of incorporating α-particle therapy in pharmaceutical platforms that can be easily converted into diagnostic counterparts.

Carbon Ions for Hypoxic Tumors: Are We Making the Most of Them?

Hypoxia, which is associated with abnormal vessel growth, is a characteristic feature of many solid tumors that increases their metastatic potential and resistance to radiotherapy. Carbon-ion radiation therapy, either alone or in combination with other treatments, is one of the most promising treatments for hypoxic tumors because the oxygen enhancement ratio decreases with increasing particle LET. Nevertheless, current clinical practice does not yet fully benefit from the use of carbon ions to tackle hypoxia. Here, we provide an overview of the existing experimental and clinical evidence supporting the efficacy of C-ion radiotherapy in overcoming hypoxia-induced radioresistance, followed by a discussion of the strategies proposed to enhance it, including different approaches to maximize LET in the tumors.

Hypoxia adapted relative biological effectiveness models for proton therapy: a simulation study

In proton therapy, a constant relative biological effectiveness (RBE) factor of 1.1 is applied although the RBE has been shown to depend on factors including the Linear Energy Transfer (LET). The biological effectiveness of radiotherapy has also been shown to depend on the level of oxygenation, quantified by the oxygen enhancement ratio (OER). To estimate the biological effectiveness across different levels of oxygenation the RBE-OER-weighted dose (ROWD) can be used. To investigate the consistency between different approaches to estimate ROWD, we implemented and compared OER models in a Monte Carlo (MC) simulation tool. Five OER models were explored: Wenzl and Wilkens 2011 (WEN), Tinganelliet al2015 (TIN), Strigariet al2018 (STR), Dahleet al2020 (DAH) and Meinet al2021 (MEI). OER calculations were combined with a proton RBE model and the microdosimetric kinetic model for ROWD calculations. ROWD and OER were studied for a water phantom scenario and a head and neck cancer case using hypoxia PET data for the OER calculation. The OER and ROWD estimates from the WEN, MEI and DAH showed good agreement while STR and TIN gave higher OER values and lower ROWD. The WEN, STR and DAH showed some degree of OER-LET dependency while this was negligible for the MEI and TIN models. The ROWD for all implemented models is reduced in hypoxic regions with an OER of 1.0-2.1 in the target volume. While some variations between the models were observed, all models display a large difference in the estimated dose from hypoxic and normoxic regions. This shows the potential to increase the dose or LET in hypoxic regions or reduce the dose to normoxic regions which again could lead to normal tissue sparing. With reliable hypoxia imaging, RBE-OER weighting could become a useful tool for proton therapy plan optimization.

The influence of hypoxia on LET and RBE relationships with implications for ultra-high dose rates and FLASH modelling

Objective. To investigate relationships between linear energy transfer (LET), fluence rates, changes in radiosensitivity and the oxygen enhancement ratio (OER) in different ion beams and extend these concepts to ultra-high dose rate (UHDR) or FLASH effects. Approach. LET values providing maximum relative biological effect (RBE), designated as LETU, are found for neon, carbon and helium beams. Proton experiments show reduced RBEs with depth in scattered (divergent) beams, but not with scanned beams, suggesting that instantaneous fluence rates (related to track separation distances) can modify RBE, all other RBE-determining factors being equal. Micro-volumetric energy transfer per μm3 (mVET) is defined by LET × fluence. High fluence rates will increase mVET rates, with proportional shifts of LETU to lower values due to more rapid energy transfer. From the relationship between LETU and OER at conventional dose rates, OER reductions in UHDR/FLASH exposures can be estimated and biological effective dose analysis of experimental lung and skin reactions becomes feasible. Main results. The Furusawa et al data show that hypoxic LETU values exceed their oxic counterparts. OER reduces from around 3–1.25 at LETU, although the relative radiosensitivities of the oxic and hypoxic α parameters (the OER(α)) exceed those of the standard OER values. Increased fluence rates are predicted to reduce LETU and OER. Large FLASH single doses will minimise RBE increments due to the β parameter reducing by a factor of 0.5–0.25 consistent with oxygen depletion, causing radioresistance. Similar results will occur for photons. Tissue α/β ratios increase by around 10 in FLASH conditions, agreeing with derived ion-beam dose rate equations. Significance. Increasing dose rates enhance local energy deposition rate per unit volume, probably causing oxygen depletion and radioresistance in pre-existing hypoxic sites during UHDR/FLASH exposures. The modelled equations provide testable hypotheses for further dose rate investigations in photon, proton and ion beams.

Adaptation of stochastic microdosimetric kinetic model to hypoxia for hypo-fractionated multi-ion therapy treatment planning

For hypo-fractionated multi-ion therapy (HFMIT), the stochastic microdosimetric kinetic (SMK) model had been developed to estimate the biological effectiveness of radiation beams with wide linear energy transfer (LET) and dose ranges. The HFMIT will be applied to radioresistant tumors with oxygen-deficient regions. The response of cells to radiation is strongly dependent on the oxygen condition in addition to radiation type, LET and absorbed dose. This study presents an adaptation of the SMK model to account for oxygen-pressure dependent cell responses, and develops the oxygen-effect-incorporated stochastic microdosimetric kinetic (OSMK) model. In the model, following assumptions were made: the numbers of radiation-induced sublethal lesions (double-strand breaks) are reduced due to lack of oxygen, and the numbers of oxygen-mediated lesions are reduced for radiation with high LET. The model parameters were determined by fitting survival data under aerobic and anoxic conditions for human salivary gland tumor cells and V79 cells exposed to helium-, carbon-, and neon-ion beams over the LET range of 18.5-654.0 keVμm^-1. The OSMK model provided good agreement with the experimental survival data of the cells with determination coefficients >0.9. In terms of oxygen enhancement ratio, the OSMK model reproduced the experimental data behavior, including slight dependence on particle type at the same LET. The OSMK model was then implemented into the in-house treatment planning software for the HFMIT to validate its applicability in clinical practice. A treatment plan with helium- and neon-ion beams was made for a pancreatic cancer case assuming an oxygen-deficient region within the tumor. The biological optimization based on the OSMK model preferentially placed the neon-ion beam to the hypoxic region, while it placed both helium- and neon-ion beams to the surrounding normoxic region. The OSMK model offered the accuracy and usability required for hypoxia-based biological optimization in HFMIT treatment planning.

FLASH radiotherapy with carbon ion beams

FLASH radiotherapy is considered a new potential breakthrough in cancer treatment. Ultra-high dose rates (>40 Gy/s) have been shown to reduce toxicity in the normal tissue without compromising tumor control, resulting in a widened therapeutic window. These high dose rates are more easily achievable in the clinic with charged particles, and clinical trials are, indeed, ongoing using electrons or protons. FLASH could be an attractive solution also for heavier ions such as carbon and could even enhance the therapeutic window. However, it is not yet known whether the FLASH effect will be the same as for sparsely ionizing radiation when densely ionizing carbons ions are used. Here we discuss the technical challenges in beam delivery and present a promising solution using 3D range-modulators in order to apply ultra-high dose rates (UHDR) compatible with FLASH with carbon ions. Furthermore, we will discuss the possible outcome of C-ion therapy at UHDR on the level of the radiobiological and radiation chemical effects.

Dose Calculation Algorithms for External Radiation Therapy: An Overview for Practitioners

Radiation therapy (RT) is a constantly evolving therapeutic technique; improvements are continuously being introduced for both methodological and practical aspects. Among the features that have undergone a huge evolution in recent decades, dose calculation algorithms are still rapidly changing. This process is propelled by the awareness that the agreement between the delivered and calculated doses is of paramount relevance in RT, since it could largely affect clinical outcomes. The aim of this work is to provide an overall picture of the main dose calculation algorithms currently used in RT, summarizing their underlying physical models and mathematical bases, and highlighting their strengths and weaknesses, referring to the most recent studies on algorithm comparisons. This handy guide is meant to provide a clear and concise overview of the topic, which will prove useful in helping clinical medical physicists to perform their responsibilities more effectively and efficiently, increasing patient benefits and improving the overall quality of the management of radiation treatment.

A systematic review on the usage of averaged LET in radiation biology for particle therapy

Linear Energy Transfer (LET) is widely used to express the radiation quality of ion beams, when characterizing the biological effectiveness. However, averaged LET may be defined in multiple ways, and the chosen definition may impact the resulting reported value. We review averaged LET definitions found in the literature, and quantify which impact using these various definitions have for different reference setups. We recorded the averaged LET definitions used in 354 publications quantifying the relative biological effectiveness (RBE) of hadronic beams, and investigated how these various definitions impact the reported averaged LET using a Monte Carlo particle transport code. We find that the kind of averaged LET being applied is, generally, poorly defined. Some definitions of averaged LET may influence the reported averaged LET values up to an order of magnitude. For publications involving protons, most applied dose averaged LET when reporting RBE. The absence of what target medium is used and what secondary particles are included further contributes to an ill-defined averaged LET. We also found evidence of inconsistent usage of averaged LET definitions when deriving LET-based RBE models. To conclude, due to commonly ill-defined averaged LET and to the inherent problems of LET-based RBE models, averaged LET may only be used as a coarse indicator of radiation quality. We propose a more rigorous way of reporting LET values, and suggest that ideally the entire particle fluence spectra should be recorded and provided for future RBE studies, from which any type of averaged LET (or other quantities) may be inferred.

Boronated Condensed DNA as a Heterochromatic Radiation Target Model

The compound 4-dihydroxyboryl-l-phenylalanine (BPA) has found use in clinical trials of boron neutron capture therapy (BNCT). Here, we have examined the interaction with DNA of an amide-blocked BPA derivative of hexa-l-arginine (Ac-BPA-Arg6-NH2). Physical and spectroscopic assays show that this peptide binds to and condenses DNA. The resulting condensates are highly resistant to the effects of nuclease incubation (68-fold) and gamma (38-fold) irradiation. Radioprotection was modeled by Monte Carlo track structure simulations of DNA single strand breaks (SSBs) with TOPAS-nBio. The differences between experimental and simulated SSB yields for uncondensed and condensed DNAs were ca. 2 and 18%, respectively. These observations indicate that the combination of a plasmid DNA target, the BPA-containing peptide, and track structure simulation provides a powerful approach to characterize DNA damage by the high-LET radiation associated with neutron capture on boron.

Assessment of RBE-Weighted Dose Models for Carbon Ion Therapy Toward Modernization of Clinical Practice at HIT: In Vitro, in Vivo, and in Patients

PURPOSE

Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation.

METHODS

Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LET_d), and base-line photon radio-sensitivity (α/β)_x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases.

RESULTS

RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters α_x and β_x.

CONCLUSION

RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts.

The effect of CELLFOODTM on radiotherapy or combined chemoradiotherapy: preclinical evidence

Background

Based on previous observations that the nutraceutical CELLFOOD™ (CF), the 'physiological modulator' that aimed to make oxygen available 'on demand', inhibits the growth of cancer cells, this study was designed to investigate the role of CF in the regulation of hypoxia-inducible factor 1 alpha (HIF1α) and its correlated proteins, phosphoglycerate kinase 1 and vascular endothelial growth factor. Our idea was that CF, acting on HIF1α, in combination with current anticancer therapies could improve their effectiveness.

Methods

To evaluate the effect of CF in association with radiotherapy and chemotherapy, different human cancer cell lines and mice with mesothelioma were analysed by tumour growth, clonogenic assay, western blot and immunohistochemical analysis.

Results

CF in combination with radiation with or without cisplatin increases the death rate of cancer cells. In vivo, 70% of mice treated with CF before the mesothelioma graft did not show any tumour growth, indicating a possible preventive effect of CF. Moreover, in mouse mesothelioma xenografts, CF improves the effect of radiotherapy also in combination with chemotherapy treatment. Immunohistochemical analysis of tumour explants showed that HIF1α expression was reduced by the combination of CF and radiotherapy treatment and even more by the combination of CF and radiotherapy and chemotherapy treatment. Mechanistically, CF increases the fraction of oxygenated cells, making the radiotherapy more effective with a greater production of reactive oxygen species (ROS) that in turn, reduce the HIF1α expression. This effect is amplified by further increase in ROS from chemotherapy.

Conclusions

Collectively, results from preclinical trials suggest that CF could be a useful intervention to improve the efficacy of radiotherapy or combined treatment strategies and could be a promising treatment modality to counteract cancer.

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.

Preliminary exploration of clinical factors affecting acute toxicity and quality of life after carbon ion therapy for prostate cancer

Purpose

To assess toxicity and quality-of-life (QOL) after carbon ion radiotherapy (CIRT) at the Shanghai Proton and Heavy Ion Center (SPHIC) and identify clinical factors that correlate with urinary, bowel and sexual function.

Methods

Sixty-four patients with localized prostate cancer admitted from July 2015 to January 2018 underwent CIRT. At baseline and 5 time-points after radiotherapy, we assessed patients’ QOL using the 26-item edition of the Expanded Prostate Cancer Index-Composite (EPIC-26) Chinese version. Logistic regression was performed to identify clinical factors associated with acute genitourinary (GU) toxicity and relative QOL.

Results

By the end of CIRT, urinary irritation/obstruction temporarily declined (− 7.92 ± 1.76, p < .001). For urinary incontinence, bowel and sexual QOL, the scores remained stable at 2-year follow-up. The occurrences of acute Grade 1 and 2 GU toxicity were 20.3 and 10.9%, respectively, and of late Grade 1 and 2 GU toxicity were 3.1 and 1.6%, respectively. No acute or late gastrointestinal (GI) toxicity occurred. Transurethral resection of the prostate (TURP) was a risk factor that predicted a decline in urinary related QOL, and age made a difference to bowel-related QOL. For sexual QOL, castration status was a remarkable risk factor. An international prostate symptom score (IPSS) ≥8 increased the risk of Grade 1–2 acute GU toxicity 5.3-fold.

Conclusion

Patients with prostate cancer had favorable QOL after CIRT. IPSS ≥8 was a risk factor to acute GU toxicity, and TURP predicted a decline in urinary QOL. Age was related to bowel QOL, and castration status was associated with sexual QOL.

Trial registration

Carbon Ion Radiotherapy for the Treatment of Localized Prostate Cancer, NCT02739659. Registered April 15, 2016.

A comparison of mechanism-inspired models for particle relative biological effectiveness (RBE)

BACKGROUND AND SIGNIFICANCE

The application of heavy ion beams in cancer therapy must account for the increasing relative biological effectiveness (RBE) with increasing penetration depth when determining dose prescriptions and organ at risk (OAR) constraints in treatment planning. Because RBE depends in a complex manner on factors such as the ion type, energy, cell and tissue radiosensitivity, physical dose, biological endpoint, and position within and outside treatment fields, biophysical models reflecting these dependencies are required for the personalization and optimization of treatment plans.

AIM

To review and compare three mechanism-inspired models which predict the complexities of particle RBE for various ion types, energies, linear energy transfer (LET) values and tissue radiation sensitivities.

METHODS

The review of models and mechanisms focuses on the Local Effect Model (LEM), the Microdosimetric-Kinetic (MK) model, and the Repair-Misrepair-Fixation (RMF) model in combination with the Monte Carlo Damage Simulation (MCDS). These models relate the induction of potentially lethal double strand breaks (DSBs) to the subsequent interactions and biological processing of DSB into more lethal forms of damage. A key element to explain the increased biological effectiveness of high LET ions compared to MV x rays is the characterization of the number and local complexity (clustering) of the initial DSB produced within a cell. For high LET ions, the spatial density of DSB induction along an ion's trajectory is much greater than along the path of a low LET electron, such as the secondary electrons produced by the megavoltage (MV) x rays used in conventional radiation therapy. The main aspects of the three models are introduced and the conceptual similarities and differences are critiqued and highlighted. Model predictions are compared in terms of the RBE for DSB induction and for reproductive cell survival.

RESULTS AND CONCLUSIONS

Comparisons of the RBE for DSB induction and for cell survival are presented for proton (¹ H), helium (⁴ He), and carbon (¹² C) ions for the therapeutically most relevant range of ion beam energies. The reviewed models embody mechanisms of action acting over the spatial scales underlying the biological processing of potentially lethal DSB into more lethal forms of damage. Differences among the number and types of input parameters, relevant biological targets, and the computational approaches among the LEM, MK and RMF models are summarized and critiqued. Potential experiments to test some of the seemingly contradictory aspects of the models are discussed.