Cediranib combined with carboplatin and paclitaxel in patients with metastatic or recurrent cervical cancer (CIRCCa): a randomised, double-blind, placebo-controlled phase 2 trial.

BACKGROUND: Patients treated with standard chemotherapy for metastatic or relapsed cervical cancer respond poorly to conventional chemotherapy (response achieved in 20-30% of patients) with an overall survival of less than 1 year. High tumour angiogenesis and high concentrations of intratumoural VEGF are adverse prognostic features. Cediranib is a potent tyrosine kinase inhibitor of VEGFR1, 2, and 3. In this trial, we aimed to assess the effect of the addition of cediranib to carboplatin and paclitaxel chemotherapy in patients with metastatic or recurrent cervical cancer. METHODS: In this randomised, double-blind, placebo-controlled phase 2 trial, which was done in 17 UK cancer treatment centres, patients aged 18 years or older initially diagnosed with metastatic carcinoma or who subsequently developed metastatic disease or local pelvic recurrence after radical treatment that was not amenable to exenterative surgery were recruited. Eligible patients received carboplatin AUC of 5 plus paclitaxel 175 mg/m(2) by infusion every 3 weeks for a maximum of six cycles and were randomised centrally (1:1) through a minimisation approach to receive cediranib 20 mg or placebo orally once daily until disease progression. The stratification factors were disease site, disease-free survival after primary therapy or primary stage IVb disease, number of lines of previous treatment, Eastern Cooperative Oncology Group performance status, and investigational site. All patients, investigators, and trial personnel were masked to study drug allocation. The primary endpoint was progression-free survival. Efficacy analysis was by intention to treat, and the safety analysis included all patients who received at least one dose of study drug. This trial is registered with the ISCRTN registry, number ISRCTN23516549, and has been completed. FINDINGS: Between Aug 19, 2010, and July 27, 2012, 69 patients were enrolled and randomly assigned to cediranib (n=34) or placebo (n=35). After a median follow-up of 24·2 months (IQR 21·9-29·5), progression-free survival was longer in the cediranib group (median 8·1 months [80% CI 7·4-8·8]) than in the placebo group (6·7 months [6·2-7·2]), with a hazard ratio (HR) of 0·58 (80% CI 0·40-0·85; one-sided p=0·032). Grade 3 or worse adverse events that occurred in the concurrent chemotherapy and trial drug period in more than 10% of patients were diarrhoea (five [16%] of 32 patients in the cediranib group vs one [3%] of 35 patients in the placebo group), fatigue (four [13%] vs two [6%]), leucopenia (five [16%] vs three [9%]), neutropenia (10 [31%] vs four [11%]), and febrile neutropenia (five [16%] vs none). The incidence of grade 2-3 hypertension was higher in the cediranib group than in the control group (11 [34%] vs four [11%]). Serious adverse events occurred in 18 patients in the placebo group and 19 patients in the cediranib group. INTERPRETATION: Cediranib has significant efficacy when added to carboplatin and paclitaxel in the treatment of metastatic or recurrent cervical cancer. This finding was accompanied by an increase in toxic effects (mainly diarrhoea, hypertension, and febrile neutropenia). FUNDING: Cancer Research UK and AstraZeneca.

Comet assay measures of DNA damage are predictive of bladder cancer cell treatment sensitivity in vitro and outcome in vivo.

Bladder cancer patients suffer significant treatment failure, including high rates of recurrence and poor outcomes for advanced disease. If mechanisms to improve tumour cell treatment sensitivity could be identified and/or if tumour response could be predicted, it should be possible to improve local-control and survival. Previously, we have shown that radiation-induced DNA damage, measured by alkaline Comet assay (ACA), correlates bladder cancer cell radiosensitivity in vitro. In this study we first show that modified-ACA measures of cisplatin and mitomycin-C-induced damage also correlate bladder cancer cell chemosensitivity in vitro, with essentially the same rank order for chemosensitivity as for radiosensitivity. Furthermore, ACA studies of radiation-induced damage in different cell-DNA substrates (nuclei, nucleoids and intact parent cells) suggest that it is a feature retained in the prepared nucleoids that is responsible for the relative damage sensitivity of bladder cancer cells, suggestive of differences in the organisation of DNA within resistant vs. sensitive cells. Second, we show that ACA analysis of biopsies from bladder tumours reveal that reduced DNA damage sensitivity associates with poorer treatment outcomes, notably that tumours with a reduced damage response show a significant association with local recurrence of non-invasive disease and that reduced damage response was a better predictor of recurrence than the presence of high-risk histology in this cohort. In conclusion, this study demonstrates that mechanisms governing treatment-induced DNA damage are both central to and predictive of bladder cancer cell treatment sensitivity and exemplifies a link between DNA damage resistance and both treatment response and tumour aggression.

Contouring variation affects estimates of normal tissue complication probability for breast fibrosis after radiotherapy.

BACKGROUND: Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis. MATERIALS AND METHODS: 280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression. RESULTS: There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (-3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from "skin" contours showed higher agreement with observed events. CONCLUSION: Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types.

BACKGROUND: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung). METHODS: A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type. RESULTS: Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected). CONCLUSIONS: There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Use of angiotensin converting enzyme inhibitors is associated with reduced risk of late bladder toxicity following radiotherapy for prostate cancer.

BACKGROUND AND PURPOSE: Genome-wide association studies (GWAS) of late hematuria following prostate cancer radiotherapy identified single nucleotide polymorphisms (SNPs) near AGT, encoding angiotensinogen. We tested the hypothesis that patients taking angiotensin converting enzyme inhibitors (ACEi) have a reduced risk of late hematuria. We additionally tested genetically-defined hypertension. MATERIALS AND METHODS: Prostate cancer patients undergoing potentially-curative radiotherapy were enrolled onto two multi-center observational studies, URWCI (N = 256) and REQUITE (N = 1,437). Patients were assessed pre-radiotherapy and followed prospectively for development of toxicity for up to four years. The cumulative probability of hematuria was estimated by the Kaplan-Meier method. Multivariable grouped relative risk models assessed the effect of ACEi on time to hematuria adjusting for clinical factors and stratified by enrollment site. A polygenic risk score (PRS) for blood pressure was tested for association with hematuria in REQUITE and our Radiogenomics Consortium GWAS. RESULTS: Patients taking ACEi during radiotherapy had a reduced risk of hematuria (HR 0.51, 95%CI 0.28 to 0.94, p = 0.030) after adjusting for prior transurethral prostate and/or bladder resection, heart disease, pelvic node radiotherapy, and bladder volume receiving 70 Gy, which are associated with hematuria. A blood pressure PRS was associated with hypertension (odds ratio per standard deviation 1.38, 95%CI 1.31 to 1.46, n = 5,288, p < 0.001) but not hematuria (HR per standard deviation 0.96, 95%CI 0.87 to 1.06, n = 5,126, p = 0.41). CONCLUSIONS: Our study is the first to show a radioprotective effect of ACEi on bladder in an international, multi-site study of patients receiving pelvic radiotherapy. Mechanistic studies are needed to understand how targeting the angiotensin pathway protects the bladder.

Treatment time and circadian genotype interact to influence radiotherapy side-effects. A prospective European validation study using the REQUITE cohort.

BACKGROUND: Circadian rhythm impacts broad biological processes, including response to cancer treatment. Evidence conflicts on whether treatment time affects risk of radiotherapy side-effects, likely because of differing time analyses and target tissues. We previously showed interactive effects of time and genotypes of circadian genes on late toxicity after breast radiotherapy and aimed to validate those results in a multi-centre cohort. METHODS: Clinical and genotype data from 1690 REQUITE breast cancer patients were used with erythema (acute; n=340) and breast atrophy (two years post-radiotherapy; n=514) as primary endpoints. Local datetimes per fraction were converted into solar times as predictors. Genetic chronotype markers were included in logistic regressions to identify primary endpoint predictors. FINDINGS: Significant predictors for erythema included BMI, radiation dose and PER3 genotype (OR 1.27(95%CI 1.03-1.56); P < 0.03). Effect of treatment time effect on acute toxicity was inconclusive, with no interaction between time and genotype. For late toxicity (breast atrophy), predictors included BMI, radiation dose, surgery type, treatment time and SNPs in CLOCK (OR 0.62 (95%CI 0.4-0.9); P < 0.01), PER3 (OR 0.65 (95%CI 0.44-0.97); P < 0.04) and RASD1 (OR 0.56 (95%CI 0.35-0.89); P < 0.02). There was a statistically significant interaction between time and genotypes of circadian rhythm genes (CLOCK OR 1.13 (95%CI 1.03-1.23), P < 0.01; PER3 OR 1.1 (95%CI 1.01-1.2), P < 0.04; RASD1 OR 1.15 (95%CI 1.04-1.28), P < 0.008), with peak time for toxicity determined by genotype. INTERPRETATION: Late atrophy can be mitigated by selecting optimal treatment time according to circadian genotypes (e.g. treat PER3 rs2087947C/C genotypes in mornings; T/T in afternoons). We predict triple-homozygous patients (14%) reduce chance of atrophy from 70% to 33% by treating in mornings as opposed to mid-afternoon. Future clinical trials could stratify patients treated at optimal times compared to those scheduled normally. FUNDING: EU-FP7.

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Purpose: Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Methods and Materials: Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. Results: One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. Conclusions: ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan.

A data science approach for early-stage prediction of Patient's susceptibility to acute side effects of advanced radiotherapy.

The prediction by classification of side effects incidence in a given medical treatment is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of such algorithms is to use several features to predict dichotomous responses (e.g., disease positive/negative). Similar to statistical inference modelling, ML modelling is subject to the class imbalance problem and is affected by the majority class, increasing the false-negative rate. In this study, seventy-nine ML models were built and evaluated to classify approximately 2000 participants from 26 hospitals in eight different countries into two groups of radiotherapy (RT) side effects incidence based on recorded observations from the international study of RT related toxicity "REQUITE". We also examined the effect of sampling techniques and cost-sensitive learning methods on the models when dealing with class imbalance. The combinations of such techniques used had a significant impact on the classification. They resulted in an improvement in incidence status prediction by shifting classifiers' attention to the minority group. The best classification model for RT acute toxicity prediction was identified based on domain experts' success criteria. The Area Under Receiver Operator Characteristic curve of the models tested with an isolated dataset ranged from 0.50 to 0.77. The scale of improved results is promising and will guide further development of models to predict RT acute toxicities. One model was optimised and found to be beneficial to identify patients who are at risk of developing acute RT early-stage toxicities as a result of undergoing breast RT ensuring relevant treatment interventions can be appropriately targeted. The design of the approach presented in this paper resulted in producing a preclinical-valid prediction model. The study was developed by a multi-disciplinary collaboration of data scientists, medical physicists, oncologists and surgeons in the UK Radiotherapy Machine Learning Network.

External Validation of a Predictive Model for Acute Skin Radiation Toxicity in the REQUITE Breast Cohort.

Background: Acute skin toxicity is a common and usually transient side-effect of breast radiotherapy although, if sufficiently severe, it can affect breast cosmesis, aftercare costs and the patient's quality-of-life. The aim of this study was to develop predictive models for acute skin toxicity using published risk factors and externally validate the models in patients recruited into the prospective multi-center REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side-effects and improve QUalITy of lifE in cancer survivors) study. Methods: Patient and treatment-related risk factors significantly associated with acute breast radiation toxicity on multivariate analysis were identified in the literature. These predictors were used to develop risk models for acute erythema and acute desquamation (skin loss) in three Radiogenomics Consortium cohorts of patients treated by breast-conserving surgery and whole breast external beam radiotherapy (n = 2,031). The models were externally validated in the REQUITE breast cancer cohort (n = 2,057). Results: The final risk model for acute erythema included BMI, breast size, hypo-fractionation, boost, tamoxifen use and smoking status. This model was validated in REQUITE with moderate discrimination (AUC 0.65), calibration and agreement between predicted and observed toxicity (Brier score 0.17). The risk model for acute desquamation, excluding the predictor tamoxifen use, failed to validate in the REQUITE cohort. Conclusions: While most published prediction research in the field has focused on model development, this study reports successful external validation of a predictive model using clinical risk factors for acute erythema following radiotherapy after breast-conserving surgery. This model retained discriminatory power but will benefit from further re-calibration. A similar model to predict acute desquamation failed to validate in the REQUITE cohort. Future improvements and more accurate predictions are expected through the addition of genetic markers and application of other modeling and machine learning techniques.

Multi-centre technical evaluation of the radiation-induced lymphocyte apoptosis assay as a predictive test for radiotherapy toxicity.

Predicting which patients will develop adverse reactions to radiotherapy is important for personalised treatment. Prediction will require an algorithm or nomogram combining clinical and biological data. The radiation-induced lymphocyte apoptosis (RILA) assay is the leading candidate as a biological predictor of radiotherapy toxicity. In this study we tested the potential of the assay for standardisation and use in multiple testing laboratories. The assay was standardised and reproducibility determined using samples from healthy volunteers assayed concurrently in three laboratories in Leicester (UK), Mannheim (Germany) and Montpellier (France). RILA assays were performed on samples taken prior to radiotherapy from 1319 cancer patients enrolled in the REQUITE project at multiple centres. The patients were being treated for breast (n = 753), prostate (n = 506) or lung (n = 60) cancer. Inter-laboratory comparisons identified several factors affecting results: storage time, incubation periods and type of foetal calf serum. Following standardisation, there was no significant difference in results between the centres. Significant differences were seen in RILA scores between cancer types (prostate > breast > lung), by smoking status (non-smokers > smokers) and co-morbidity with rheumatoid arthritis (arthritics > non-arthritics). An analysis of acute radiotherapy toxicity showed as expected that RILA assay does not predict most end-points, but unexpectedly did predict acute breast pain. This result may elucidate the mechanism by which the RILA assay predicts late radiotherapy toxicity. The work shows clinical trials involving multiple laboratory measurement of the RILA assay are feasible and the need to account for tumour type and other variables when applying to predictive models.

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer.

PURPOSE: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. METHODS: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. RESULTS: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician- (47,025 forms) and patient- (54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade ≥2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). CONCLUSION: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. PATIENT SUMMARY: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short- and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity.

Racial differences in endometrial cancer molecular portraits in The Cancer Genome Atlas.

Endometrial cancer (EC) is now the most prevalent gynaecological malignancy in the Western world. Black or African American women (BoAA) have double the mortality of Caucasian women, and their tumours tend to be of higher grade. Despite these disparities, little is known regarding the mutational landscape of EC between races. Hence, we wished to investigate the molecular features of ECs within The Cancer Genome Atlas (TCGA) dataset by racial groupings. In total 374 Caucasian, 109 BoAA and 20 Asian patients were included in the analysis. Asian women were diagnosed at younger age, 54.2 years versus 64.5 years for Caucasian and 64.9 years for BoAA women (OR 3.432; p=0.011); BoAA women were more likely to have serous type tumors (OR 2.061; p=0.008). No difference in overall survival was evident. The most frequently mutated gene in Caucasian and Asian tumours was PTEN (63% and 85%), unlike BoAA cases where it was TP53 (49%). Mutation and somatic copy number alteration (SCNA) analysis revealed an enrichment of TP53 mutations in BoAAs; whereas POLE and RPL22 mutations were more frequent in Caucasians. Major recurrent SCNA racial differences were observed at chromosomes 3p, 8, 10, and 16, which clustered BoAA tumors into 4 distinct groups and Caucasian tumors into 5 groups. There was a significantly higher frequency of somatic mutations in DNA mismatch repair genes in Asian tumours, in particular PMS2 (p=0.0036). In conclusion, inherent racial disparities appear to be present in the molecular profile of EC, which could have potential implications on clinical management.

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients.

PURPOSE: Several small studies have indicated that the ATM rs1801516 SNP is associated with risk of normal tissue toxicity after radiotherapy. However, the findings have not been consistent. In order to test this SNP in a well-powered study, an individual patient data meta-analysis was carried out by the International Radiogenomics Consortium. MATERIALS AND METHODS: The analysis included 5456 patients from 17 different cohorts. 2759 patients were given radiotherapy for breast cancer and 2697 for prostate cancer. Eight toxicity scores (overall toxicity, acute toxicity, late toxicity, acute skin toxicity, acute rectal toxicity, telangiectasia, fibrosis and late rectal toxicity) were analyzed. Adjustments were made for treatment and patient related factors with potential impact on the risk of toxicity. RESULTS: For all endpoints except late rectal toxicity, a significantly increased risk of toxicity was found for carriers of the minor (Asn) allele with odds ratios of approximately 1.5 for acute toxicity and 1.2 for late toxicity. The results were consistent with a co-dominant pattern of inheritance. CONCLUSION: This study convincingly showed a significant association between the ATM rs1801516 Asn allele and increased risk of radiation-induced normal tissue toxicity.

XRCC1 Polymorphism Associated With Late Toxicity After Radiation Therapy in Breast Cancer Patients.

PURPOSE: To identify single-nucleotide polymorphisms (SNPs) in oxidative stress-related genes associated with risk of late toxicities in breast cancer patients receiving radiation therapy. METHODS AND MATERIALS: Using a 2-stage design, 305 SNPs in 59 candidate genes were investigated in the discovery phase in 753 breast cancer patients from 2 prospective cohorts from Germany. The 10 most promising SNPs in 4 genes were evaluated in the replication phase in up to 1883 breast cancer patients from 6 cohorts identified through the Radiogenomics Consortium. Outcomes of interest were late skin toxicity and fibrosis of the breast, as well as an overall toxicity score (Standardized Total Average Toxicity). Multivariable logistic and linear regression models were used to assess associations between SNPs and late toxicity. A meta-analysis approach was used to summarize evidence. RESULTS: The association of a genetic variant in the base excision repair gene XRCC1, rs2682585, with normal tissue late radiation toxicity was replicated in all tested studies. In the combined analysis of discovery and replication cohorts, carrying the rare allele was associated with a significantly lower risk of skin toxicities (multivariate odds ratio 0.77, 95% confidence interval 0.61-0.96, P=.02) and a decrease in Standardized Total Average Toxicity scores (-0.08, 95% confidence interval -0.15 to -0.02, P=.016). CONCLUSIONS: Using a stage design with replication, we identified a variant allele in the base excision repair gene XRCC1 that could be used in combination with additional variants for developing a test to predict late toxicities after radiation therapy in breast cancer patients.

Antimicrobial therapy to prevent or treat oral mucositis.

Oral mucositis represents a significant source of morbidity after chemotherapy and radiation therapy. Since infection may have an important role in the pathophysiology of oral mucositis, several antimicrobial agents have been investigated for their efficacy in preventing and treating this disease. We sought to establish the weight of evidence for antimicrobial treatment and identified 31 prospectively designed clinical trials of which 13 reported some benefit and 15 did not. No clear pattern was identified regarding patient type, cancer treatment, or type of antimicrobial agent used, and inconsistent assessment of oral mucositis made comparison of outcomes difficult. Newer drugs, such as the topical antimicrobial peptide iseganan HCl initially showed promise in reducing mucositis and the related oral pain but the results of a phase 3 trial were disappointing and the line of enquiry was abandoned altogether. Hence, there is a need to better understand the role of the microflora in the cause of oral mucositis if an antimicrobial agent for prevention and treatment of this disease is to be developed.

Are depressive symptoms more common among British South Asian patients compared with British White patients with cancer? A cross-sectional survey.

OBJECTIVES: This cross-sectional survey investigated whether there were ethnic differences in depressive symptoms among British South Asian (BSA) patients with cancer compared with British White (BW) patients during 9 months following presentation at a UK Cancer Centre. We examined associations between depressed mood, coping strategies and the burden of symptoms. DESIGN: Questionnaires were administered to 94 BSA and 185 BW recently diagnosed patients with cancer at baseline and at 3 and 9 months. In total, 53.8% of the BSA samples were born in the Indian subcontinent, 33% in Africa and 12.9% in the UK. Three screening tools for depression were used to counter concerns about ethnic bias and validity in linguistic translation. The Hospital Anxiety and Depression Scale (HADS-D), Patient Health Questionnaire-9 (both validated in Gujarati), Emotion Thermometers (including the Distress Thermometer (DT), Mini-MAC and the newly developed Cancer Insight and Denial questionnaire (CIDQ) were completed. SETTING: Leicestershire Cancer Centre, UK. PARTICIPANTS: 94 BSA and 185 BW recently diagnosed patients with cancer. RESULTS: BSA self-reported significantly higher rates of depressive symptoms compared with BW patients longitudinally (HADS-D ≥8: baseline: BSA 35.1% vs BW 16.8%, p=0.001; 3 months BSA 45.6% vs BW 20.8%, p=0.001; 9 months BSA 40.6% vs BW 15.3%, p=0.004). BSA patients used potentially maladaptive coping strategies more frequently than BW patients at baseline (hopelessness/helplessness p=0.005, fatalism p=0.0005, avoidance p=0.005; the CIDQ denial statement 'I do not really believe I have cancer' p=0.0005). BSA patients experienced more physical symptoms (DT checklist), which correlated with ethnic differences in depressive symptoms especially at 3 months. CONCLUSIONS: Health professionals need to be aware of a greater probability of depressive symptomatology (including somatic symptoms) and how this may present clinically in the first 9 months after diagnosis if this ethnic disparity in mental well-being is to be addressed.

Standardized Total Average Toxicity score: a scale- and grade-independent measure of late radiotherapy toxicity to facilitate pooling of data from different studies.

PURPOSE: The search for clinical and biologic biomarkers associated with late radiotherapy toxicity is hindered by the use of multiple and different endpoints from a variety of scoring systems, hampering comparisons across studies and pooling of data. We propose a novel metric, the Standardized Total Average Toxicity (STAT) score, to try to overcome these difficulties. METHODS AND MATERIALS: STAT scores were derived for 1010 patients from the Cambridge breast intensity-modulated radiotherapy trial and 493 women from the University Hospitals of Leicester. The sensitivity of the STAT score to detect differences between patient groups, stratified by factors known to influence late toxicity, was compared with that of individual endpoints. Analysis of residuals was used to quantify the effect of these covariates. RESULTS: In the Cambridge cohort, STAT scores detected differences (p < 0.00005) between patients attributable to breast volume, surgical specimen weight, dosimetry, acute toxicity, radiation boost to tumor bed, postoperative infection, and smoking (p < 0.0002), with no loss of sensitivity over individual toxicity endpoints. Diabetes (p = 0.017), poor postoperative surgical cosmesis (p = 0.0036), use of chemotherapy (p = 0.0054), and increasing age (p = 0.041) were also associated with increased STAT score. When the Cambridge and Leicester datasets were combined, STAT was associated with smoking status (p < 0.00005), diabetes (p = 0.041), chemotherapy (p = 0.0008), and radiotherapy boost (p = 0.0001). STAT was independent of the toxicity scale used and was able to deal with missing data. There were correlations between residuals of the STAT score obtained using different toxicity scales (r > 0.86, p < 0.00005 for both datasets). CONCLUSIONS: The STAT score may be used to facilitate the analysis of overall late radiation toxicity, from multiple trials or centers, in studies of possible genetic and nongenetic determinants of radiotherapy toxicity.

Variation in telangiectasia predisposing genes is associated with overall radiation toxicity.

PURPOSE: In patients receiving radiotherapy for breast cancer where the heart is within the radiation field, cutaneous telangiectasiae could be a marker of potential radiation-induced heart disease. We hypothesized that single nucleotide polymorphisms (SNPs) in genes known to cause heritable telangiectasia-associated disorders could predispose to such late, normal tissue vascular damage. METHODS AND MATERIALS: The relationship between cutaneous telangiectasia as a late normal tissue radiation injury phenotype in 633 breast cancer patients treated with radiotherapy was examined. Patients were clinically assessed for the presence of cutaneous telangiectasia and genotyped at nine SNPs in three candidate genes. Candidate SNPs were within the endoglin (ENG) and activin A receptor, type II-like 1 (ACVRL1) genes, mutations in which cause hereditary hemorrhagic telangiectasia and the ataxia-telangiectasia mutated (ATM) gene associated with ataxia-telangiectasia. RESULTS: A total of 121 (19.1%) patients exhibited a degree of cutaneous telangiectasiae on clinical examination. Regression was used to examine the associations between the presence of telangiectasiae in patients who underwent breast-conserving surgery, controlling for the effects of boost and known brassiere size (n=388), and individual geno- or haplotypes. Inheritance of ACVRL1 SNPs marginally contributed to the risk of cutaneous telangiectasiae. Haplotypic analysis revealed a stronger association between inheritance of a ATM haplotype and the presence of cutaneous telangiectasiae, fibrosis and overall toxicity. No significant association was observed between telangiectasiae and the coinheritance of the candidate ENG SNPs. CONCLUSIONS: Genetic variation in the ATM gene influences reaction to radiotherapy through both vascular damage and increased fibrosis. The predisposing variation in the ATM gene will need to be better defined to optimize it as a predictive marker for assessing radiotherapy late effects.

Individual patient data meta-analysis shows no association between the SNP rs1800469 in TGFB and late radiotherapy toxicity.

BACKGROUND AND PURPOSE: Reported associations between risk of radiation-induced normal tissue injury and single nucleotide polymorphisms (SNPs) in TGFB1, encoding the pro-fibrotic cytokine transforming growth factor-beta 1 (TGF-ß1), remain controversial. To overcome publication bias, the international Radiogenomics Consortium collected and analysed individual patient level data from both published and unpublished studies. MATERIALS AND METHODS: TGFB1 SNP rs1800469 c.-1347T>C (previously known as C-509T) genotype, treatment-related data, and clinically-assessed fibrosis (measured at least 2years after therapy) were available in 2782 participants from 11 cohorts. All received adjuvant breast radiotherapy. Associations between late fibrosis or overall toxicity, reported by STAT (Standardised Total Average Toxicity) score, and rs1800469 genotype were assessed. RESULTS: No statistically significant associations between either fibrosis or overall toxicity and rs1800469 genotype were observed with univariate or multivariate regression analysis. The multivariate odds ratio (OR), obtained from meta-analysis, for an increase in late fibrosis grade with each additional rare allele of rs1800469 was 0.98 (95% Confidence Interval (CI) 0.85-1.11). This CI is sufficiently narrow to rule out any clinically relevant effect on toxicity risk in carriers vs. non-carriers with a high probability. CONCLUSION: This meta-analysis has not confirmed previous reports of association between fibrosis or overall toxicity and rs1800469 genotype in breast cancer patients. It has demonstrated successful collaboration within the Radiogenomics Consortium.