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.

Genome-wide association study of treatment-related toxicity two years following radiotherapy for breast cancer.

BACKGROUND AND PURPOSE: Up to a quarter of breast cancer patients treated by surgery and radiotherapy experience clinically significant toxicity. If patients at high risk of adverse effects could be identified at diagnosis, their treatment could be tailored accordingly. This study was designed to identify common single nucleotide polymorphisms (SNPs) associated with toxicity two years following whole breast radiotherapy. MATERIALS AND METHODS: A genome-wide association study (GWAS) was performed in 1,640 breast cancer patients with complete SNP, clinical, treatment and toxicity data, recruited across 18 European and US centres into the prospective REQUITE cohort study. Toxicity data (CTCAE v4.0) were collected at baseline, end of radiotherapy, and annual follow-up. A total of 7,097,340 SNPs were tested for association with the residuals of toxicity endpoints, adjusted for clinical, treatment co-variates and population substructure. RESULTS: Quantile-quantile plots showed more associations with toxicity above the p < 5 × 10-5 level than expected by chance. Eight SNPs reached genome-wide significance. Nipple retraction grade ≥ 2 was associated with the rs188287402 variant (p = 2.80 × 10-8), breast oedema grade ≥ 2 with rs12657177 (p = 1.12 × 10-10), rs75912034 (p = 1.12 × 10-10), rs145328458 (p = 1.06 × 10-9) and rs61966612 (p = 1.23 × 10-9), induration grade ≥ 2 with rs77311050 (p = 2.54 × 10-8) and rs34063419 (p = 1.21 × 10-8), and arm lymphoedema grade ≥ 1 with rs643644 (p = 3.54 × 10-8). Heritability estimates across significant endpoints ranged from 25% to 39%. Our study did not replicate previously reported SNPs associated with breast radiation toxicity at the pre-specified significance level. CONCLUSIONS: This GWAS for long-term breast radiation toxicity provides further evidence for significant association of common SNPs with distinct toxicity endpoints.

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer.

Introduction: We hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT). Methods: The study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index. The ID was calculated as the product of the mean body dose and body volume. The weekly ID accounted for differences in fractionation. The worsening (end of radiotherapy versus baseline) of European Organisation for Research and Treatment of Cancer EORTC) Quality of Life Questionnaire (QLQ)-C30 scores in physical/role/social functioning and fatigue symptom scales were evaluated, and two outcome measures were defined as worsening in ≥2 (WS2) or ≥3 (WS3) scales, respectively. The weekly ID and clinical risk factors were tested in multivariable logistic regression analysis. Results: In REQUITE, WS2 was seen in 28% and WS3 in 16% of patients. The median weekly ID was 13.1 L·Gy/week [interquartile (IQ) range 10.2-19.3]. The weekly ID, diabetes, the use of intensity-modulated radiotherapy, and the dose per fraction were significantly associated with WS2 [AUC (area under the receiver operating characteristics curve) =0.59; 95% CI 0.55-0.63] and WS3 (AUC=0.60; 95% CI 0.55-0.64). The prevalence of WS2 (15.3%) and WS3 (6.1%) was lower in DUE-01, but the median weekly ID was higher (15.8 L·Gy/week; IQ range 13.2-19.3). The model for WS2 was validated with reduced discrimination (AUC=0.52 95% CI 0.47-0.61), The AUC for WS3 was 0.58. Conclusion: Increasing the weekly ID and the dose per fraction lead to the worsening of fatigue and functional outcomes in patients with localized PCa treated with EBRT.

The correlation between pre-treatment symptoms, acute and late toxicity and patient-reported health-related quality of life in non-small cell lung cancer patients: Results of the REQUITE study.

BACKGROUND AND PURPOSE: To investigate the association between clinician-scored toxicities and patient-reported health-related quality of life (HRQoL), in early-stage (ES-) and locally-advanced (LA-) non-small cell lung cancer (NSCLC) patients receiving loco-regional radiotherapy, included in the international real-world REQUITE study. MATERIALS AND METHODS: Clinicians scored eleven radiotherapy-related toxicities (and baseline symptoms) with the Common Terminology Criteria for Adverse Events version 4. HRQoL was assessed with the European Organization for Research and Treatment of Cancer core HRQoL questionnaire (EORTC-QLQ-C30). Statistical analyses used the mixed-model method; statistical significance was set at p = 0.01. Analyses were performed for baseline and subsequent time points up to 2 years after radiotherapy and per treatment modality, radiotherapy technique and disease stage. RESULTS: Data of 435 patients were analysed. Pre-treatment, overall symptoms, dyspnea, chest wall pain, dysphagia and cough impacted overall HRQoL and specific domains. At subsequent time points, cough and dysphagia were overtaken by pericarditis in affecting HRQoL. Toxicities during concurrent chemo-radiotherapy and 3-dimensional radiotherapy had the most impact on HRQoL. Conversely, toxicities in sequential chemo-radiotherapy and SBRT had limited impact on patients' HRQoL. Stage impacts the correlations: LA-NSCLC patients are more adversely affected by toxicity than ES-NSCLC patients, mimicking the results of radiotherapy technique and treatment modality. CONCLUSION: Pre-treatment symptoms and acute/late toxicities variously impact HRQoL of ES- and LA-NSCLC patients undergoing different treatment approaches and radiotherapy techniques. Throughout the disease, dyspnea seems crucial in this association, highlighting the additional effect of co-existing comorbidities. Our data call for optimized radiotherapy limiting toxicities that may affect patients' HRQoL.

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.

Overview of health-related quality of life and toxicity of non-small cell lung cancer patients receiving curative-intent radiotherapy in a real-life setting (the REQUITE study).

OBJECTIVES: Radiotherapy-induced toxicity may negatively impact health-related quality of life (HRQoL). This report investigates the impact of curative-intent radiotherapy on HRQoL and toxicity in early stage and locally-advanced non-small cell lung cancer patients treated with radiotherapy or chemo-radiotherapy enrolled in the observational prospective REQUITE study. MATERIALS AND METHODS: HRQoL was assessed using the European Organisation for Research and Treatment of Cancer QLQ-C30 questionnaire up to 2 years post radiotherapy. Eleven toxicities were scored by clinicians using the Common Terminology Criteria for Adverse Events (CTCAE) version 4. Toxicity scores were calculated by subtracting baseline values. Mixed model analyses were applied to determine statistical significance (p ≤ 0.01). Meaningful clinical important differences (MCID) were determined for changes in HRQoL. Analysis was performed on the overall data, different radiotherapy techniques, multimodality treatments and disease stages. RESULTS: Data of 510 patients were analysed. There was no significant change in HRQoL or its domains, except for deterioration in cognitive functioning (p = 0.01). Radiotherapy technique had no significant impact on HRQoL. The addition of chemotherapy was significantly associated with HRQoL over time (p <.001). Overall toxicity did not significantly change over time. Acute toxicities of radiation-dermatitis (p =.003), dysphagia (p =.002) and esophagitis (p <.001) peaked at 3 months and decreased thereafter. Pneumonitis initially deteriorated but improved significantly after 12 months (p =.011). A proportion of patients experienced meaningful clinically important improvements and deteriorations in overall HRQoL and its domains. In some patients, pre-treatment symptoms improved gradually. CONCLUSIONS: While overall HRQoL and toxicity did not change over time, some patients improved, whereas others experienced acute radiotherapy-induced toxicities and deteriorated HRQoL, especially physical and cognitive functioning. Patient characteristics, more so than radiotherapy technique and treatment modality, impact post-radiotherapy toxicity and HRQoL outcomes. This stresses the importance of considering the potential impact of radiotherapy on individuals' HRQoL, symptoms and toxicity in treatment decision-making.

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.

Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity.

AIM: To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi). MATERIALS AND METHODS: Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 literature-identified SNPs, the 30% most strongly associated with each toxicity were tested. SNP-SNP combinations (named SNP-allele sets) seen in ≥10% of the cohort were condensed into risk (RS) and protection (PS) scores, respectively indicating increased or decreased toxicity risk. Performance of RS and PS was evaluated by logistic regression. RS and PS were then combined into a single PRSi evaluated by area under the receiver operating characteristic curve (AUC). RESULTS: Among 1,387 analysed patients, toxicity rates were 11.7% (rectal bleeding), 4.0% (urinary frequency), 5.5% (haematuria), 7.8% (nocturia) and 17.1% (decreased urinary stream). RS and PS combined 8 to 15 different SNP-allele sets, depending on the toxicity endpoint. Distributions of PRSi differed significantly in patients with/without toxicity with AUCs ranging from 0.61 to 0.78. PRSi was better than the classical summed PRS, particularly for the urinary frequency, haematuria and decreased urinary stream endpoints. CONCLUSIONS: Our method incorporates SNP-SNP interactions when calculating PRS for radiotherapy toxicity. Our approach is better than classical summation in discriminating patients with toxicity and should enable incorporating genetic information to improve normal tissue complication probability models.

A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort.

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.

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.

Radiogenomics Consortium Genome-Wide Association Study Meta-Analysis of Late Toxicity After Prostate Cancer Radiotherapy.

BACKGROUND: A total of 10%-20% of patients develop long-term toxicity following radiotherapy for prostate cancer. Identification of common genetic variants associated with susceptibility to radiotoxicity might improve risk prediction and inform functional mechanistic studies. METHODS: We conducted an individual patient data meta-analysis of six genome-wide association studies (n = 3871) in men of European ancestry who underwent radiotherapy for prostate cancer. Radiotoxicities (increased urinary frequency, decreased urinary stream, hematuria, rectal bleeding) were graded prospectively. We used grouped relative risk models to test associations with approximately 6 million genotyped or imputed variants (time to first grade 2 or higher toxicity event). Variants with two-sided Pmeta less than 5 × 10-8 were considered statistically significant. Bayesian false discovery probability provided an additional measure of confidence. Statistically significant variants were evaluated in three Japanese cohorts (n = 962). All statistical tests were two-sided. RESULTS: Meta-analysis of the European ancestry cohorts identified three genomic signals: single nucleotide polymorphism rs17055178 with rectal bleeding (Pmeta = 6.2 × 10-10), rs10969913 with decreased urinary stream (Pmeta = 2.9 × 10-10), and rs11122573 with hematuria (Pmeta = 1.8 × 10-8). Fine-scale mapping of these three regions was used to identify another independent signal (rs147121532) associated with hematuria (Pconditional = 4.7 × 10-6). Credible causal variants at these four signals lie in gene-regulatory regions, some modulating expression of nearby genes. Previously identified variants showed consistent associations (rs17599026 with increased urinary frequency, rs7720298 with decreased urinary stream, rs1801516 with overall toxicity) in new cohorts. rs10969913 and rs17599026 had similar effects in the photon-treated Japanese cohorts. CONCLUSIONS: This study increases the understanding of the architecture of common genetic variants affecting radiotoxicity, points to novel radio-pathogenic mechanisms, and develops risk models for testing in clinical studies. Further multinational radiogenomics studies in larger cohorts are worthwhile.

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.

Patients with a High Polygenic Risk of Breast Cancer do not have An Increased Risk of Radiotherapy Toxicity.

PURPOSE: It has been hypothesized that increased predisposition to breast cancer may correlate with radiosensitivity, and thus increased risk of toxicity following breast irradiation. This study investigated the relationship between common breast cancer risk variants and radiotherapy toxicity. EXPERIMENTAL DESIGN: SNP genotypes were determined in female breast cancer patients from the RAPPER (Radiogenomics: Assessment of polymorphisms for predicting the effects of radiotherapy) study using the Illumina CytoSNP12 genome-wide array. A further 15,582,449 genotypes were imputed using the 1000 Genomes Project reference panel. Patient (n = 1,160) polygenic risk scores were generated by summing risk-allele dosages, both unweighted and weighted by published effect sizes for breast cancer risk. Regression models were used to test associations of individual variants and polygenic risk scores with acute and late toxicity phenotypes (telangiectasia, breast edema, photographically assessed shrinkage, induration, pigmentation, breast pain, breast sensitivity, and overall toxicity). RESULTS: Genotypes of 90 confirmed breast cancer risk variants were accurately determined and polygenic risk scores were approximately normally distributed. Variant rs6964587 was associated with increased breast edema 5 years following radiotherapy (Beta, 0.22; 95% confidence interval, 0.09-0.34; P = 7 × 10(-4)). No other associations were found between individual variants or the unweighted (P > 0.17) or weighted (P > 0.13) polygenic risk score and radiotherapy toxicity. This study had >87% power to detect an association between the polygenic risk score (relative risk > 1.1) and toxicity. CONCLUSIONS: Cancer patients with a high polygenic predisposition to breast cancer do not have an increased risk of radiotherapy toxicity up to 5 years following radiotherapy but individual variants may increase risk.

A three-stage genome-wide association study identifies a susceptibility locus for late radiotherapy toxicity at 2q24.1.

There is increasing evidence supporting the role of genetic variants in the development of radiation-induced toxicity. However, previous candidate gene association studies failed to elucidate the common genetic variation underlying this phenotype, which could emerge years after the completion of treatment. We performed a genome-wide association study on a Spanish cohort of 741 individuals with prostate cancer treated with external beam radiotherapy (EBRT). The replication cohorts consisted of 633 cases from the UK and 368 cases from North America. One locus comprising TANC1 (lowest unadjusted P value for overall late toxicity=6.85×10(-9), odds ratio (OR)=6.61, 95% confidence interval (CI)=2.23-19.63) was replicated in the second stage (lowest unadjusted P value for overall late toxicity=2.08×10(-4), OR=6.17, 95% CI=2.25-16.95; Pcombined=4.16×10(-10)). The inclusion of the third cohort gave unadjusted Pcombined=4.64×10(-11). These results, together with the role of TANC1 in regenerating damaged muscle, suggest that the TANC1 locus influences the development of late radiation-induced damage.

A genome wide association study (GWAS) providing evidence of an association between common genetic variants and late radiotherapy toxicity.

BACKGROUND AND PURPOSE: This study was designed to identify common single nucleotide polymorphisms (SNPs) associated with toxicity 2years after radiotherapy. MATERIALS AND METHODS: A genome wide association study was performed in 1850 patients from the RAPPER study: 1217 received adjuvant breast radiotherapy and 633 had radical prostate radiotherapy. Genotype associations with both overall and individual endpoints of toxicity were tested via univariable and multivariable regression. Replication of potentially associated SNPs was carried out in three independent patient cohorts who had radiotherapy for prostate (516 RADIOGEN and 862 Gene-PARE) or breast (355 LeND) cancer. RESULTS: Quantile-quantile plots show more associations at the P<5×10(-7) level than expected by chance (164 vs. 9 for the prostate cases and 29 vs. 4 for breast cases), providing evidence that common genetic variants are associated with risk of toxicity. Strongest associations were for individual endpoints rather than an overall measure of toxicity in all patients. However, in general, significant associations were not validated at a nominal 0.05 level in the replication cohorts. CONCLUSIONS: This largest GWAS to date provides evidence of true association between common genetic variants and toxicity. Associations with toxicity appeared to be tumour site-specific. Future GWAS require higher statistical power, in particular in the validation stage, to test clinically relevant effect sizes of SNP associations with individual endpoints, but the required sample sizes are achievable.

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.

Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study.

BACKGROUND: Several studies have reported associations between radiation toxicity and single nucleotide polymorphisms (SNPs) in candidate genes. Few associations have been tested in independent validation studies. This prospective study aimed to validate reported associations between genotype and radiation toxicity in a large independent dataset. METHODS: 92 (of 98 attempted) SNPs in 46 genes were successfully genotyped in 1613 patients: 976 received adjuvant breast radiotherapy in the Cambridge breast IMRT trial (ISRCTN21474421, n=942) or in a prospective study of breast toxicity at the Christie Hospital, Manchester, UK (n=34). A further 637 received radical prostate radiotherapy in the MRC RT01 multicentre trial (ISRCTN47772397, n=224) or in the Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer (CHHiP) trial (ISRCTN97182923, n=413). Late toxicity was assessed 2 years after radiotherapy with a validated photographic technique (patients with breast cancer only), clinical assessment, and patient questionnaires. Association tests of genotype with overall radiation toxicity score and individual endpoints were undertaken in univariate and multivariable analyses. At a type I error rate adjusted for multiple testing, this study had 99% power to detect a SNP, with minor allele frequency of 0·35, associated with a per allele odds ratio of 2·2. FINDINGS: None of the previously reported associations were confirmed by this study, after adjustment for multiple comparisons. The p value distribution of the SNPs tested against overall toxicity score was not different from that expected by chance. INTERPRETATION: We did not replicate previously reported late toxicity associations, suggesting that we can essentially exclude the hypothesis that published SNPs individually exert a clinically relevant effect. Continued recruitment of patients into studies within the Radiogenomics Consortium is essential so that sufficiently powered studies can be done and methodological challenges addressed. FUNDING: Cancer Research UK, The Royal College of Radiologists, Addenbrooke's Charitable Trust, Breast Cancer Campaign, Cambridge National Institute of Health Research (NIHR) Biomedical Research Centre, Experimental Cancer Medicine Centre, East Midlands Innovation, the National Cancer Institute, Joseph Mitchell Trust, Royal Marsden NHS Foundation Trust, Institute of Cancer Research NIHR Biomedical Research Centre for Cancer.

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.

No association between SNPs regulating TGF-ß1 secretion and late radiotherapy toxicity to the breast: results from the RAPPER study.

BACKGROUND AND PURPOSE: Several small studies have reported associations between TGFB1 single nucleotide polymorphisms (SNPs), considered to increase secretion of TGF-ß1, and greater than 3-fold increases in incidence of fibrosis - an indicator of late toxicity after radiotherapy in breast cancer patients. MATERIALS AND METHODS: Two SNPs in TGFB1, C-509T (rs1800469) and L10P (rs1800470), were genotyped in 778 breast cancer patients who had received radiotherapy to the breast. Late radiotherapy toxicity was assessed two years after radiotherapy using a validated photographic technique, clinical assessment and patient questionnaires. RESULTS: On photographic assessment, 210 (27%) patients showed some degree of breast shrinkage, whilst 45 (6%) patients showed marked breast shrinkage. There was no significant association of genotype at either of the TGFB1 SNPs with any measure of late radiation toxicity. CONCLUSION: This adequately powered trial failed to confirm previously reported increases in fibrosis with TGFB1 genotype - any increase greater than 1.36 can be excluded with 95% confidence. Similar frequent failures to replicate associations with candidate genes have been resolved using genome-wide association scans: this methodology detects common, low risk alleles but requires even larger patient numbers for adequate statistical power.

Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype.

A key challenge in radiotherapy is to maximize radiation doses to cancer cells while minimizing damage to surrounding healthy tissue. As severe toxicity in a minority of patients limits the doses that can be safely given to the majority, there is interest in developing a test to measure an individual's radiosensitivity before treatment. Variation in sensitivity to radiation is an inherited genetic trait and recent progress in genotyping raises the possibility of genome-wide studies to characterize genetic profiles that predict patient response to radiotherapy.