Functional consequences of a p53-MDM2-p21 incoherent feedforward loop.

Genetically identical cells can respond heterogeneously to cancer therapy, with a subpopulation of cells often entering a temporarily arrested treatment-tolerant state before repopulating the tumor. To investigate how heterogeneity in the cell cycle arrest protein p21 arises, we imaged the dynamics of p21 transcription and protein expression along with those of p53, its transcriptional regulator, in single cells using live cell fluorescence microscopy. Surprisingly, we found that the rate of p21 transcription depends on the change in p53 rather than its absolute level. Through combined theoretical and experimental modeling, we determined that p21 transcription is governed by an incoherent feedforward loop mediated by MDM2. This network architecture facilitates rapid induction of p21 expression and variability in p21 transcription. Abrogating the feedforward loop overcomes rapid S-phase p21 degradation, with cells transitioning into a quiescent state that transcriptionally resembles a treatment-tolerant persister state. Our findings have important implications for therapeutic strategies based on activating p53.

Using diffusion MRI to understand white matter damage and the link between brain microstructure and cognitive deficits in paediatric medulloblastoma patients.

PURPOSE: Survivors of medulloblastoma face a range of challenges after treatment, involving behavioural, cognitive, language and motor skills. Post-treatment outcomes are associated with structural changes within the brain resulting from both the tumour and the treatment. Diffusion magnetic resonance imaging (MRI) has been used to investigate the microstructure of the brain. In this review, we aim to summarise the literature on diffusion MRI in patients treated for medulloblastoma and discuss future directions on how diffusion imaging can be used to improve patient quality. METHOD: This review summarises the current literature on medulloblastoma in children, focusing on the impact of both the tumour and its treatment on brain microstructure. We review studies where diffusion MRI has been correlated with either treatment characteristics or cognitive outcomes. We discuss the role diffusion MRI has taken in understanding the relationship between microstructural damage and cognitive and behavioural deficits. RESULTS: We identified 35 studies that analysed diffusion MRI changes in patients treated for medulloblastoma. The majority of these studies found significant group differences in measures of brain microstructure between patients and controls, and some of these studies showed associations between microstructure and neurocognitive outcomes, which could be influenced by patient characteristics (e.g. age), treatment, radiation dose and treatment type. CONCLUSIONS: In future, studies would benefit from being able to separate microstructural white matter damage caused by the tumour, tumour-related complications and treatment. Additionally, advanced diffusion modelling methods can be explored to understand and describe microstructural changes to white matter.

Radiation Reveal: Moving from research engagement to involvement.

Here, we report on the process of a highly impactful and successful creative, collaborative, and multi-partner public engagement project, Radiation Reveal. It brought together ten young adults aged 17-25-year-olds with experience of radiotherapy with researchers at Cancer Research UK RadNet City of London across three 2-hour online workshops. Our aims were to 1) initiate discussions between young adults and radiation researchers, and 2) identify what people wish they had known about radiotherapy before or during treatment. These aims were surpassed; other benefits included peer support, participants' continued involvement in subsequent engagement projects, lasting friendships, creation of support groups for others, and creation and national dissemination of top ten tips for medical professionals and social media resources. A key learning was that this project required a dedicated and (com)passionate person with connections to national cancer charities. When designing the project, constant feedback is also needed from charities and young adults with and without radiotherapy experience. Finally, visually capturing discussions and keeping the door open beyond workshops further enhanced impact. Here, we hope to inform and inspire people to help project the patient voice in all we do.

Phase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity.

BACKGROUND: Glioblastomas comprise heterogeneous cell populations with dynamic, bidirectional plasticity between treatment-resistant stem-like and treatment-sensitive differentiated states, with treatment influencing this process. However, current treatment protocols do not account for this plasticity. Previously, we generated a mathematical model based on preclinical experiments to describe this process and optimize a radiation therapy fractionation schedule that substantially increased survival relative to standard fractionation in a murine glioblastoma model. METHODS: We developed statistical models to predict the survival benefit of interventions to glioblastoma patients based on the corresponding survival benefit in the mouse model used in our preclinical study. We applied our mathematical model of glioblastoma radiation response to optimize a radiation therapy fractionation schedule for patients undergoing re-irradiation for glioblastoma and developed a first-in-human trial (NCT03557372) to assess the feasibility and safety of administering our schedule. RESULTS: Our statistical modeling predicted that the hazard ratio when comparing our novel radiation schedule with a standard schedule would be 0.74. Our mathematical modeling suggested that a practical, near-optimal schedule for re-irradiation of recurrent glioblastoma patients was 3.96 Gy × 7 (1 fraction/day) followed by 1.0 Gy × 9 (3 fractions/day). Our optimized schedule was successfully administered to 14/14 (100%) patients. CONCLUSIONS: A novel radiation therapy schedule based on mathematical modeling of cell-state plasticity is feasible and safe to administer to glioblastoma patients.

Spatial intra-tumor heterogeneity is associated with survival of lung adenocarcinoma patients.

Intra-tumor heterogeneity (ITH) of human tumors is important for tumor progression, treatment response, and drug resistance. However, the spatial distribution of ITH remains incompletely understood. Here, we present spatial analysis of ITH in lung adenocarcinomas from 147 patients using multi-region mass spectrometry of >5,000 regions, single-cell copy number sequencing of ~2,000 single cells, and cyclic immunofluorescence of >10 million cells. We identified two distinct spatial patterns among tumors, termed clustered and random geographic diversification (GD). These patterns were observed in the same samples using both proteomic and genomic data. The random proteomic GD pattern, which is characterized by decreased cell adhesion and lower levels of tumor-interacting endothelial cells, was significantly associated with increased risk of recurrence or death in two independent patient cohorts. Our study presents comprehensive spatial mapping of ITH in lung adenocarcinoma and provides insights into the mechanisms and clinical consequences of GD.

Computational modelling of perivascular-niche dynamics for the optimization of treatment schedules for glioblastoma.

Glioblastoma stem-like cells dynamically transition between a chemoradiation-resistant state and a chemoradiation-sensitive state. However, physical barriers in the tumour microenvironment restrict the delivery of chemotherapy to tumour compartments that are distant from blood vessels. Here, we show that a massively parallel computational model of the spatiotemporal dynamics of the perivascular niche that incorporates glioblastoma stem-like cells and differentiated tumour cells as well as relevant tissue-level phenomena can be used to optimize the administration schedules of concurrent radiation and temozolomide-the standard-of-care treatment for glioblastoma. In mice with platelet-derived growth factor (PDGF)-driven glioblastoma, the model-optimized treatment schedule increased the survival of the animals. For standard radiation fractionation in patients, the model predicts that chemotherapy may be optimally administered about one hour before radiation treatment. Computational models of the spatiotemporal dynamics of the tumour microenvironment could be used to predict tumour responses to a broader range of treatments and to optimize treatment regimens.

Evaluation of erectile potency and radiation dose to the penile bulb using image guided radiotherapy in the CHHiP trial.

BACKGROUND AND PURPOSE: The penile bulb (PB) dose may be critical in development of post prostate radiotherapy erectile dysfunction (ED). This study aimed to generate PB dose constraints based on dose-volume histograms (DVHs) in patients treated with prostate radiotherapy, and to identify clinical and dosimetric parameters that predict the risk of ED post prostate radiotherapy. MATERIALS AND METHODS: Penile bulb DVHs were generated for 276 patients treated within the randomised IGRT substudy of the multicentre randomised trial, CHHiP. Incidence of ED in relation to dose and randomised IGRT groups were evaluated using Wilcoxon rank sum, Chi-squared test and atlases of complication incidence. Youden index was used to find dose-volume constraints that discriminated for ED. Multivariate analysis (MVA) of effect of dosimetry, clinical and patient-related variables was performed. RESULTS: Reduced treatment margins using IGRT (IGRT-R) produced significantly reduced mean PB dose compared with standard margins (IGRT-S) (median: 25 Gy (IGRT-S) versus 11 Gy (IGRT-R); p < 0.0001). Significant difference in both mean (median: 23 Gy (ED) vs. 18 Gy (no ED); p = 0.011) and maximum (median: 59 Gy (ED) vs. 52 Gy (no ED); p = 0.018) PB doses between those with and without clinician reported ED were identified. Mean PB dose cut-point for ED was derived at around 20 Gy. On MVA, PB mean dose and age predicted for impotence. CONCLUSION: PB dose appears predictive of post-radiotherapy ED with calculated threshold mean dose of around 20 Gy, substantially lower than published recommendations. IGRT-R enables favourable PB dosimetry and can be recommended provided prostate coverage is not compromised.

A randomised assessment of image guided radiotherapy within a phase 3 trial of conventional or hypofractionated high dose intensity modulated radiotherapy for prostate cancer.

BACKGROUND AND PURPOSE: Image-guided radiotherapy (IGRT) improves treatment set-up accuracy and provides the opportunity to reduce target volume margins. We introduced IGRT methods using standard (IGRT-S) or reduced (IGRT-R) margins in a randomised phase 2 substudy within CHHiP trial. We present a pre-planned analysis of the impact of IGRT on dosimetry and acute/late pelvic side effects using gastrointestinal and genitourinary clinician and patient-reported outcomes (PRO) and evaluate efficacy. MATERIALS AND METHODS: CHHiP is a randomised phase 3, non-inferiority trial for men with localised prostate cancer. 3216 patients were randomly assigned to conventional (74 Gy in 2 Gy/fraction (f) daily) or moderate hypofractionation (60 or 57 Gy in 3 Gy/f daily) between October 2002 and June 2011. The IGRT substudy included a second randomisation assigning to no-IGRT, IGRT-S (standard CTV-PTV margins), or IGRT-R (reduced CTV-PTV margins). Primary substudy endpoint was late RTOG bowel and urinary toxicity at 2 years post-radiotherapy. RESULTS: Between June 2010 to July 2011, 293 men were recruited from 16 centres. Median follow-up is 56.9(IQR 54.3-60.9) months. Rectal and bladder dose-volume and surface percentages were significantly lower in IGRT-R compared to IGRT-S group; (p < 0.0001). Cumulative proportion with RTOG grade ≥ 2 toxicity reported to 2 years for bowel was 8.3(95% CI 3.2-20.7)%, 8.3(4.7-14.6)% and 5.8(2.6-12.4)% and for urinary 8.4(3.2-20.8)%, 4.6(2.1-9.9)% and 3.9(1.5-9.9)% in no IGRT, IGRT-S and IGRT-R groups respectively. In an exploratory analysis, treatment efficacy appeared similar in all three groups. CONCLUSION: Introduction of IGRT was feasible in a national randomised trial and IGRT-R produced dosimetric benefits. Overall side effect profiles were acceptable in all groups but lowest with IGRT and reduced margins. ISRCTN: 97182923.

Incorporating spatial dose metrics in machine learning-based normal tissue complication probability (NTCP) models of severe acute dysphagia resulting from head and neck radiotherapy.

Severe acute dysphagia commonly results from head and neck radiotherapy (RT). A model enabling prediction of severity of acute dysphagia for individual patients could guide clinical decision-making. Statistical associations between RT dose distributions and dysphagia could inform RT planning protocols aiming to reduce the incidence of severe dysphagia. We aimed to establish such a model and associations incorporating spatial dose metrics. Models of severe acute dysphagia were developed using pharyngeal mucosa (PM) RT dose (dose-volume and spatial dose metrics) and clinical data. Penalized logistic regression (PLR), support vector classification and random forest classification (RFC) models were generated and internally (173 patients) and externally (90 patients) validated. These were compared using area under the receiver operating characteristic curve (AUC) to assess performance. Associations between treatment features and dysphagia were explored using RFC models. The PLR model using dose-volume metrics (PLRstandard) performed as well as the more complex models and had very good discrimination (AUC = 0.82) on external validation. The features with the highest RFC importance values were the volume, length and circumference of PM receiving 1 Gy/fraction and higher. The volumes of PM receiving 1 Gy/fraction or higher should be minimized to reduce the incidence of severe acute dysphagia.

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy.

PURPOSE: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue-sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. METHODS AND MATERIALS: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogram data. The reduced dose data were input into functional logistic regression models (functional partial least squares-logistic regression [FPLS-LR] and functional principal component-logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate-response associations, assessed using bootstrapping. RESULTS: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/-0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/-0.96, 0.79/-0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. CONCLUSIONS: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

BACKGROUND AND PURPOSE: Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. MATERIALS AND METHODS: Predictive models of severe acute mucositis were generated using radiotherapy dose (dose-volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. RESULTS: The dose-volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFCstandard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d.=0.09) and 3.9 (s.d.=2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. CONCLUSIONS: The RFCstandard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence.

Assessment of fully-automated atlas-based segmentation of novel oral mucosal surface organ-at-risk.

BACKGROUND AND PURPOSE: Current oral mucositis normal tissue complication probability models, based on the dose distribution to the oral cavity volume, have suboptimal predictive power. Improving the delineation of the oral mucosa is likely to improve these models, but is resource intensive. We developed and evaluated fully-automated atlas-based segmentation (ABS) of a novel delineation technique for the oral mucosal surfaces. MATERIAL AND METHODS: An atlas of mucosal surface contours (MSC) consisting of 46 patients was developed. It was applied to an independent test cohort of 10 patients for whom manual segmentation of MSC structures, by three different clinicians, and conventional outlining of oral cavity contours (OCC), by an additional clinician, were also performed. Geometric comparisons were made using the dice similarity coefficient (DSC), validation index (VI) and Hausdorff distance (HD). Dosimetric comparisons were carried out using dose-volume histograms. RESULTS: The median difference, in the DSC and HD, between automated-manual comparisons and manual-manual comparisons were small and non-significant (-0.024; p=0.33 and -0.5; p=0.88, respectively). The median VI was 0.086. The maximum normalised volume difference between automated and manual MSC structures across all of the dose levels, averaged over the test cohort, was 8%. This difference reached approximately 28% when comparing automated MSC and OCC structures. CONCLUSIONS: Fully-automated ABS of MSC is suitable for use in radiotherapy dose-response modelling.

Quality assurance in MRI breast screening: comparing signal-to-noise ratio in dynamic contrast-enhanced imaging protocols.

MRI has been extensively used in breast cancer staging, management and high risk screening. Detection sensitivity is paramount in breast screening, but variations of signal-to-noise ratio (SNR) as a function of position are often overlooked. We propose and demonstrate practical methods to assess spatial SNR variations in dynamic contrast-enhanced (DCE) breast examinations and apply those methods to different protocols and systems. Four different protocols in three different MRI systems (1.5 and 3.0 T) with receiver coils of different design were employed on oil-filled test objects with and without uniformity filters. Twenty 3D datasets were acquired with each protocol; each dataset was acquired in under 60 s, thus complying with current breast DCE guidelines. In addition to the standard SNR calculated on a pixel-by-pixel basis, we propose other regional indices considering the mean and standard deviation of the signal over a small sub-region centred on each pixel. These regional indices include effects of the spatial variation of coil sensitivity and other structured artefacts. The proposed regional SNR indices demonstrate spatial variations in SNR as well as the presence of artefacts and sensitivity variations, which are otherwise difficult to quantify and might be overlooked in a clinical setting. Spatial variations in SNR depend on protocol choice and hardware characteristics. The use of uniformity filters was shown to lead to a rise of SNR values, altering the noise distribution. Correlation between noise in adjacent pixels was associated with data truncation along the phase encoding direction. Methods to characterise spatial SNR variations using regional information were demonstrated, with implications for quality assurance in breast screening and multi-centre trials.

Prospective, longitudinal, multi-modal functional imaging for radical chemo-IMRT treatment of locally advanced head and neck cancer: the INSIGHT study.

BACKGROUND: Radical chemo-radiotherapy (CRT) is an effective organ-sparing treatment option for patients with locally advanced head and neck cancer (LAHNC). Despite advances in treatment for LAHNC, a significant minority of these patients continue to fail to achieve complete response with standard CRT. By constructing a multi-modality functional imaging (FI) predictive biomarker for CRT outcome for patients with LAHNC we hope to be able to reliably identify those patients at high risk of failing standard CRT. Such a biomarker would in future enable CRT to be tailored to the specific biological characteristics of each patients' tumour, potentially leading to improved treatment outcomes. METHODS/DESIGN: The INSIGHT study is a single-centre, prospective, longitudinal multi-modality imaging study using functional MRI and FDG-PET/CT for patients with LAHNC squamous cell carcinomas receiving radical CRT. Two cohorts of patients are being recruited: one treated with, and another treated without, induction chemotherapy. All patients receive radical intensity modulated radiotherapy with concurrent chemotherapy. Patients undergo functional imaging before, during and 3 months after completion of radiotherapy, as well as at the time of relapse, should that occur within the first two years after treatment. Serum samples are collected from patients at the same time points as the FI scans for analysis of a panel of serum markers of tumour hypoxia. DISCUSSION: The primary aim of the INSIGHT study is to acquire a prospective multi-parametric longitudinal data set comprising functional MRI, FDG PET/CT, and serum biomarker data from patients with LAHNC undergoing primary radical CRT. This data set will be used to construct a predictive imaging biomarker for outcome after CRT for LAHNC. This predictive imaging biomarker will be used in future studies of functional imaging based treatment stratification for patients with LAHNC. Additional objectives are: defining the reproducibility of FI parameters; determining robust methods for defining FI based biological target volumes for IMRT planning; creation of a searchable database of functional imaging data for data mining. The INSIGHT study will help to establish the role of FI in the clinical management of LAHNC. TRIAL REGISTRATION: NCRI H&N CSG ID 13860.

A novel method for delineation of oral mucosa for radiotherapy dose-response studies.

There is currently no standard method for delineating the oral mucosa and most attempts are oversimplified. A new method to obtain anatomically accurate contours of the oral mucosa surfaces was developed and applied to 11 patients. This is expected to represent an opportunity for improved toxicity modelling of oral mucositis.

Brain-sparing methods for IMRT of head and neck cancer.

PURPOSE: Radical radiotherapy for head and neck cancer (HNC) may deliver significant doses to brain structures. There is evidence that this may cause a decline in neurocognitive function (NCF). Radiation dose to the medial temporal lobes, and particularly to the hippocampi, seems to be critical in determining NCF outcomes. We evaluated the feasibility of two alternative intensity-modulated radiotherapy (IMRT) techniques to generate hippocampus- and brain-sparing HNC treatment plans to preserve NCF. METHODS AND MATERIALS: A planning study was undertaken for ten patients with HNC whose planning target volume (PTV) included the nasopharynx. Patients had been previously treated using standard (chemo)-IMRT techniques. Bilateral hippocampi were delineated according to the RTOG atlas, on T1w MRI co-registered to the RT planning CT. Hippocampus-sparing plans (HSRT), and whole-brain/hippocampus-sparing fixed-field non-coplanar IMRT (BSRT) plans, were generated. DVHs and dose difference maps were used to compare plans. NTCP calculations for NCF impairment, based on hippocampal dosimetry, were performed for all plans. RESULTS: Significant reductions in hippocampal doses relative to standard plans were achieved in eight of ten cases for both HSRT and BSRT. EQD2 D40% to bilateral hippocampi was significantly reduced from a mean of 23.5 Gy (range 14.5-35.0) in the standard plans to a mean of 8.6 Gy (4.2-24.7) for HSRT (p = 0.001) and a mean of 9.0 Gy (4.3-17.3) for BSRT (p < 0.001). Both HSRT and BSRT resulted in a significant reduction in doses to the whole brain, brain stem, and cerebellum. CONCLUSION: We demonstrate that IMRT plans for HNC involving the nasopharynx can be successfully optimised to significantly reduce dose to the bilateral hippocampi and whole brain. The magnitude of the achievable dose reductions results in significant reductions in the probability of radiation-induced NCF decline. These results could readily be translated into a future clinical trial.