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

Training and temporally validating an NTCP model of acute toxicity after whole breast radiotherapy, including the impact of advanced delivery techniques

PURPOSE

The aim is to train and validate a multivariable Normal Tissue Complication Probability (NTCP) model predicting acute skin reactions in patients with breast cancer receiving adjuvant Radiotherapy (RT).

METHODS AND MATERIALS

We retrospectively reviewed 1570 single-institute patients with breast cancer treated with whole breast irradiation (40 Gy/15fr). The patients were divided into training (n = 878, treated with 3d-CRT, from 2009 to 2017) and validation cohorts (n = 692, treated from 2017 to 2021, including advanced RT techniques). In the validation cohort, patients were classified according to the delivery techniques into static (n = 404) and arc techniques (n = 288). Several clinical/technical information and DVHs of the "skin" (5 mm inner expansion from the body contour) were available. Skin toxicity was assessed during follow-up using the RTOG scale criteria. A multivariable logistic regression model was generated combining skin DVH and clinical parameters, using cross-validation methods that ensured high internal consistency and robustness. The performance of the model was tested in the validation cohort.

RESULTS

14.0 %/17.4 % of patients developed ≥ G2 toxicity, in the training/validation cohorts, respectively. The resulting multivariable logistic model included axillary lymph node dissection (OR = 1.58, 95 %CI = 1.01-2.48, p = 0.045), hypertension (OR = 1.54, 95 %CI = 1.04-2.27, p = 0.030) and skin V20Gy (OR = 1.008, 95 %CI = 1.004-1.013, p < 0.0001). The AUC of the model was 0.64/0.59 in training/validation, with better performance in the validation cohort if considering only V20Gy (0.62). The model showed satisfactory agreement between predicted and observed toxicity rates: in the validation group, the slope of the calibration plot was 0.96 (R2 = 0.6) with excellent goodness-of-fit (Hosmer-Lemeshow p-value = 0.99). Looking at each of the three predictors individually, only the role of V20Gy was confirmed in the validation group. Results were similar when considering patients treated with static or arc techniques.

CONCLUSION

An NTCP model for acute toxicity after moderately hypofractionated breast RT was trained. The model underwent temporal validation even for patients treated with advanced delivery techniques. Despite clinical differences and techniques, the confirmation of the dosimetry parameter in the validation cohort highlights its robustness and corroborates the hypothesis that skin DVH may assess the risk with the potential for improving plan optimisation.

Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

PURPOSE

In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

METHODS AND MATERIALS

The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

RESULTS

Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

CONCLUSIONS

Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases.

Skin dose-volume predictors of moderate-severe late side effects after whole breast radiotherapy

BACKGROUND

Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by combining dosimetric parameters of the breast dermis and clinical factors.

METHODS

The skin structure was defined as the outer CT body contour's 5 mm inner isotropic expansion. It was retrospectively segmented on a large mono-institutional cohort of early-stage breast cancer patients enrolled between 2009 and 2017 (n = 1066). Patients were treated with tangential-field RT, delivering 40 Gy in 15 fractions to the whole breast. Toxicity was reported during Follow-Up (FU) using SOMA/LENT scoring. The study endpoint was moderate-severe late side effects consisting of Fibrosis-Atrophy-Telangiectasia-Pain (FATP G ≥ 2) developed within 42 months after RT completion. A machine learning pipeline was designed with a logistic model combining clinical factors and absolute skin DVH (cc) parameters as output.

RESULTS

The FATP G2 + rate was 3.8 %, with 40/1066 patients experiencing side effects. After the preprocessing of variables, a cross-validation was applied to define the best-performing model. We selected a 4-variable model with Post-Surgery Cosmetic alterations (Odds Ratio, OR = 7.3), Aromatase Inhibitors (as a protective factor with OR = 0.45), V20 Gy (50 % of the prescribed dose, OR = 1.02), and V42 Gy (105 %, OR = 1.09). Factors were also converted into an adjusted V20Gy.

CONCLUSIONS

The association between late reactions and skin DVH when delivering 40 Gy/15 fr was quantified, suggesting an independent role of V20 and V42. Few clinical factors heavily modulate the risk.

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.

Radiogenomics in lung cancer: Where are we?

Huge technological and biomedical advances have improved the survival and quality of life of lung cancer patients treated with radiotherapy. However, during treatment planning, a probability that the patient will experience adverse effects is assumed. Radiotoxicity is a complex entity that is largely dose-dependent but also has important intrinsic factors. One of the most studied is the genetic variants that may be associated with susceptibility to the development of adverse effects of radiotherapy. This review aims to present the current status of radiogenomics in lung cancer, integrating results obtained in association studies of SNPs (single nucleotide polymorphisms) related to radiotherapy toxicities. We conclude that despite numerous publications in this field, methodologies and endpoints vary greatly, making comparisons between studies difficult. Analyzing SNPs from the candidate gene approach, together with the study in cohorts limited by the sample size, has complicated the possibility of having validated results. All this delays the incorporation of genetic biomarkers in predictive models for clinical application. Thus, from all analysed SNPs, only 12 have great potential as esophagitis genetic risk factors and deserve further exploration. This review highlights the efforts that have been made to date in the radiogenomic study of radiotoxicity in lung cancer.

Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer

BACKGROUND AND PURPOSE

We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC).

MATERIALS AND METHODS

We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS.

RESULTS

From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified "3'-5'-exoribonuclease activity" (FDR = 1.6e-10) for dysphagia, "inositol phosphate-mediated signalling" for mucositis (FDR = 2.20e-09), and "drug catabolic process" for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %).

CONCLUSION

In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies.

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.

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.

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.

A genome-wide association study of radiotherapy induced toxicity in head and neck cancer patients identifies a susceptibility locus associated with mucositis

PURPOSE

A two-stage genome-wide association study was carried out in head and neck cancer (HNC) patients aiming to identify genetic variants associated with either specific radiotherapy-induced (RT) toxicity endpoints or a general proneness to develop toxicity after RT.

MATERIALS AND METHODS

The analysis included 1780 HNC patients treated with primary RT for laryngeal or oro/hypopharyngeal cancers. In a non-hypothesis-driven explorative discovery study, associations were tested in 1183 patients treated within The Danish Head and Neck Cancer Group. Significant associations were later tested in an independent Dutch cohort of 597 HNC patients and if replicated, summary data obtained from discovery and replication studies were meta-analysed. Further validation of significantly replicated findings was pursued in an Asian cohort of 235 HNC patients with nasopharynx as the primary tumour site.

RESULTS

We found and replicated a significant association between a locus on chromosome 5 and mucositis with a pooled OR for rs1131769*C in meta-analysis = 1.95 (95% CI 1.48-2.41; ppooled = 4.34 × 10-16).

CONCLUSION

This first exploratory GWAS in European cohorts of HNC patients identified and replicated a risk locus for mucositis. A larger Meta-GWAS to identify further risk variants for RT-induced toxicity in HNC patients is warranted.

Miguel A, David A, Patrick B, Pierre B, Erik B, Renée B, Patricia CC, Jenny CC, Ananya C, Gilles D, Sylvian D, Dunning Alison M, Elliott Rebecca M, Dawn E, Corinne FF, Marzia F, Sara GE, Carsten H, Higginson Daniel S, Kerns Sarah L, Kerstie J, Meritxell M, Maarten L, Mónica R, Tiziana R, Andreas R, Rosenstein Barry S, Ruysscher Dirk D, Ahmed S, Claudia S, Petra S, Paloma SF, Elena S, Hilary S, Holly S, Veerle S, Paul S, Begoña TL, Talbot Christopher J, Riccardo V, Ana V, Liv V, Veldwijk Marlon R, Tim W, Adam W, West Catharine M, Yolande L. 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.

Myeloid Toxicity of Radionuclide Cancer Therapy

Emergent genomic analytic techniques in patients with cancer offer the potential to define the risk of myelo dysplastic syndrome (MDS) and acute leukemia (AL) manifesting following targeted radionuclide therapy of metastatic lymphoma, neuroendocrine tumors (NETs), and prostate cancer. Characterization of the genetic profile will allow risk stratification of patients before theranostic radionuclide management of advanced cancers and offers the opportunity to minimize toxicity while preserving optimal individualized efficacy in the practice of personalized precision nuclear oncology. Our review of a single-center experience of prospective radionuclide theranostic management of metastatic non-Hodgkin lymphoma (NHL), NETs, and castration-resistant prostate cancer (metastatic castrate-resistant prostate cancer [mCRPC]) over the past decade, and comparison with published studies, shows that while the risk of significant myelotoxicity is generally low, at <3%, the consequences in the small minority of patients who develop MDS or AL are substantial, and survival is poor. Timely identification of patients at heightened risk of hematologic toxic complication, using novel genomic technology before institution of radionuclide therapy, will facilitate amelioration of myelotoxicity. In current clinical practice, the minimal hematological toxicity of chemo-free theranostic management of advanced cancer is significantly less compared with newly adopted chemotherapy -immunotherapy regimens, and the financial toxicity associated with these novel agents is avoided.

A two-stage genome-wide association study of radiation-induced acute toxicity in head and neck cancer

BACKGROUND

Most head and neck cancer (HNC) patients receive radiotherapy (RT) and develop toxicities. This genome-wide association study (GWAS) was designed to identify single nucleotide polymorphisms (SNPs) associated with common acute radiation-induced toxicities (RITs) in an HNC cohort.

METHODS

A two-stage GWAS was performed in 1279 HNC patients treated with RT and prospectively scored for mucositis, xerostomia, sticky saliva, and dysphagia. The area under the curve (AUC) was used to estimate the average load of toxicity during RT. At the discovery study, multivariate linear regression was used in 957 patients, and the top-ranking SNPs were tested in 322 independent replication cohort. Next, the discovery and the replication studies were meta-analyzed.

RESULTS

A region on 5q21.3 containing 16 SNPs showed genome-wide (GW) significance association at P-value < 5.0 × 10-8 with patient-rated acute xerostomia in the discovery study. The top signal was rs35542 with an adjusted effect size of 0.17*A (95% CI 0.12 to 0.23; P-value <  = 3.78 × 10-9). The genome wide significant SNPs were located within three genes (EFNA5, FBXL17, and FER). In-silico functional analysis showed these genes may be involved in DNA damage response and co-expressed in minor salivary glands. We found 428 suggestive SNPs (P-value < 1.0 × 10-5) for other toxicities, taken to the replication study. Eleven of them showed a nominal association (P-value < 0.05).

CONCLUSIONS

This GWAS suggested novel SNPs for patient-rated acute xerostomia in HNC patients. If validated, these SNPs and their related functional pathways could lead to a predictive assay to identify sensitive patients to radiation, which may eventually allow a more individualized RT treatment.

Real Life Data on Patient-Reported Outcomes and Neuro-Cognitive Functioning of Lung Cancer Patients: The PRO-Long Study

INTRODUCTION

This report investigates the impact of systemic treatments (chemotherapy or immunotherapy) with(out) loco-regional radiotherapy, on HRQoL, toxicity and neurocognitive functioning (NCF) in locally advanced and metastatic non-small cell lung cancer patients enrolled in the PRO-Long study.

MATERIALS AND METHODS

Data on patient-reported HRQoL and fourteen toxicities was collected, while NCF was tested, up to one-year post-treatment. HRQoL was assessed using the European Organisation for Research and Treatment of Cancer QLQ-C30. Lung cancer, treatment and neuro-psychological related toxicities were scored with the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events. NCF was evaluated with six neurocognitive tests. Mixed model analyses were conducted to determine statistical significance (p = .01). Meaningful clinical important differences (MCIDs) were applied for changes in HRQoL and NCF data, while toxicities were compared to baseline values.

RESULTS

In total, 50 patients were enrolled. Overall HRQoL (p = .357) nor its domains (physical, p = .643; role, p = .069; emotional, p = .254; cognitive, p = 494; social, p = .735) changed significantly over time. Meaningful improvements in overall HRQoL were seen in 22, 38 and 39% and deteriorations in 22, 5 and 28% of patients at 2-3, 6 and 12 months respectively post-treatment. Overall toxicity (p = .007), lack of appetite (p = .001), nausea (p = .004) and dysphagia (p = .000) significantly decreased over time. Treatment caused acute toxicity, such as dyspnoea (45%) and memory problems (42%), but also alleviated pre-existing symptoms, including lack of appetite (32%), anxiety (29%) and depression (28%) at 2/3 months. The NCF domains of visual memory (p = .000) and cognitive processing speed (p = .000) showed significant improvements over time. In terms of MCIDs, at 2-3 months (18%) and 6 months (15%), verbal memory was particularly impacted; at 12 months, visual memory (18%) and executive function (18%) deteriorated primarily.

CONCLUSION

The results suggest that therapy has no significant negative impact on overall HRQoL, its domains, and NCF. About one-third of patients reported a meaningful improved HRQoL at 1 year post-treatment. Treatment caused toxicity, but also alleviated pre-existing symptoms.

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.

The impact of smoking on adjuvant breast cancer radiation treatment: A systematic review

BACKGROUND

The influence of cigarette smoking on cancer risk has been well-studied. Similarly, exposure to ionizing radiation from radiotherapy (RT) can produce detrimental effects on an individual's health. In patients administered RT, there has been an observed relationship in other primary carcinomas. The purpose of this systematic review was to summarize the influence of cigarette smoking on outcomes post adjuvant RT in breast cancer patients.

METHODS

OVID Medline, Cochrane and Embase were searched and 1893 articles were identified. A total of 71 articles were included in the review. Study type, published year and sample size, age, systemic therapies, RT techniques and treatment side effects were collected if available.

RESULTS

The review found 198 different outcomes which fell into 7 categories and similar outcomes were recorded. 40% of skin reaction outcomes, 50% of cardiovascular outcomes, 71% of reconstruction outcomes, 29% of pulmonary function outcomes, 33% of mortality outcomes and 42% of secondary recurrence outcomes reported significant differences between smokers and non-smokers. None of the articles reported non-smokers to have a higher risk than smokers.

CONCLUSION

Cigarette smoking can pose a higher risk of post-treatment complications that can influence an individual's quality of life, survival rate and/or recurrence risk. This review further assessed the impact of smoking on various patient outcomes and side-effects in the adjuvant breast RT setting. The information provided in this review suggest that smoking cessation programs would help educate patients to understand their risks of being a current or former smoker when undergoing RT.

Harnessing data science to advance radiation oncology

Radiation oncology, a major treatment modality in the care of patients with malignant disease, is a technology‐ and computer‐intensive medical specialty. As such, it should lend itself ideally to data science methods, where computer science, statistics, and clinical knowledge are combined to advance state‐of‐the‐art care. Nevertheless, data science methods in radiation oncology research are still in their infancy and successful applications leading to improved patient care remain scarce. Here, we discuss data interoperability issues within and across organizational boundaries that hamper the introduction of big data and data science techniques in radiation oncology. At the semantic level, creating common underlying models and codification of the data, including the use of data elements with standardized definitions, an ontology, remains a work in progress. Methodological issues in data science and in the use of large population‐based health data registries are identified. We show that data science methods and big data cannot replace randomized clinical trials in comparative effectiveness research by reviewing a series of instances where the outcomes of big data analyses and randomized trials are at odds. We also discuss the modern wave of machine learning and artificial intelligence as represented by deep learning and convolutional neural networks. Finally, we identify promising research avenues and remain optimistic that the data sources in radiation oncology can be linked to yield important insights in the near future. We argue that data science will be a valuable complement to, but not a replacement of, the traditional hypothesis‐driven translational research chain and the randomized clinical trials that form the backbone of evidence‐based medicine.

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.

Establishing mechanisms affecting the individual response to ionizing radiation

Purpose: Humans are increasingly exposed to ionizing radiation (IR). Both low (<100 mGy) and high doses can cause stochastic effects, including cancer; whereas doses above 100 mGy are needed to promote tissue or cell damage. 10-15% of radiotherapy (RT) patients suffer adverse reactions, described as displaying radiosensitivity (RS). Sensitivity to IR's stochastic effects is termed radiosusceptibility (RSu). To optimize radiation protection we need to understand the range of individual variability and underlying mechanisms. We review the potential mechanisms contributing to RS/RSu focusing on RS following RT, the most tractable RS group.Conclusions: The IR-induced DNA damage response (DDR) has been well characterized. Patients with mutations in the DDR have been identified and display marked RS but they represent only a small percentage of the RT patients with adverse reactions. We review the impacting mechanisms and additional factors influencing RS/RSu. We discuss whether RS/RSu might be genetically determined. As a recommendation, we propose that a prospective study be established to assess RS following RT. The study should detail tumor site and encompass a well-defined grading system. Predictive assays should be independently validated. Detailed analysis of the inflammatory, stress and immune responses, mitochondrial function and life style factors should be included. Existing cohorts should also be optimally exploited.

The Implications of Genetic Testing on Radiation Therapy Decisions: A Guide for Radiation Oncologists

The advent of affordable and rapid next-generation DNA sequencing technology, along with the US Supreme Court ruling invalidating gene patents, has led to a deluge of germline and tumor genetic variant tests that are being rapidly incorporated into clinical cancer decision-making. A major concern for clinicians is whether the presence of germline mutations may increase the risk of radiation toxicity or secondary malignancies. Because scarce clinical data exist to inform decisions at this time, the American Society for Radiation Oncology convened a group of radiation science experts and clinicians to summarize potential issues, review relevant data, and provide guidance for adult patients and their care teams regarding the impact, if any, that genetic testing should have on radiation therapy recommendations. During the American Society for Radiation Oncology workshop, several main points emerged, which are discussed in this manuscript: (1) variants of uncertain significance should be considered nondeleterious until functional genomic data emerge to demonstrate otherwise; (2) possession of germline alterations in a single copy of a gene critical for radiation damage responses does not necessarily equate to increased risk of radiation-induced toxicity; (3) deleterious ataxia-telangiesctasia gene mutations may modestly increase second cancer risk after radiation therapy, and thus follow-up for these patients after indicated radiation therapy should include second cancer screening; (4) conveying to patients the difference between relative and absolute risk is critical to decision-making; and (5) more work is needed to assess the impact of tumor somatic alterations on the probability of response to radiation therapy and the potential for individualization of radiation doses. Data on radiosensitivity related to specific genetic mutations is also briefly discussed.

Clinical and epidemiological observations on individual radiation sensitivity and susceptibility

Purpose: To summarize existing knowledge and to understand individual response to radiation exposure, the MELODI Association together with CONCERT European Joint Programme has organized a workshop in March 2018 on radiation sensitivity and susceptibility.Methods: The workshop reviewed the current evidence on this matter, to inform the MELODI Strategic Research Agenda (SRA), to determine social and scientific needs and to come up with recommendations for suitable and feasible future research initiatives to be taken for the benefit of an improved medical diagnosis and treatment as well as for radiation protection.Results: The present paper gives an overview of the current evidence in this field, including potential effect modifiers such as age, gender, genetic profile, and health status of the exposed population, based on clinical and epidemiological observations.Conclusion: The authors conclude with the following recommendations for the way forward in radiation research: (a) there is need for large (prospective) cohort studies; (b) build upon existing radiation research cohorts; (c) use data from well-defined cohorts with good exposure assessment and biological material already collected; (d) focus on study quality with standardized data collection and reporting; (e) improve statistical analysis; (f) cooperation between radiobiology and epidemiology; and (g) take consequences of radiosensitivity and radiosusceptibility into account.

Reporting of Late Morbidity After Radiation Therapy in Large Prospective Studies: A Descriptive Review of the Current Status

PURPOSE

The purpose of this review was to evaluate the current status of reporting prospectively assessed late morbidity after curative radiation therapy in large clinical studies.

METHODS AND MATERIALS

A descriptive review on publications from 10 high-impact journals with a primary or partial focus on radiation therapy published between December 1, 2015, and November 30, 2017, was conducted. Publications were considered eligible if they reported prospectively assessed late morbidity after curative radiation therapy and included ≥200 patients with cancer of any type. Full text publication and supplementary material were analyzed according to items based on extensions to the Consolidated Standards of Reporting Trials (CONSORT) statement regarding reporting of harms and patient reported outcomes.

RESULTS

Overall, 802 publications were identified in PubMed; of these, 69 met the eligibility criteria. Mild and moderate morbidity were reported in 40% and 57% of publications; aggregated endpoints instead of individual endpoints were reported in 23%. In 43% of publications, crude incidence of worst grade of morbidity was used as the only statistical method for summarizing physician-assessed morbidity. Duration of morbidity or recurrent events were not reported in any of the publications.

CONCLUSIONS

Comprehensive, quantitative reporting of late morbidity after radiation therapy is challenging because of the high dimensionality and time evolution of the range of normal tissue effects. The following suggestions and recommendations are proposed: (1) report on individual severity grades, including moderate and mild; (2) use patient reported outcomes in complement to physician-assessed morbidity; (3) report on individual symptoms/endpoints on top of aggregated endpoints; (4) report on duration of morbidity or recurrent events; (5) take steps toward a consensus on severity grading scales/patient questionnaires; (6) use time to event analysis and prevalence rates; (7) report or use statistical methods accounting for pretreatment morbidity when relevant.

Precision Radiotherapy and Radiation Risk Assessment: How Do We Overcome Radiogenomic Diversity?

Precision medicine is a rapidly developing area that aims to deliver targeted therapies based on individual patient characteristics. However, current radiation treatment is not yet personalized; consequently, there is a critical need for specific patient characteristics of both tumor and normal tissues to be fully incorporated into dose prescription. Furthermore, current risk assessment following environmental, occupational, or accidental exposures to radiation is based on population effects, and does not account for individual diversity underpinning radiosensitivity. The lack of personalized approaches in both radiotherapy and radiation risk assessment resulted in the current situation where a population-based model, effective dose, is being used. In this review article, to stimulate scientific discussion for precision medicine in both radiotherapy and radiation risk assessment, we propose a novel radiological concept and metric - the personalized dose and the personalized risk index - that incorporate individual physiological, lifestyle-related and genomic variations and radiosensitivity, outlining the potential clinical application for precision medicine. We also review on recent progress in both genomics and biobanking research, which is promising for providing novel insights into individual radiosensitivity, and for creating a novel conceptual framework of precision radiotherapy and radiation risk assessment.

A new approach for modeling patient overall radiosensitivity and predicting multiple toxicity endpoints for breast cancer patients

INTRODUCTION

Evaluation of patient characteristics inducing toxicity in breast radiotherapy, using simultaneous modeling of multiple endpoints.

METHODS AND MATERIALS

In 269 early-stage breast cancer patients treated with whole-breast irradiation (WBI) after breast-conserving surgery, toxicity was scored, based on five dichotomized endpoints. Five logistic regression models were fitted, one for each endpoint and the effect sizes of all variables were estimated using maximum likelihood (MLE). The MLEs are improved with James-Stein estimates (JSEs). The method combines all the MLEs, obtained for the same variable but from different endpoints. Misclassification errors were computed using MLE- and JSE-based prediction models. For associations, p-values from the sum of squares of MLEs were compared with p-values from the Standardized Total Average Toxicity (STAT) Score.

RESULTS

With JSEs, 19 highest ranked variables were predictive of the five different endpoints. Important variables increasing radiation-induced toxicity were chemotherapy, age, SATB2 rs2881208 SNP and nodal irradiation. Treatment position (prone position) was most protective and ranked eighth. Overall, the misclassification errors were 45% and 34% for the MLE- and JSE-based models, respectively. p-Values from the sum of squares of MLEs and p-values from STAT score led to very similar conclusions, except for the variables nodal irradiation and treatment position, for which STAT p-values suggested an association with radiosensitivity, whereas p-values from the sum of squares indicated no association. Breast volume was ranked as the most significant variable in both strategies.

DISCUSSION

The James-Stein estimator was used for selecting variables that are predictive for multiple toxicity endpoints. With this estimator, 19 variables were predictive for all toxicities of which four were significantly associated with overall radiosensitivity. JSEs led to almost 25% reduction in the misclassification error rate compared to conventional MLEs. Finally, patient characteristics that are associated with radiosensitivity were identified without explicitly quantifying radiosensitivity.

Clinical and Functional Assays of Radiosensitivity and Radiation-Induced Second Cancer

Whilst the near instantaneous physical interaction of radiation energy with living cells leaves little opportunity for inter-individual variation in the initial yield of DNA damage, all the downstream processes in how damage is recognized, repaired or resolved and therefore the ultimate fate of cells can vary across the population. In the clinic, this variability is observed most readily as rare extreme sensitivity to radiotherapy with acute and late tissue toxic reactions. Though some radiosensitivity can be anticipated in individuals with known genetic predispositions manifest through recognizable phenotypes and clinical presentations, others exhibit unexpected radiosensitivity which nevertheless has an underlying genetic cause. Currently, functional assays for cellular radiosensitivity represent a strategy to identify patients with potential radiosensitivity before radiotherapy begins, without needing to discover or evaluate the impact of the precise genetic determinants. Yet, some of the genes responsible for extreme radiosensitivity would also be expected to confer susceptibility to radiation-induced cancer, which can be considered another late adverse event associated with radiotherapy. Here, the utility of functional assays of radiosensitivity for identifying individuals susceptible to radiotherapy-induced second cancer is discussed, considering both the common mechanisms and important differences between stochastic radiation carcinogenesis and the range of deterministic acute and late toxic effects of radiotherapy.

Radiogenomics: Identification of Genomic Predictors for Radiation Toxicity

The overall goal of radiogenomics is the identification of genomic markers that are predictive for the development of adverse effects resulting from cancer treatment with radiation. The principal rationale for a focus on toxicity in radiogenomics is that for many patients treated with radiation, especially individuals diagnosed with early-stage cancers, the survival rates are high, and therefore a substantial number of people will live for a significant period of time beyond treatment. However, many of these patients could suffer from debilitating complications resulting from radiotherapy. Work in radiogenomics has greatly benefited from creation of the Radiogenomics Consortium (RGC) that includes investigators at multiple institutions located in a variety of countries. The common goal of the RGC membership is to share biospecimens and data so as to achieve large-scale studies with increased statistical power to enable identification of relevant genomic markers. A major aim of research in radiogenomics is the development of a predictive instrument to enable identification of people who are at greatest risk for adverse effects resulting from cancer treatment using radiation. It is anticipated that creation of a predictive assay characterized by a high level of sensitivity and specificity will improve precision radiotherapy and assist patients and their physicians to select the optimal treatment for each individual.

Adherence to ICRU-83 reporting recommendations is inadequate in prostate dosimetry studies

PURPOSE

This study aimed to investigate if the International Commission on Radiation Units and Measurements (ICRU) 83 recommendations for reporting dosimetric endpoints are followed in published prostate studies using modulated techniques.

METHODS AND MATERIALS

Prostate dosimetry studies using inverse planning techniques were identified through a search of PubMed and EMBASE databases. These studies were analyzed to determine if the endpoints reported followed the recommendations outlined in ICRU-83. A data collection form was completed and any alternative methods of reporting were recorded. Results were analyzed using frequencies, percentages, and Fisher exact tests.

RESULTS

The ICRU-83 recommendations were not followed in the majority of studies. For the planning target volume, the dose received by 2% of the volume, the dose received by 98% of the volume, and the dose received by 50% of the volume were reported in 22.9%, 18.8%, and 8.3% of studies, respectively. The adherence to reporting for the clinical target volume was below 5% for all specifications. The mean dose, the dose received by a specified volume, and dose received by 2% of the volume for organs at risk were reported in 47.1%, 83.3%, and 16.7%, respectively. The homogeneity index was used in 14.6% of studies. Conformity was discussed in 45.8% of studies. Confidence intervals were included in 37.5% of studies.

CONCLUSIONS

The reporting recommendations of ICRU-83 were not adhered to in the majority of the dosimetry studies reviewed, highlighting the need for greater diligence for authors and reviewers when publishing planning outcomes for modulated techniques.

Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era

The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost-utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations.

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.

Radiogenomics: A systems biology approach to understanding genetic risk factors for radiotherapy toxicity?

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review 'omics' approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different 'omics' approaches may be more efficient in identifying critical pathways than pathway analysis based on single 'omics' data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterised by different mechanisms. Thus 'omics' and functional approaches may synergise if they are integrated into radiogenomics 'systems biology' to facilitate the goal of individualised radiotherapy.

Meta-analysis of Genome Wide Association Studies Identifies Genetic Markers of Late Toxicity Following Radiotherapy for Prostate Cancer

Nearly 50% of cancer patients undergo radiotherapy. Late radiotherapy toxicity affects quality-of-life in long-term cancer survivors and risk of side-effects in a minority limits doses prescribed to the majority of patients. Development of a test predicting risk of toxicity could benefit many cancer patients. We aimed to meta-analyze individual level data from four genome-wide association studies from prostate cancer radiotherapy cohorts including 1564 men to identify genetic markers of toxicity. Prospectively assessed two-year toxicity endpoints (urinary frequency, decreased urine stream, rectal bleeding, overall toxicity) and single nucleotide polymorphism (SNP) associations were tested using multivariable regression, adjusting for clinical and patient-related risk factors. A fixed-effects meta-analysis identified two SNPs: rs17599026 on 5q31.2 with urinary frequency (odds ratio [OR] 3.12, 95% confidence interval [CI] 2.08-4.69, p-value 4.16×10(-8)) and rs7720298 on 5p15.2 with decreased urine stream (OR 2.71, 95% CI 1.90-3.86, p-value=3.21×10(-8)). These SNPs lie within genes that are expressed in tissues adversely affected by pelvic radiotherapy including bladder, kidney, rectum and small intestine. The results show that heterogeneous radiotherapy cohorts can be combined to identify new moderate-penetrance genetic variants associated with radiotherapy toxicity. The work provides a basis for larger collaborative efforts to identify enough variants for a future test involving polygenic risk profiling.

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.

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.

Evidence for variation in human radiosensitivity and its potential impact on radiological protection

Radiological protection standards generally assume that all members of the population are equally sensitive to the adverse health effects associated with radiation exposure, recognising the age- and sex-related differences in sensitivity to radiation-induced cancer. It has become very clear over recent years that genetic and lifestyle factors can play important roles in the susceptibility of individuals to a range of diseases; as such, the same may apply to radiation-associated diseases. Evidence is accumulating from studies at many levels of biological organisation - cells, experimental organisms, and humans - that a range of radiosensitivity exists between individuals in the population. Consideration of improvements in radiological protection practices to take account of such differences will require the availability of robust and accurate ways to assess the sensitivity of an individual or population subgroup. In addition, there will need to be careful consideration of the ethical aspects relating to use of individual sensitivity information. These ethical considerations are very likely to be exposure context dependent, and require careful risk-benefit balance consideration before practical application.

Incorporating Genetic Biomarkers into Predictive Models of Normal Tissue Toxicity

There is considerable variation in the level of toxicity patients experience for a given dose of radiotherapy, which is associated with differences in underlying individual normal tissue radiosensitivity. A number of syndromes have a large effect on clinical radiosensitivity, but these are rare. Among non-syndromic patients, variation is less extreme, but equivalent to a ±20% variation in dose. Thus, if individual normal tissue radiosensitivity could be measured, it should be possible to optimise schedules for individual patients. Early investigations of in vitro cellular radiosensitivity supported a link with tissue response, but individual studies were equivocal. A lymphocyte apoptosis assay has potential, and is currently under prospective validation. The investigation of underlying genetic variation also has potential. Although early candidate gene studies were inconclusive, more recent genome-wide association studies are revealing definite associations between genotype and toxicity and highlighting the potential for future genetic testing. Genetic testing and individualised dose prescriptions could reduce toxicity in radiosensitive patients, and permit isotoxic dose escalation to increase local control in radioresistant individuals. The approach could improve outcomes for half the patients requiring radical radiotherapy. As a number of patient- and treatment-related factors also affect the risk of toxicity for a given dose, genetic testing data will need to be incorporated into models that combine patient, treatment and genetic data.

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.

Ataxia telangiectasia-mutated gene polymorphisms and acute normal tissue injuries in cancer patients after radiation therapy: a systematic review and meta-analysis

PURPOSE

Studies of the association between ataxia telangiectasia-mutated (ATM) gene polymorphisms and acute radiation injuries are often small in sample size, and the results are inconsistent. We conducted the first meta-analysis to provide a systematic review of published findings.

METHODS AND MATERIALS

Publications were identified by searching PubMed up to April 25, 2014. Primary meta-analysis was performed for all acute radiation injuries, and subgroup meta-analyses were based on clinical endpoint. The influence of sample size and radiation injury incidence on genetic effects was estimated in sensitivity analyses. Power calculations were also conducted.

RESULTS

The meta-analysis was conducted on the ATM polymorphism rs1801516, including 5 studies with 1588 participants. For all studies, the cut-off for differentiating cases from controls was grade 2 acute radiation injuries. The primary meta-analysis showed a significant association with overall acute radiation injuries (allelic model: odds ratio = 1.33, 95% confidence interval: 1.04-1.71). Subgroup analyses detected an association between the rs1801516 polymorphism and a significant increase in urinary and lower gastrointestinal injuries and an increase in skin injury that was not statistically significant. There was no between-study heterogeneity in any meta-analyses. In the sensitivity analyses, small studies did not show larger effects than large studies. In addition, studies with high incidence of acute radiation injuries showed larger effects than studies with low incidence. Power calculations revealed that the statistical power of the primary meta-analysis was borderline, whereas there was adequate power for the subgroup analysis of studies with high incidence of acute radiation injuries.

CONCLUSIONS

Our meta-analysis showed a consistency of the results from the overall and subgroup analyses. We also showed that the genetic effect of the rs1801516 polymorphism on acute radiation injuries was dependent on the incidence of the injury. These support the evidence of an association between the rs1801516 polymorphism and acute radiation injuries, encouraging further research of this topic.

A Review of the Use of Topical Calendula in the Prevention and Treatment of Radiotherapy-Induced Skin Reactions

Calendula is a topical agent derived from a plant of the marigold family Calendula Officinalis. Containing numerous polyphenolic antioxidants, calendula has been studied in both the laboratory and clinical setting for the use in treating and preventing radiation induced skin toxicity. Despite strong evidence in the laboratory supporting calendula's mechanism of action in preventing radiation induced skin toxicity, clinical studies have demonstrated mixed results. In light of the controversy surrounding the efficacy of calendula in treating and preventing radiodermatitis, the topic warrants further discussion.

Acute symptoms during the course of head and neck radiotherapy or chemoradiation are strong predictors of late dysphagia

PURPOSE

To determine if acute symptoms during definitive radiotherapy (RT) or chemoradiation (CHRT) are prognostic factors for late dysphagia in head and neck cancer (HNC).

MATERIAL AND METHODS

This prospective cohort study consisted of 260 HNC patients who received definitive RT or CHRT. The primary endpoint was grade 2-4 swallowing dysfunction at 6 months after completing RT (SWALM6). During treatment, acute symptoms, including oral mucositis, xerostomia and dysphagia, were scored, and the scores were accumulated weekly and entered into an existing reference model for SWALM6 that consisted of dose-volume variables only.

RESULTS

Both acute xerostomia and dysphagia were strong prognostic factors for SWALM6. When acute scores were added as variables to the reference model, model performance increased as the course of treatment progressed: the AUC rose from 0.78 at the baseline to 0.85 in week 6. New models built for weeks 3-6 were significantly better able to identify patients with and without late dysphagia.

CONCLUSION

Acute xerostomia and dysphagia during the course of RT are strong prognostic factors for late dysphagia. Including accumulated acute symptom scores on a weekly basis in prediction models for late dysphagia significantly improves the identification of high-risk and low-risk patients at an early stage during treatment and might facilitate individualized treatment adaptation.

Radiogenomics helps to achieve personalized therapy by evaluating patient responses to radiation treatment

Radiogenomics is the whole genome application of radiogenetics, which focuses on uncovering the underlying genetic causes of individual variation in sensitivity to radiation. There is a growing consensus that radiosensitivity is a complex, inherited polygenic trait, dependent on the interaction of many genes involved in multiple cell processes. An understanding of the genes involved in processes such as DNA damage response and oxidative stress response, has evolved toward examination of how genetic variants, most often, single nucleotide polymorphisms (SNPs), may influence interindividual radioresponse. Many experimental approaches, such as candidate SNP association studies, genome-wide association studies and massively parallel sequencing are being proposed to address these questions. We present a review focusing on recent advances in association studies of SNPs to radiotherapy response and discuss challenges and opportunities for further studies. We also highlight the clinical perspective of radiogenomics in the future of personalized treatment in radiation oncology.

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 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.

Evaluating the role of mitochondrial DNA variation to the genetic predisposition to radiation-induced toxicity

BACKGROUND AND PURPOSE

Mitochondrial DNA common variants have been reported to be associated with the development of radiation-induced toxicity. Using a large cohort of patients, we aimed to validate these findings by investigating the potential role of common European mitochondrial DNA SNPs (mtSNPs) to the development of radio-toxicity.

MATERIAL AND METHODS

Overall acute and late toxicity data were assessed in a cohort of 606 prostate cancer patients by means of Standardized Total Average Toxicity (STAT) score. We carried out association tests between radiation toxicity and a selection of 15 mtSNPs (and the haplogroups defined by them).

RESULTS

Statistically significant association between mtSNPs and haplogroups with toxicity could not be validated in our Spanish cohort.

CONCLUSIONS

The present study suggests that the mtDNA common variants analyzed are not associated with clinically relevant increases in risk of overall radiation-induced toxicity in prostate cancer patients.

Association of XRCC1 and XRCC3 gene haplotypes with the development of radiation-induced fibrosis in patients with nasopharyngeal carcinoma

Radiation-induced fibrosis is one of the late complications of radiotherapy (RT) for nasopharyngeal carcinoma (NPC). The aim of this study was to investigate the association between X-ray repair cross-complementing protein 1 and 3 (XRCC1 and XRCC3, respectively) gene haplotypes and radiation-induced fibrosis in NPC patients. Genomic DNA was extracted from blood samples of 120 NPC patients previously treated with RT. In total, 12 tag single-nucleotide polymorphisms (SNPs) were selected from the XRCC1 and XRCC3 genes and were genotyped using restriction fragment length polymorphism analysis or unlabeled probe melting analysis. Single-marker and haplotype analyses were performed using multivariate logistic regression analysis. The functional variant rs861539 of XRCC3 may be associated with radiation-induced fibrosis [asymptotic P-value (P_asym)<0.05]. No significant association was observed between radiation-induced fibrosis and any of the tag SNPs of XRCC1 and XRCC3 in either single-marker or haplotype analysis after 10,000 permutations [empirical P-value (P_emp)>0.05]. Our preliminary results indicated that the rs861539 variant of XRCC3 may be associated with an increased risk of radiation-induced fibrosis; however, a large-scale study is required to confirm this result.

Finding the genetic determinants of adverse reactions to radiotherapy

Individual variation in radiosensitivity is thought to be at least partly determined by genetic factors. The remaining difference between individuals is caused by comorbidities, variation in treatment, body habitus and stochastic factors. Evidence for the heritability of radiosensitivity comes from rare genetic disorders and from cell-based studies. To what extent common and rare genetic variants might explain the genetic component of radiosensitivity has not been fully elucidated. If the genetic variants accounting for this heritability were to be determined, they could be incorporated into any future predictive statistical model of adverse reactions to radiotherapy. With the evolution of DNA sequencing and bioinformatics, radiogenomics has emerged as a new research field with the aim of finding the genetic determinants of adverse reactions to radiotherapy. Similar to the investigation of other complex genetic disease traits, early studies in radiogenomics involved candidate gene association studies--many plagued by false associations caused by low sample sizes and problematic experimental design. More recently, some promising genetic associations (e.g. with tumour necrosis factor) have emerged from large multi-institutional cohorts with built-in replication. At the same time, several small- to medium-sized genome-wide association studies (GWAS) have been or are about to be published. These studies will probably lead to an increasing number of genetic polymorphisms that may predict adverse reactions to radiotherapy. The future of the field is to create large patient cohorts for multiple cancer types, to validate the genetic loci and build reliable predictive models. For example, the REQUITE project involves multiple groups in Europe and North America. For further discovery studies, larger GWAS will be necessary to include rare sequence variants through next generation sequencing. Ultimately, radiogenomics seeks to predict which cancer patients will show radiosensitivity or radioresistance, so oncologists and surgeons can alter treatment accordingly to lower adverse reactions or increase the efficacy of radiotherapy.