The use of radiotherapy, surgery and chemotherapy in the curative treatment of cancer: results from the FORTY (Favourable Outcomes from RadioTherapY) project.

OBJECTIVES: Radiotherapy, surgery and chemotherapy play key roles in the curative treatment of cancer, alone and in combination. Quantifying their roles is essential for equipment provision and workforce planning. The estimate that 40% of cancer patients are cured by RT has been used extensively to inform and influence policy but is relatively old and warrants review. METHODS: Patient, tumour and treatment event data was obtained for the 5 year period from 2009 to 2013, allowing a further 5 years for survival outcomes to be known. We analysed patient-level data on utilisation of surgery, radiotherapy, and chemotherapy in cancer patients in England. Data were sourced from Public Health England, using National Cancer Registrations, the National Radiotherapy Dataset (RTDS) and the Systemic Anti-Cancer Therapy Dataset (SACT). All tumour sites (excluding C44) and ages were included. We analysed three cohorts: all patients [n = 1,029,569], patients who survived 5 years or more [n = 537,970] and patients who survived <5 years [n = 491,599]. RESULTS: Overall cancer-specific 5-year survival was 52%, and in those patients, surgery was the most common curative treatment, with 80% receiving surgery, alone or in combination; radiotherapy was delivered to 39% and chemotherapy to 29%; 45% received two and 13% all three modalities. CONCLUSIONS: The high proportion receiving multi-modality treatment emphasises the importance of integrated, resourced, multidisciplinary cancer care. Radiotherapy was delivered to almost 40% of patients who survived 5 years which underlines its importance in cancer management. ADVANCES IN KNOWLEDGE: The results are essential in planning cancer services. They also inform the public health narrative.

A computational approach to quantifying miscounting of radiation-induced double-strand break immunofluorescent foci.

Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting.

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy.

OBJECTIVES: High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision. METHODS: Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined. RESULTS: The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%. CONCLUSIONS: The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking. ADVANCES IN KNOWLEDGE: Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.

The suitability of micronuclei as markers of relative biological effect.

Micronucleus (MN) formation is routinely used as a biodosimeter for radiation exposures and has historically been used as a measure of DNA damage in cells. Strongly correlating with dose, MN are also suggested to indicate radiation quality, differentiating between particle and photon irradiation. The "gold standard" for measuring MN formation is Fenech's cytokinesis-block micronucleus (CBMN) cytome assay, which uses the cytokinesis blocking agent cytochalasin-B. Here, we present a comprehensive analysis of the literature investigating MN induction trends in vitro, collating 193 publications, with 2476 data points. Data were collected from original studies that used the CBMN assay to quantify MN in response to ionizing radiation in vitro. Overall, the meta-analysis showed that individual studies mostly have a linear increase of MN with dose [85% of MN per cell (MNPC) datasets and 89% of percentage containing MN (PCMN) datasets had an R2 greater than 0.90]. However, there is high variation between studies, resulting in a low R2 when data are combined (0.47 for MNPC datasets and 0.60 for PCMN datasets). Particle type, species, cell type, and cytochalasin-B concentration were suggested to influence MN frequency. However, variation in the data meant that the effects could not be strongly correlated with the experimental parameters investigated. There is less variation between studies when comparing the PCMN rather than the number of MNPC. Deviation from CBMN protocol specified timings did not have a large effect on MN induction. However, further analysis showed less variation between studies following Fenech's protocol closely, which provided more reliable results. By limiting the cell type and species as well as only selecting studies following the Fenech protocol, R2 was increased to 0.64 for both measures. We therefore determine that due to variation between studies, MN are currently a poor predictor of radiation-induced DNA damage and make recommendations for futures studies assessing MN to improve consistency between datasets.

A Monte Carlo study of different LET definitions and calculation parameters for proton beam therapy.

The strongin vitroevidence that proton Relative Biological Effectiveness (RBE) varies with Linear Energy Transfer (LET) has led to an interest in applying LET within treatment planning. However, there is a lack of consensus on LET definition, Monte Carlo (MC) parameters or clinical methodology. This work aims to investigate how common variations of LET definition may affect potential clinical applications. MC simulations (GATE/GEANT4) were used to calculate absorbed dose and different types of LET for a simple Spread Out Bragg Peak (SOBP) and for four clinical PBT plans covering a range of tumour sites. Variations in the following LET calculation methods were considered: (i) averaging (dose-averaged LET (LETd) & track-averaged LET); (ii) scoring (LETdto water, to medium and to mass density); (iii) particle inclusion (LETdto all protons, to primary protons and to particles); (iv) MC settings (hit type and Maximum Step Size (MSS)). LET distributions were compared using: qualitative comparison, LET Volume Histograms (LVHs), single value criteria (maximum and mean values) and optimised LET-weighted dose models. Substantial differences were found between LET values in averaging, scoring and particle type. These differences depended on the methodology, but for one patient a difference of ∼100% was observed between the maximum LETdfor all particles and maximum LETdfor all protons within the brainstem in the high isodose region (4 keVµm-1and 8 keVµm-1respectively). An RBE model using LETdincluding heavier ions was found to predict substantially different LET-weighted dose compared to those using other LET definitions. In conclusion, the selection of LET definition may affect the results of clinical metrics considered in treatment planning and the results of an RBE model. The authors' advocate for the scoring of dose-averaged LET to water for primary and secondary protons using a random hit type and automated MSS.

Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage.

Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.

Heavy charged particle beam therapy and related new radiotherapy technologies: The clinical potential, physics and technical developments required to deliver benefit for patients with cancer.

In the UK, one in two people will develop cancer during their lifetimes and radiotherapy (RT) plays a key role in effective treatment. High energy proton beam therapy commenced in the UK National Health Service in 2018. Heavier charged particles have potential advantages over protons by delivering more dose in the Bragg peak, with a sharper penumbra, lower oxygen dependence and increased biological effectiveness. However, they also require more costly equipment including larger gantries to deliver the treatment. There are significant uncertainties in the modelling of relative biological effectiveness and the effects of the fragmentation tail which can deliver dose beyond the Bragg peak. These effects need to be carefully considered especially in relation to long-term outcomes.In 2019, a group of clinicians, clinical scientists, engineers, physical and life scientists from academia and industry, together with funding agency stakeholders, met to consider how the UK should address new technologies for RT, especially the use of heavier charged particles such as helium and carbon and new modes of delivery such as FLASH and spatially fractionated radiotherapy (SFRT).There was unanimous agreement that the UK should develop a facility for heavier charged particle therapy, perhaps constituting a new National Ion Research Centre to enable research using protons and heavier charged particles. Discussion followed on the scale and features, including which ions should be included, from protons through helium, boron, and lithium to carbon, and even oxygen. The consensus view was that any facility intended to treat patients must be located in a hospital setting while providing dedicated research space for physics, preclinical biology and clinical research with beam lines designed for both in vitro and in vivo research. The facility should to be able to investigate and deliver both ultra-high dose rate FLASH RT and SFRT (GRID, minibeams etc.). Discussion included a number of accelerator design options and whether gantries were required. Other potential collaborations might be exploited, including with space agencies, electronics and global communications industries and the nuclear industry.In preparation for clinical delivery, there may be opportunities to send patients overseas (for 12C or 4He ion therapy) using the model of the National Health Service (NHS) Proton Overseas Programme and to look at potential national clinical trials which include heavier ions, FLASH or SFRT. This could be accomplished under the auspices of NCRI CTRad (National Cancer Research Institute, Clinical and Translational Radiotherapy Research Working Group).The initiative should be a community approach, involving all interested parties with a vision that combines discovery science, a translational research capability and a clinical treatment facility. Barriers to the project and ways to overcome them were discussed. Finally, a set of different scenarios of features with different costs and timelines was constructed, with consideration given to the funding environment (prer-Covid-19) and need for cross-funder collaboration.

Radiobiologically derived biphasic fractionation schemes to overcome the effects of tumour hypoxia.

OBJECTIVE: As a fractionated course of radiotherapy proceeds tumour shrinkage leads to resolution of hypoxia and the initiation of accelerated proliferation of radioresistant cancer cells with better repair capacity. We hypothesise that, in tumours with significant hypoxia, improved tumour control could be achieved with biphasic fractionation schedules that either use acceleration after 3-4 weeks of conventional radiotherapy or deliver a higher proportional dose towards the end of a course of treatment. We conducted a modelling study based on the concept of biological effective dose (BED) comparing such novel regimens with conventional fractionation. METHODS: The comparator conventional fractionation schedule 70 Gy in 35 fractions delivered over 7 weeks was tested against the following novel regimens, both of which were designed to be isoeffective in terms of late normal tissue toxicity.40 Gy in 20 fractions over 4 weeks followed by 22.32 Gy in 6 consecutive daily fractions (delayed acceleration)30.4 Gy in 27 fractions over 4 weeks followed by 40 Gy in 15 fractions over 3 weeks (temporal dose redistribution)The delayed acceleration regimen is exactly identical to that of the comparator schedule over the first 28 days and the BED gains with the novel schedule are achieved during the second phase of treatment when reoxygenation is complete. For the temporal redistribution regimen, it was assumed that the reoxygenation fraction progressively increases during the first 4 weeks of treatment and an iterative approach was used to calculate the final tumour BED for varying hypoxic fractions. RESULTS: Novel fractionation with delayed acceleration or temporal fractionation results in tumour BED gains equivalent to 3.5-8 Gy when delivered in 2 Gy fractions. CONCLUSION: In hypoxic tumours, novel fractionation strategies result in significantly higher tumour BED in comparison to conventional fractionation. ADVANCES IN KNOWLEDGE: We demonstrate that novel biphasic fractionation regimens could overcome the effects of tumour hypoxia resulting in biological dose escalation.

Proton beam therapy: perspectives on the National Health Service England clinical service and research programme.

The UK has an important role in the evaluation of proton beam therapy (PBT) and takes its place on the world stage with the opening of the first National Health Service (NHS) PBT centre in Manchester in 2018, and the second in London coming in 2020. Systematic evaluation of the role of PBT is a key objective. By September 2019, 108 patients had started treatment, 60 paediatric, 19 teenagers and young adults and 29 adults. Obtaining robust outcome data is vital, if we are to understand the strengths and weaknesses of current treatment approaches. This is important in demonstrating when PBT will provide an advantage and when it will not, and in quantifying the magnitude of benefit.The UK also has an important part to play in translational PBT research, and building a research capability has always been the vision. We are perfectly placed to perform translational pre-clinical biological and physical experiments in the dedicated research room in Manchester. The nature of DNA damage from proton irradiation is considerably different from X-rays and this needs to be more fully explored. A better understanding is needed of the relative biological effectiveness (RBE) of protons, especially at the end of the Bragg peak, and of the effects on tumour and normal tissue of PBT combined with conventional chemotherapy, targeted drugs and immunomodulatory agents. These experiments can be enhanced by deterministic mathematical models of the molecular and cellular processes of DNA damage response. The fashion of ultra-high dose rate FLASH irradiation also needs to be explored.

A systematic review of health economic evaluations of proton beam therapy for adult cancer: Appraising methodology and quality.

BACKGROUND AND PURPOSE: With high treatment costs and limited capacity, decisions on which adult patients to treat with proton beam therapy (PBT) must be based on the relative value compared to the current standard of care. Cost-utility analyses (CUAs) are the gold-standard method for doing this. We aimed to appraise the methodology and quality of CUAs in this area. MATERIALS AND METHODS: We performed a systematic review of the literature to identify CUA studies of PBT in adult disease using MEDLINE, EMBASE, EconLIT, NHS Economic Evaluation Database (NHS EED), Web of Science, and the Tufts Medical Center Cost-Effectiveness Analysis Registry from 1st January 2010 up to 6th June 2018. General characteristics, information relating to modelling approaches, and methodological quality were extracted and synthesized narratively. RESULTS: Seven PBT CUA studies in adult disease were identified. Without randomised controlled trials to inform the comparative effectiveness of PBT, studies used either results from one-armed studies, or dose-response models derived from radiobiological and epidemiological studies of PBT. Costing methods varied widely. The assessment of model quality highlighted a lack of transparency in the identification of model parameters, and absence of external validation of model outcomes. Furthermore, appropriate assessment of uncertainty was often deficient. CONCLUSION: In order to foster credibility, future CUA studies must be more systematic in their approach to evidence synthesis and expansive in their consideration of uncertainties in light of the lack of clinical evidence.

Using the Malthus programme to predict the recruitment of patients to MR-linac research trials in prostate and lung cancer.

In this study, we used evidence-based mathematical modelling to predict the patient cohort for MR-linac to assess its feasibility in a time of austerity. We discuss our results and the implications of evidence-based radiotherapy demand modelling tools such as Malthus on the implementation of new technology and value-based healthcare.

Modelling and Bayesian adaptive prediction of individual patients' tumour volume change during radiotherapy.

The aim of this study is to develop a mathematical modelling method that can predict individual patients' response to radiotherapy, in terms of tumour volume change during the treatment. The main concept is to start from a population-average model, which is subsequently updated from an individual's tumour volume measurement. The model becomes increasingly personalized and so too does the prediction it produces. This idea of adaptive prediction was realised by using a Bayesian approach for updating the model parameters. The feasibility of the developed method was demonstrated on the data from 25 non-small cell lung cancer patients treated with helical tomotherapy, during which tumour volume was measured from daily imaging as part of the image-guided radiotherapy. The method could provide useful information for adaptive treatment planning and dose scheduling based on the patient's personalised response.

Mathematical modelling of tumour volume dynamics in response to stereotactic ablative radiotherapy for non-small cell lung cancer.

This paper reports a modelling study of tumour volume dynamics in response to stereotactic ablative radiotherapy (SABR). The main objective was to develop a model that is adequate to describe tumour volume change measured during SABR, and at the same time is not excessively complex as lacking support from clinical data. To this end, various modelling options were explored, and a rigorous statistical method, the Akaike information criterion, was used to help determine a trade-off between model accuracy and complexity. The models were calibrated to the data from 11 non-small cell lung cancer patients treated with SABR. The results showed that it is feasible to model the tumour volume dynamics during SABR, opening up the potential for using such models in a clinical environment in the future.

The effect of the G1-S transition checkpoint on an age structured cell cycle model.

Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the errors present in these estimates may effect treatment efficacy and planning. If mathematical models are to be used to make accurate, quantitative predictions concerning treatments, whose efficacy is phase dependent, knowledge of the phase distribution is crucial. In this paper it is shown that two different transition rates at the G1-S checkpoint provide a good fit to a growth curve obtained experimentally. However, the different transition functions predict a different phase distribution for the population, but both lying within the bounds of experimental error. Since treatment outcome is effected by the phase distribution of the population this difference may be critical in treatment planning. Using an age-structured population balance approach the cell cycle is modelled with particular emphasis on the G1-S checkpoint. By considering the probability of cells transitioning at the G1-S checkpoint, different transition functions are obtained. A suitable finite difference scheme for the numerical simulation of the model is derived and shown to be stable. The model is then fitted using the different probability transition functions to experimental data and the effects of the different probability transition functions on the model's results are discussed.

Hadron therapy information sharing prototype.

The European PARTNER project developed a prototypical system for sharing hadron therapy data. This system allows doctors and patients to record and report treatment-related events during and after hadron therapy. It presents doctors and statisticians with an integrated view of adverse events across institutions, using open-source components for data federation, semantics, and analysis. There is a particular emphasis upon semantic consistency, achieved through intelligent, annotated form designs. The system as presented is ready for use in a clinical setting, and amenable to further customization. The essential contribution of the work reported here lies in the novel data integration and reporting methods, as well as the approach to software sustainability achieved through the use of community-supported open-source components.

Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy.

Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of 'general Markov models', providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy and argue that the proposed method can automate the creation of Markov models from existing data. The approach has the potential to support the radiotherapy community in conducting systematic analyses involving predictive modelling of existing and upcoming radiotherapy data. We expect it to facilitate the application of modelling techniques in medical decision problems beyond the field of radiotherapy, and to improve the comparability of their results.

Evaluation of poly (ADP-ribose) polymerase inhibitor ABT-888 combined with radiotherapy and temozolomide in glioblastoma.

BACKGROUND: The cytotoxicity of radiotherapy and chemotherapy can be enhanced by modulating DNA repair. PARP is a family of enzymes required for an efficient base-excision repair of DNA single-strand breaks and inhibition of PARP can prevent the repair of these lesions. The current study investigates the trimodal combination of ABT-888, a potent inhibitor of PARP1-2, ionizing radiation and temozolomide(TMZ)-based chemotherapy in glioblastoma (GBM) cells. METHODS: Four human GBM cell lines were treated for 5 h with 5 µM ABT-888 before being exposed to X-rays concurrently with TMZ at doses of 5 or 10 µM for 2 h. ABT-888's PARP inhibition was measured using immunodetection of poly(ADP-ribose) (pADPr). Cell survival and the different cell death pathways were examined via clonogenic assay and morphological characterization of the cell and cell nucleus. RESULTS: Combining ABT-888 with radiation yielded enhanced cell killing in all four cell lines, as demonstrated by a sensitizer enhancement ratio at 50% survival (SER50) ranging between 1.12 and 1.37. Radio- and chemo-sensitization was further enhanced when ABT-888 was combined with both X-rays and TMZ in the O6-methylguanine-DNA-methyltransferase (MGMT)-methylated cell lines with a SER50 up to 1.44. This effect was also measured in one of the MGMT-unmethylated cell lines with a SER50 value of 1.30. Apoptosis induction by ABT-888, TMZ and X-rays was also considered and the effect of ABT-888 on the number of apoptotic cells was noticeable at later time points. In addition, this work showed that ABT-888 mediated sensitization is replication dependent, thus demonstrating that this effect might be more pronounced in tumour cells in which endogenous replication lesions are present in a larger proportion than in normal cells. CONCLUSIONS: This study suggests that ABT-888 has the clinical potential to enhance the current standard treatment for GBM, in combination with conventional chemo-radiotherapy. Interestingly, our results suggest that the use of PARP inhibitors might be clinically significant in those patients whose tumour is MGMT-unmethylated and currently derive less benefit from TMZ.

Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation.

Model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated.