Common genetic variation associated with increased susceptibility to prostate cancer does not increase risk of radiotherapy toxicity.

BACKGROUND: Numerous germline single-nucleotide polymorphisms increase susceptibility to prostate cancer, some lying near genes involved in cellular radiation response. This study investigated whether prostate cancer patients with a high genetic risk have increased toxicity following radiotherapy. METHODS: The study included 1560 prostate cancer patients from four radiotherapy cohorts: RAPPER (n=533), RADIOGEN (n=597), GenePARE (n=290) and CCI (n=150). Data from genome-wide association studies were imputed with the 1000 Genomes reference panel. Individuals were genetically similar with a European ancestry based on principal component analysis. Genetic risks were quantified using polygenic risk scores. Regression models tested associations between risk scores and 2-year toxicity (overall, urinary frequency, decreased stream, rectal bleeding). Results were combined across studies using standard inverse-variance fixed effects meta-analysis methods. RESULTS: A total of 75 variants were genotyped/imputed successfully. Neither non-weighted nor weighted polygenic risk scores were associated with late radiation toxicity in individual studies (P>0.11) or after meta-analysis (P>0.24). No individual variant was associated with 2-year toxicity. CONCLUSION: Patients with a high polygenic susceptibility for prostate cancer have no increased risk for developing late radiotherapy toxicity. These findings suggest that patients with a genetic predisposition for prostate cancer, inferred by common variants, can be safely treated using current standard radiotherapy regimens.

Radiogenomics: the search for genetic predictors of radiotherapy response.

'Radiogenomics' is the study of genetic variation associated with response to radiotherapy. Radiogenomics aims to uncover the genes and biologic pathways responsible for radiotherapy toxicity that could be targeted with radioprotective agents and; identify genetic markers that can be used in risk prediction models in the clinic. The long-term goal of the field is to develop single nucleotide polymorphism-based risk models that can be used to stratify patients to more precisely tailored radiotherapy protocols. The field has evolved over the last two decades in parallel with advances in genomics, moving from narrowly focused candidate gene studies to large, collaborative genome-wide association studies. Several confirmed genetic variants have been identified and the field is making progress toward clinical translation.

A 2-stage genome-wide association study to identify single nucleotide polymorphisms associated with development of urinary symptoms after radiotherapy for prostate cancer.

PURPOSE: We identified single nucleotide polymorphisms associated with change in the AUA Symptom Score after radiotherapy for prostate cancer. MATERIALS AND METHODS: A total of 723 patients treated with brachytherapy with or without external beam radiation therapy were assessed at baseline and annually after radiotherapy using the AUA Symptom Score. A 2-stage genome-wide association study was performed with the primary end point of change in AUA Symptom Score from baseline at each of 4 followup periods. Single nucleotide polymorphism associations were assessed using multivariable linear regression adjusting for pre-radiotherapy AUA Symptom Score severity category and clinical variables. Fisher's trend method was used to calculate combined p values from the discovery and replication cohorts. RESULTS: A region on chromosome 9p21.2 containing 8 single nucleotide polymorphisms showed the strongest association with change in AUA Symptom Score (combined p values 8.8×10(-6) to 6.5×10(-7) at 2 to 3 years after radiotherapy). These single nucleotide polymorphisms form a haplotype block that encompasses the inflammation signaling gene IFNK. These single nucleotide polymorphisms were independently associated with change in AUA Symptom Score after adjusting for clinical predictors including smoking history, hypertension, α-blocker use and pre-radiotherapy AUA Symptom Score. An additional 24 single nucleotide polymorphisms showed moderate significance for association with change in AUA Symptom Score. Several of these single nucleotide polymorphisms were more strongly associated with change in specific AUA Symptom Score items, including rs13035033 in the MYO3B gene, which was associated with straining (beta coefficient 0.9, 95% CI 0.6-1.2, p = 5.0×10(-9)). CONCLUSIONS: If validated, these single nucleotide polymorphisms could provide insight into the biology underlying urinary symptoms following radiotherapy and could lead to development of an assay to identify patients at risk for experiencing these effects.

Predicting the germline dependence of hematuria risk in prostate cancer radiotherapy patients.

BACKGROUND AND PURPOSE: Late radiation-induced hematuria can develop in prostate cancer patients undergoing radiotherapy and can negatively impact the quality-of-life of survivors. If a genetic component of risk could be modeled, this could potentially be the basis for modifying treatment for high-risk patients. We therefore investigated whether a previously developed machine learning-based modeling method using genome-wide common single nucleotide polymorphisms (SNPs) can stratify patients in terms of the risk of radiation-induced hematuria. MATERIALS AND METHODS: We applied a two-step machine learning algorithm that we previously developed for genome-wide association studies called pre-conditioned random forest regression (PRFR). PRFR includes a pre-conditioning step, producing adjusted outcomes, followed by random forest regression modeling. Data was from germline genome-wide SNPs for 668 prostate cancer patients treated with radiotherapy. The cohort was stratified only once, at the outset of the modeling process, into two groups: a training set (2/3 of samples) for modeling and a validation set (1/3 of samples). Post-modeling bioinformatics analysis was conducted to identify biological correlates plausibly associated with the risk of hematuria. RESULTS: The PRFR method achieved significantly better predictive performance compared to other alternative methods (all p < 0.05). The odds ratio between the high and low risk groups, each of which consisted of 1/3 of samples in the validation set, was 2.87 (p = 0.029), implying a clinically useful level of discrimination. Bioinformatics analysis identified six key proteins encoded by CTNND2, GSK3B, KCNQ2, NEDD4L, PRKAA1, and TXNL1 genes as well as four statistically significant biological process networks previously shown to be associated with the bladder and urinary tract. CONCLUSION: The risk of hematuria is significantly dependent on common genetic variants. The PRFR algorithm resulted in a stratification of prostate cancer patients at differential risk levels of post-radiotherapy hematuria. Bioinformatics analysis identified important biological processes involved in radiation-induced hematuria.

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.

Comparing symptom reporting by prostate cancer patients and healthcare professionals in the international multicentre REQUITE study.

INTRODUCTION: Previous studies showed that healthcare professionals and patients had only moderate to low agreement on their assessment of treatment-related symptoms. We aimed to determine the levels of agreement in a large cohort of prostate cancer patients. METHODS: Analyses were made of data from 1,756 prostate cancer patients treated with external beam radiotherapy (RT) and/or brachytherapy in Europe and the USA and recruited into the prospective multicentre observational REQUITE study. Eleven pelvic symptoms at the end of RT were compared after translating patient-reported outcomes (PROs) into CTCAE-based healthcare professional ratings. Gwet's AC2 agreement coefficient and 95% confidence intervals were calculated for each symptom. To compare severity of grading between patients and healthcare professionals, percent agreement and deviations for each symptom were graphically depicted. Stratified and sensitivity analyses were conducted to identify potential influencing factors and to assess heterogeneity and robustness of results. RESULTS: The agreement for the 11 pelvic symptoms varied from very good (AC2 > 0.8: haematuria, rectal bleeding, management of sphincter control) to poor agreement (AC2 ≤ 0.2: proctitis and urinary urgency). Fatigue had a negative impact on the agreement. Patients tended to grade symptoms more severely than healthcare professionals. Information on sexual dysfunction was missing more frequently in healthcare professional assessment than PROs. CONCLUSION: Agreement was better for observable than subjective symptoms, with patients usually grading symptoms more severely than healthcare professionals. Our findings emphasize that PROs should complement symptom assessment by healthcare professionals and be taken into consideration for clinical decision-making to incorporate the patient perspective.

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.

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.

Ocular complications with the use of radium-223: a case series.

BACKGROUND: Radium-223 is used for the treatment of osseous metastases in castrate-resistant prostate cancer, and has been shown to increase time to the first skeletal-related event, reduce the rate of hospitalization, and improve quality of life. It is well tolerated, with hematologic toxicity as the main adverse event. Thus far, no ocular complication has been reported in the literature after initial administration of radium-223 with a single case reported of ocular complications after a patient's second course of radium-223. CASE PRESENTATIONS: We present three cases of ocular complications after the use of radium-223 in patients with metastatic prostatic adenocarcinoma. Ocular complications presented as blurry vision, and formal diagnosis included uveitis and hyphema. CONCLUSIONS: Documentation of adverse events is exceedingly important due to the high incidence of metastatic prostate cancer and increasing interest for the use of radium-223 in other osteoblastic disease. The authors postulate that these ocular complications may be a result of radiation's potential effect on neovascularization, polypharmacy, or the biomolecular effects of radium-223 on integral signaling proteins, potentially coupled with poor underlying ocular health.

Factors associated with late local failure and its influence on survival in men undergoing prostate brachytherapy.

BACKGROUND AND PURPOSE: To determine the factors associated with a positive post-treatment prostate biopsy (PB) and the effects of local failure on biochemical control and cause-specific survival (CSS) in men receiving prostate brachytherapy. METHODS AND MATERIALS: Of 545 men with post-implant PB, 484 were routine (median 24 months) while 61 (median 55 months) were for cause. 114 had a repeat PB for rising PSA. Initial mean PSA was 10.5 ng/ml (±13.9) while 244 (44.8%), 202 (37.1%) and 99 (18.2%) had low, intermediate or high-risk disease. Treatments were implant only in 287 (52.7%), and implant with androgen deprivation therapy (ADT) ± external beam in 258. Radiation doses were converted to the biologically equivalent dose (BED). Final biopsy results were the last biopsy performed on that patient. Associations for the first and final biopsies with PSA, clinical stage (CS), Gleason grade group, time on hormone therapy (ADT) and BED were determined by ANOVA, chi-square and binary linear regression. Freedom from Phoenix failure (FFPF) and cause-specific survival were estimated by Kaplan Meier method and Cox proportions hazards. RESULTS: After a median of 11.4 years the first and final biopsy were positive in 10.8% and 8.8%, respectively. Significant linear regression associations with first positive PB were ADT (p = 0.005), CS (p = 0.044) and BED (p = 0.030) while only BED (p < 0.001) was significant for the final PB. Positive biopsy occurred in 21/112 (18.8%), 16/230 (7.0%) and 3/182 (1.6%) for BED ≤150, >150-200 and >200 Gy (p < 0.001), and in 29/261 (11.1%) for BED (median) ≤185 Gy vs. 5/263 (1.9%) for > 185 Gy (OR 4.2, p < 0.001). 15-year FFPF was 75.6 vs. 17.5% and cause-specific survival was 94.2 vs. 75.5% for negative vs. positive biopsy. CONCLUSIONS: Higher radiation doses are associated with 1.9% late local failure following prostate brachytherapy. A negative post-implant PB is associated with superior FFPF and decreased prostate cancer mortality.

No Association Between Polygenic Risk Scores for Cancer and Development of Radiation Therapy Toxicity.

PURPOSE: Our aim was to test whether updated polygenic risk scores (PRS) for susceptibility to cancer affect risk of radiation therapy toxicity. METHODS AND MATERIALS: Analyses included 9,717 patients with breast (n=3,078), prostate (n=5,748) or lung (n=891) cancer from Radiogenomics and REQUITE Consortia cohorts. Patients underwent potentially curative radiation therapy and were assessed prospectively for toxicity. Germline genotyping involved genome-wide single nucleotide polymorphism (SNP) arrays with nontyped SNPs imputed. PRS for each cancer were generated by summing literature-identified cancer susceptibility risk alleles: 352 breast, 136 prostate, and 24 lung. Weighted PRS were generated using log odds ratio (ORs) for cancer susceptibility. Standardized total average toxicity (STAT) scores at 2 and 5 years (breast, prostate) or 6 to 12 months (lung) quantified toxicity. Primary analysis tested late STAT, secondary analyses investigated acute STAT, and individual endpoints and SNPs using multivariable regression. RESULTS: Increasing PRS did not increase risk of late toxicity in patients with breast (OR, 1.000; 95% confidence interval [CI], 0.997-1.002), prostate (OR, 0.99; 95% CI, 0.98-1.00; weighted PRS OR, 0.93; 95% CI, 0.83-1.03), or lung (OR, 0.93; 95% CI, 0.87-1.00; weighted PRS OR, 0.68; 95% CI, 0.45-1.03) cancer. Similar results were seen for acute toxicity. Secondary analyses identified rs138944387 associated with breast pain (OR, 3.05; 95% CI, 1.86-5.01; P = 1.09 × 10-5) and rs17513613 with breast edema (OR, 0.94; 95% CI, 0.92-0.97; P = 1.08 × 10-5). CONCLUSIONS: Patients with increased polygenic predisposition to breast, prostate, or lung cancer can safely undergo radiation therapy with no anticipated excess toxicity risk. Some individual SNPs increase the likelihood of a specific toxicity endpoint, warranting validation in independent cohorts and functional studies to elucidate biologic mechanisms.

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.

Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score.

BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

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.

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.

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.

Influence of pretreatment and treatment factors on intermediate to long-term outcome after prostate brachytherapy.

PURPOSE: We describe how treatment factors influence biochemical freedom from failure, local control, freedom from metastasis and cause specific survival in patients treated with prostate brachytherapy. MATERIALS AND METHODS: We followed 2,111 men who underwent brachytherapy a median of 6 years (range 2 to 17). Median prostate specific antigen was 7 ng/ml. Of the men 1,455 (68.9%) had clinical stage T2a or less and 1,428 (67.6%) had Gleason score less than 7. A total of 1,171 patients (55.5%) received (125)I, 221 (10.4%) received (103)Pd and 719 (34.1%) received supplemental external beam irradiation combined with (103)Pd. Post-implant dosimetry was done 30 days after implantation with doses converted to the biologically effective dose. Prostate biopsy was done 2 years after permanent prostate brachytherapy in 586 men (27.8%). Survival functions were determined by the Kaplan-Meier method and Cox regression with proportions tested by the log rank test. RESULTS: The 12-year biochemical freedom from failure rate was 78.6%, and stage, Gleason score, prostate specific antigen and biologically effective dose were significant predictors (p = 0.007, <0.001, 0.005 and <0.001, respectively). In 964 patients at low risk the biochemical freedom from failure rate was 88.1% and significant predictors were hormonal therapy (p = 0.030), prostate specific antigen (p = 0.026) and biologically effective dose (p = 0.003). In 499 patients at intermediate risk the biochemical freedom from failure rate was 79.2% with biologically effective dose a significant predictor (p <0.001). In 648 men at high risk the biochemical freedom from failure rate was 67% and significant predictors were hormonal therapy, Gleason score and biologically effective dose (p = 0.036, <0.001 and 0.012, respectively). The local failure rate was 7.3% with biologically effective dose a significant predictor (p <0.001). Prostate biopsy was positive in 21 of 121 cases (21.5%) for a biologically effective dose of 150 Gy2 or less, in 14 of 248 (5.6%) for greater than 150 to 200 Gy2 and in 3 of 193 (1.6%) for greater than 200 Gy2 (p <0.001). The 12-year freedom from metastasis rate was 95.2% with Gleason score a significant predictor (p <0.001). Cause specific survival at 12 years was 94.5% with Gleason score and biologically effective dose significant predictors (p <0.001 and 0.027, respectively). CONCLUSIONS: Permanent prostate brachytherapy yields excellent long-term oncologic outcomes. High biologically effective dose may need to be delivered to achieve successful biochemical freedom from failure, local control and cause specific survival.

ATM Variants in Breast Cancer: Implications for Breast Radiation Therapy Treatment Recommendations.

PURPOSE: Advances in germline genetic testing have led to a surge in identification of ataxia-telangiectasia mutated (ATM) variant carriers among breast cancer patients, raising numerous questions regarding use of breast radiation therapy (RT) in this population. METHODS: A literature search using PubMed identified articles assessing association(s) between the germline ATM variant status and the risk of toxicity after breast RT. An expert panel of breast radiation oncologists, genetic counselors, and basic scientists convened to review the association between ATM variants and radiation-induced toxicity or secondary malignancy risk and to determine any impact on breast RT recommendations. RESULTS: Carriers of pathogenic variants in ATM have a 2- to 4-fold increased risk for developing breast cancer. ATM variants do not consistently increase risks of toxicities after RT, except possibly among patients with the single nucleotide variant c5557G>A (rs1801516), in whom a small increased risk for the development of both acute and late radiation effects has been identified. In most breast cancer patients with ATM variants, the excess 5-year absolute risk of developing a secondary contralateral breast cancer (CBC) after radiation is extremely low. The exception is in women younger than 45 years old with deleterious rare ATM missense variants, who may be at higher risk for developing a radiation-induced CBC over time. CONCLUSIONS: Adjuvant radiation is safe for most breast cancer patients who harbor ATM variants. The possible exceptions are patients with the variant c5557G>A (rs1801516) and patients younger than 45 years old with certain rare deleterious ATM variants, who may be at higher risk for developing CBC. These latter patients should be counseled regarding this potential risk, and every effort should be made to minimize the contralateral breast dose. However, the inconsistency of published data limits precise recommendations, magnifying the need for further prospective studies and the development of a centralized database cataloging RT outcomes and genetic status.

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.