STROGAR - STrengthening the Reporting Of Genetic Association studies in Radiogenomics

Reporting Standards for Complication Studies of Radiation Therapy for Pediatric Cancer: Lessons From PENTEC

The major aim of Pediatric Normal Tissue Effects in the Clinic (PENTEC) was to synthesize quantitative published dose/-volume/toxicity data in pediatric radiation therapy. Such systematic reviews are often challenging because of the lack of standardization and difficulty of reporting outcomes, clinical factors, and treatment details in journal articles. This has clinical consequences: optimization of treatment plans must balance between the risks of toxicity and local failure; counseling patients and their parents requires knowledge of the excess risks encountered after a specific treatment. Studies addressing outcomes after pediatric radiation therapy are particularly challenging because: (a) survivors may live for decades after treatment, and the latency time to toxicity can be very long; (b) children's maturation can be affected by radiation, depending on the developmental status of the organs involved at time of treatment; and (c) treatment regimens frequently involve chemotherapies, possibly modifying and adding to the toxicity of radiation. Here we discuss: basic reporting strategies to account for the actuarial nature of the complications; the reporting of modeling of abnormal development; and the need for standardized, comprehensively reported data sets and multivariate models (ie, accounting for the simultaneous effects of radiation dose, age, developmental status at time of treatment, and chemotherapy dose). We encourage the use of tools that facilitate comprehensive reporting, for example, electronic supplements for journal articles. Finally, we stress the need for clinicians to be able to trust artificial intelligence models of outcome of radiation therapy, which requires transparency, rigor, reproducibility, and comprehensive reporting. Adopting the reporting methods discussed here and in the individual PENTEC articles will increase the clinical and scientific usefulness of individual reports and associated pooled analyses.

Moving the Needle Forward in Genomically-Guided Precision Radiation Treatment

Radiation treatment (RT) is a mainstay treatment for many types of cancer. Recommendations for RT and the radiation plan are individualized to each patient, taking into consideration the patient's tumor pathology, staging, anatomy, and other clinical characteristics. Information on germline mutations and somatic tumor mutations is at present rarely used to guide specific clinical decisions in RT. Many genes, such as ATM, and BRCA1/2, have been identified in the laboratory to confer radiation sensitivity. However, our understanding of the clinical significance of mutations in these genes remains limited and, as individual mutations in such genes can be rare, their impact on tumor response and toxicity remains unclear. Current guidelines, including those from the National Comprehensive Cancer Network (NCCN), provide limited guidance on how genetic results should be integrated into RT recommendations. With an increasing understanding of the molecular underpinning of radiation response, genomically-guided RT can inform decisions surrounding RT dose, volume, concurrent therapies, and even omission to further improve oncologic outcomes and reduce risks of toxicities. Here, we review existing evidence from laboratory, pre-clinical, and clinical studies with regard to how genetic alterations may affect radiosensitivity. We also summarize recent data from clinical trials and explore potential future directions to utilize genetic data to support clinical decision-making in developing a pathway toward personalized RT.

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.

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.

The Normal, the Radiosensitive, and the Ataxic in the Era of Precision Radiotherapy: A Narrative Review

(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after exposure to a dose that induces no toxicity in the general population. Diagnosing iRS before radiotherapy could avoid unnecessary toxicities in patients with a grossly normal phenotype. Thus, we reviewed iRS diagnostic data and their impact on decision-making processes and the RT workflow; (2) Methods: following a description of radiation toxicities, we conducted a critical review of the current state of the knowledge on individual determinants of cellular/tissue radiation; (3) Results: tremendous advances in technology now allow minimally-invasive genomic, epigenetic and functional testing and a better understanding of iRS. Ongoing large translational studies implement various tests and enriched NTCP models designed to improve the prediction of toxicities. iRS testing could better support informed radiotherapy decisions for individuals with a normal phenotype who experience unusual toxicities. Ethics of medical decisions with an accurate prediction of personalized radiotherapy's risk/benefits and its health economics impact are at stake; (4) Conclusions: iRS testing represents a critical unmet need to design personalized radiotherapy protocols relying on extended NTCP models integrating iRS.

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.

Reporting guidelines for human microbiome research: the STORMS checklist

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

Genetic variants associated with mandibular osteoradionecrosis following radiotherapy for head and neck malignancy

BACKGROUND/AIM

Utilising radiotherapy in the management of head and neck cancer (HNC) often results in long term toxicities. Mandibular osteoradionecrosis (ORN) represents a late toxicity associated with significant morbidity. We aim to identify a panel of common genetic variants which can predict ORN to aid development of personalised radiotherapy protocols.

METHOD

Single nucleotide polymorphism (SNP) arrays were applied to DNA samples from patients who had prior HNC radiotherapy and minimum two years follow-up. A case cohort of mandibular ORN was compared to a control group of participants recruited to CRUK HOPON clinical trial. Relevant clinical parameters influencing ORN risk (e.g. smoking/alcohol) were collected. Significant associations from array data were internally validated using polymerase chain reaction (PCR) and pyrosequencing.

RESULTS

Following inclusion of 141 patients in the analysis (52 cases, 89 controls), a model predictive for ORN was developed; after controlling for alcohol consumption, smoking, and age, 4053 SNPs were identified as significant. This was reduced to a representative model of 18 SNPs achieving 92% accuracy. Following internal technical validation, a six SNP model (rs34798038, rs6011731, rs2348569, rs530752, rs7477958, rs1415848) was retained within multivariate regression analysis (ROC AUC 0.859). Of these, four SNPs (rs34798038 (A/G) (p 0.006), rs6011731 (C/T) (p 0.018), rs530752 (A/G) (p 0.046) and rs2348569 (G/G) (p 0.005)) were significantly associated with the absence of ORN.

CONCLUSION

This is the first genome wide association study in HNC using ORN as the endpoint and offers new insight into ORN pathogenesis. Subject to validation, these variants may guide patient selection for personalised radiotherapy strategies.

Breast cancer patient perspective on opportunities and challenges of a genetic test aimed to predict radio-induced side effects before treatment: Analysis of the Italian branch of the REQUITE project

AIM

To explore breast cancer patient's perspective on future genetic testing for prediction of toxicity after breast radiotherapy (RT).

MATERIALS AND METHODS

The study involved patient enrolled in the Italian branch of the REQUITE project conducted at the National Cancer Institute in Milan. Semi-structured interviews were conducted within one month from the end of radiotherapy treatment by two radiation oncologists and a radiotherapy technician previously trained by a clinical psychologist with experience in the oncology field. Semi-structured interviews are characterized by a set of pre-defined questions and developed ad hoc by researchers in Leicester within the REQUITE project. The interview questions investigated interest in undergoing the genetic test and expectations on its usefulness and disadvantages.

RESULTS

Eighteen interviews were conducted and analysed. Forty-five initial codes were combined into nine themes which were then clustered in two main macro-areas (i) Opportunities and (ii) Challenges. Overall, all patients understand the aim of the genetic test and considered its intrinsic opportunity to make the physician more confident with the treatment. Regarding side effects, most of patients felt prepared to RT but not without fear. Many women considered important to have the largest and reliable information, also about negative experiences. Prevailing emotions were anxiety and fear but not connected to genetic test's result.

CONCLUSIONS

A genetic test could be an opportunity because generate knowledge and give patients a dynamic role in the decision-making approach. Prediction of single patient radiosensitivity before RT could prompt suggestion to entail a more and more tailored radiation treatment in the era of personalized approach.

Validation of Polymorphisms Associated with the Risk of Radiation-Induced Oesophagitis in an Independent Cohort of Non-Small-Cell Lung Cancer Patients

Simple Summary

Genetic variants identified in association with radiation therapy side effects in non-small-cell lung cancer patients require an independent validation. Therefore, the aim of our study was to replicate, in an independent cohort, the analyses of previously published studies associating single-nucleotide polymorphisms with radiation-induced oesophagitis. Following the original models, 2 of the 18 variants associated with radiation-induced oesophagitis in non-small-cell lung cancer patients were confirmed. Furthermore, we meta-analysed our cohort together with those of the reference studies. Twelve variants located in genes of inflammation and DNA double-strand break repair pathways remained associated with oesophagitis. These variants could be included in models for clinical prediction of radiation-induced oesophagitis to evaluate their performance.

Abstract

Several studies have identified single-nucleotide polymorphisms (SNPs) associated with adverse effects in non-small-cell lung cancer (NSCLC) patients treated with radiation therapy. Here, using an independent cohort, we aimed to validate the reported associations. We selected 23 SNPs in 17 genes previously associated with radiation-induced oesophagitis for validation in a cohort of 178 Spanish NSCLC patients. Of them, 18 SNPs were finally analysed, following the methods described in the original published studies. Two SNPs replicated their association with radiation-induced oesophagitis (rs7165790 located in the BLM gene: odds ratio (OR) = 0.16, 95% CI = 0.04–0.65, p-value = 0.010; rs4772468 at FGF14: OR = 4.36, 95% CI = 1.15–16.46, p-value = 0.029). The SNP rs2868371 at HSPB1 was also validated but displayed an opposite effect to the formerly described (OR = 3.72; 95% CI = 1.49–9.25; p-value = 0.004). Additionally, we tested a meta-analytic approach including our results and the previous datasets reported in the referenced publications. Twelve SNPs (including the two previously validated) retained their statistically significant association with radiation-induced oesophagitis. This study strengthens the role of inflammation and DNA double-strand break repair pathways in the risk prediction of developing radiation-induced oesophagitis in NSCLC patients. The validated variants are good candidates to be evaluated in risk prediction models for patient stratification based on their radiation susceptibility.

Breast cancer radiotherapy: What physicians need to know in the era of the precision medicine

Breast cancer is the most common cancer in women worldwide and encompasses a broad spectrum of diseases in one with significant epidemiological, clinical, and biological heterogeneity, which determines a different natural history and prognostic profile. Although classical tumour staging (TNM) still provides valuable information, the current reality is that the clinicians must consider other biological and molecular factors that directly influence treatment decision-making. The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. This knowledge has brought with it a major impact regarding surgical and systemic management and has been practice-changing, but it has also created significant uncertainties regarding how best integrate the radiotherapy treatment into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualised treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. The aim of the present review is to clarify the meaning of this term and to critically evaluate its role and impact on contemporary breast cancer radiotherapy.

Insights into the theranostic value of precision medicine on advanced radiotherapy to breast cancer

Breast cancer is the most common cancer in women worldwide. "Breast cancer" encompasses a broad spectrum of diseases (i.e., subtypes) with significant epidemiological, clinical, and biological heterogeneity. Each of these subtypes has a different natural history and prognostic profile. Although tumour staging (TNM classification) still provides valuable information in the overall management of breast cancer, the current reality is that clinicians must consider other biological and molecular factors that directly influence treatment decision-making, including extent of surgery, indication for chemotherapy, hormonal therapy, and even radiotherapy (and treatment volumes). The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. While these changes have been extremely positive in terms of surgical and systemic management, they have also created significant uncertainties concerning integration of local and locoregional radiotherapy into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances. Beyond the evident technological advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualized treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. Although precision medicine has been much discussed in the last five years or so, the concept remains somewhat ambiguous, and it often appear to be used as a "catch-all" term. The present review aims to clarify the meaning of this term and, more importantly, to critically evaluate the role and impact of precision medicine on breast cancer radiotherapy. Finally, we will discuss the current and future of precision medicine in radiotherapy.

Harnessing genome-wide association studies to minimize adverse radiation-induced side effects

Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%–10% of patients will experience adverse radiation side effects. Genomic susceptibility is thought to be responsible for approximately 40% of the clinical variability observed. In the era of precision medicine, the link between genetic susceptibility and radiation-induced side effects is further strengthening. Genome-wide association studies (GWAS) have begun to identify single-nucleotide polymorphisms (SNPs) attributed to overall and tissue-specific toxicity following radiation for treatment of breast cancer, prostate cancer, and other cancers. Here, we review the use of GWAS in identifying polymorphisms that are predictive of acute and long-term radiation-induced side effects with a focus on chest, pelvic, and head-and-neck irradiation. Integration of GWAS with “omic” data, patient characteristics, and clinical correlates into predictive models could decrease radiation-induced side effects while increasing therapeutic efficacy.

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.

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.

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

PURPOSE

REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data.

METHODS

An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated.

RESULTS

The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician- (47,025 forms) and patient- (54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade ≥2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung).

CONCLUSION

The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers.

PATIENT SUMMARY

Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short- and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity.

Genome-Wide Association Study of Susceptibility Loci for Radiation-Induced Brain Injury

BACKGROUND

Radiation-induced brain injury is a nonnegligible issue in the management of cancer patients treated by partial or whole brain irradiation. In particular, temporal lobe injury (TLI), a deleterious late complication in nasopharyngeal carcinoma, greatly affects the long-term life quality of these patients. Although genome-wide association studies (GWASs) have successfully identified single nucleotide polymorphisms (SNPs) associated with radiation toxicity, genetic variants contributing to the radiation-induced brain injury have not yet been assessed.

METHODS

We recruited and performed follow-up for a prospective observational cohort, Genetic Architecture of Radiotherapy Toxicity and Prognosis, using magnetic resonance imaging for TLI diagnosis. We conducted genome-wide association analysis in 1082 patients and validated the top associations in two independent cohorts of 1119 and 741 patients, respectively. All statistical tests were two-sided.

RESULTS

We identified a promoter variant rs17111237 (A > G, minor allele frequency [MAF] = 0.14) in CEP128 associated with TLI risk (hazard ratio = 1.45, 95% confidence interval = 1.26 to 1.66, Pcombined=3.18 × 10-7) which is in moderate linkage disequilibrium (LD) with rs162171 (MAF = 0.18, R2 = 0.69), the top signal in CEP128 (hazard ratio = 1.46, 95% confidence interval = 1.29-1.66, Pcombined= 6.17 × 10-9). Combining the clinical variables with the top SNP, we divided the patients into different subgroups with varying risk with 5-year TLI-free rates ranging from 33.7% to 95.5%. CEP128, a key component of mother centriole, tightly interacts with multiple radiation-resistant genes and plays an important role in maintaining the functional cilia, which otherwise will lead to a malfunction of the neural network. We found that A > G alteration at rs17111237 impaired the promoter activity of CEP128 and knockdown of CEP128 decreased the clonogenic cell survival of U87 cells under radiation. Noteworthy, 12.7% (27/212) of the GWAS-based associated genes (P < .001) were enriched in the neurogenesis pathway.

CONCLUSIONS

This three-stage study is the first GWAS of radiation-induced brain injury that implicates the genetic susceptibility gene CEP128 involved in TLI development and provides the novel insight into the underlying mechanisms of radiation-induced brain injury.

Radiogenomics in the Era of Advanced Radiotherapy

Most radiogenomics studies investigate how genetic variation can help to explain the differences in early and late radiotherapy toxicity between individuals. The field of radiogenomics in photon beam therapy has grown rapidly in recent years, carving out a unique translational discipline, which has progressed from candidate gene studies to larger scale genome-wide association studies, meta-analyses and now prospective validation studies. Genotyping is increasingly sophisticated and affordable, and whole-genome sequencing may soon become readily available as a diagnostic tool in the clinic. The ultimate aim of radiogenomics research is to tailor treatment to the individual with a test based on a combination of treatment, clinical and genetic factors. This personalisation would allow the greatest tumour control while minimising acute and long-term toxicity. Here we discuss the evolution of the field of radiogenomics with reference to the most recent developments and challenges.

Genomics of radiation sensitivity in squamous cell carcinomas

Radiotherapy is an important modality in the management of squamous cell cancers with 50% of patients receiving radiotherapy at some point. Despite technological advances, the risk of severe toxicity in a proportion of radiosensitive patients limits radiation doses that can be safely prescribed affecting the potential for cure. While comorbidities, lifestyle and treatment factors can influence interindividual variations, genetic factors are thought to play a major role, accounting for approximately 80% of the variance observed. Over the last decade, substantial progress has been made in the field of radiogenomics, with compelling associations for SNPs identified in genes involved in DNA-damage response, cell-cycle control, apoptosis, antioxidant defenses and cytokine production. Future research efforts should be collaborative, focused on validating and broadening their clinical applicability. Numerous obstacles exist to the clinical application of this knowledge, which need to be overcome before personalized radiation therapy becomes a routine component of oncologic care.

A review of radiation genomics: integrating patient radiation response with genomics for personalised and targeted radiation therapy

Background

The success of radiation therapy for cancer patients is dependent on the ability to deliver a total tumouricidal radiation dose capable of eradicating all cancer cells within the clinical target volume, however, the radiation dose tolerance of the surrounding healthy tissues becomes the main dose-limiting factor. The normal tissue adverse effects following radiotherapy are common and significantly impact the quality of life of patients. The likelihood of developing these adverse effects following radiotherapy cannot be predicted based only on the radiation treatment parameters. However, there is evidence to suggest that some common genetic variants are associated with radiotherapy response and the risk of developing adverse effects. Radiation genomics is a field that has evolved in recent years investigating the association between patient genomic data and the response to radiation therapy. This field aims to identify genetic markers that are linked to individual radiosensitivity with the potential to predict the risk of developing adverse effects due to radiotherapy using patient genomic information. It also aims to determine the relative radioresponse of patients using their genetic information for the potential prediction of patient radiation treatment response.

Methods and materials

This paper reports on a review of recent studies in the field of radiation genomics investigating the association between genomic data and patients response to radiation therapy, including the investigation of the role of genetic variants on an individual’s predisposition to enhanced radiotherapy radiosensitivity or radioresponse.

Conclusion

The potential for early prediction of treatment response and patient outcome is critical in cancer patients to make decisions regarding continuation, escalation, discontinuation, and/or change in treatment options to maximise patient survival while minimising adverse effects and maintaining patients’ quality of life.

Association Between Inflammatory Biomarker C-Reactive Protein and Radiotherapy-Induced Early Adverse Skin Reactions in a Multiracial/Ethnic Breast Cancer Population

Purpose This study examined an inflammatory biomarker, high-sensitivity C-reactive protein (hsCRP), in radiotherapy (RT)-induced early adverse skin reactions or toxicities in breast cancer. Patients and Methods Between 2011 and 2013, 1,000 patients with breast cancer who underwent RT were evaluated prospectively for skin toxicities through the National Cancer Institute-funded Wake Forest University Community Clinical Oncology Program Research Base. Pre- and post-RT plasma hsCRP levels and Oncology Nursing Society skin toxicity criteria (0 to 6) were used to assess RT-induced skin toxicities. Multivariable logistic regression analyses were applied to ascertain the associations between hsCRP and RT-induced skin toxicities after adjusting for potential confounders. Results The study comprised 623 white, 280 African American, 64 Asian/Pacific Islander, and 33 other race patients; 24% of the patients were Hispanic, and 47% were obese. Approximately 42% and 15% of patients developed RT-induced grade 3+ and 4+ skin toxicities, respectively. The hsCRP levels differed significantly by race and body mass index but not by ethnicity. In multivariable analysis, grade 4+ skin toxicity was significantly associated with obesity (odds ratio [OR], 2.17; 95% CI, 1.41 to 3.34], post-RT hsCRP ≥ 4.11 mg/L (OR, 1.61; 95% CI, 1.07 to 2.44), and both factors combined (OR, 3.65; 95% CI, 2.18 to 6.14). Above-median post-RT hsCRP (OR, 1.93; 95% CI, 1.03 to 3.63), and change in hsCRP (OR, 2.80; 95% CI, 1.42 to 5.54) were significantly associated with grade 4+ skin toxicity in nonobese patients. Conclusion This large prospective study is the first to our knowledge of hsCRP as an inflammatory biomarker in RT-induced skin toxicities in breast cancer. We demonstrate that nonobese patients with elevated RT-related change in hsCRP levels have a significantly increased risk of grade 4+ skin toxicity. The outcomes may help to predict RT responses and guide decision making.

Precision Oncology and Genomically Guided Radiation Therapy: A Report From the American Society for Radiation Oncology/American Association of Physicists in Medicine/National Cancer Institute Precision Medicine Conference

PURPOSE

To summarize important talking points from a 2016 symposium focusing on real-world challenges to advancing precision medicine in radiation oncology, and to help radiation oncologists navigate the practical challenges of precision, radiation oncology.

METHODS AND MATERIALS

The American Society for Radiation Oncology, American Association of Physicists in Medicine, and National Cancer Institute cosponsored a meeting on precision medicine in radiation oncology. In June 2016 numerous scientists, clinicians, and physicists convened at the National Institutes of Health to discuss challenges and future directions toward personalized radiation therapy. Various breakout sessions were held to discuss particular components and approaches to the implementation of personalized radiation oncology. This article summarizes the genomically guided radiation therapy breakout session.

RESULTS

A summary of existing genomic data enabling personalized radiation therapy, ongoing clinical trials, current challenges, and future directions was collected. The group attempted to provide both a current overview of data that radiation oncologists could use to personalize therapy, along with data that are anticipated in the coming years. It seems apparent from the provided review that a considerable opportunity exists to truly bring genomically guided radiation therapy into clinical reality.

CONCLUSIONS

Genomically guided radiation therapy is a necessity that must be embraced in the coming years. Incorporating these data into treatment recommendations will provide radiation oncologists with a substantial opportunity to improve outcomes for numerous cancer patients. More research focused on this topic is needed to bring genomic signatures into routine standard of care.

TNFSF10/TRAIL regulates human T4 effector memory lymphocyte radiosensitivity and predicts radiation-induced acute and subacute dermatitis

Sensitivity of T4 effector-memory (T4EM) lymphocytes to radiation-induced apoptosis shows heritability compatible with a Mendelian mode of transmission. Using gene expression studies and flow cytometry, we show a higher TNF-Related Apoptosis Inducing Ligand (TRAIL/TNFSF10) mRNA level and a higher level of membrane bound TRAIL (mTRAIL) on radiosensitive compared to radioresistant T4EM lymphocytes. Functionally, we show that mTRAIL mediates a pro-apoptotic autocrine signaling after irradiation of T4EM lymphocytes linking mTRAIL expression to T4EM radiosensitivity. Using single marker and multimarker Family-Based Association Testing, we identified 3 SNPs in the TRAIL gene that are significantly associated with T4EM lymphocytes radiosensitivity. Among these 3 SNPs, two are also associated with acute and subacute dermatitis after radiotherapy in breast cancer indicating that T4EM lymphocytes radiosensitivity may be used to predict response to radiotherapy. Altogether, these results show that mTRAIL level regulates the response of T4EM lymphocytes to ionizing radiation and suggest that TRAIL/TNFSF10 genetic variants hold promise as markers of individual radiosensitivity.

Radiogenomics and radiotherapy response modeling

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

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.

Genetic Variants in MTHFR Gene Predict ≥ 2 Radiation Pneumonitis in Esophageal Squamous Cell Carcinoma Patients Treated with Thoracic Radiotherapy

Reactive oxygen species (ROS), formed as an indirect production of radiotherapy (RT), could cause DNA damage of normal tissues. Meanwhile, our body possesses the ability to restore the damage by DNA repair pathways. The imbalance between the two systems could finally result in radiation injury. Therefore, in this prospective cohort study, we explored the association of genetic variants in ROS metabolism and DNA repair pathway-related genes with radiation pneumonitis (RP). A total of 265 locally advanced esophageal squamous cell carcinoma (ESCC) patients receiving RT in Chinese Han population were enrolled. Five functional single nucleotide polymorphisms (SNPs) (rs1695 in GSTP1; rs4880 in SOD2; rs3957356 in GSTA1; and rs1801131, rs1801133 in MTHFR) were genotyped using the MassArray system, and rs1801131 was found to be a predictor of ≥ 2 RP. Our results showed that, compared with TT genotype, patients with GG/GT genotypes of rs1801131 had a notably lower risk of developing ≥ 2 RP (HR = 0.339, 95% CI = 0.137–0.839, P = 0.019). Further independent studies are required to confirm this findings.

Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement

The optimal design and patient selection for interventional trials in radiogenomics seem trivial at first sight. However, radiogenomics do not give binary information like in e.g. targetable mutation biomarkers. Here, the risk to develop severe side effects is continuous, with increasing incidences of side effects with higher doses and/or volumes. In addition, a multi-SNP assay will produce a predicted probability of developing side effects and will require one or more cut-off thresholds for classifying risk into discrete categories. A classical biomarker trial design is therefore not optimal, whereas a risk factor stratification approach is more appropriate. Patient selection is crucial and this should be based on the dose-response relations for a specific endpoint. Alternatives to standard treatment should be available and this should take into account the preferences of patients. This will be discussed in detail.

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.

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.

Gender bias in individual radiosensitivity and the association with genetic polymorphic variations

PURPOSE

To assess the extent of variation in radiosensitivity between individuals, gender-related dissimilarity and impact on the association with single nucleotide polymorphisms (SNPs).

MATERIALS AND METHODS

Survival curves of 152 fibroblast cell strains derived from both gender were generated. Individual radiosensitivity was characterized by the surviving fraction at 2Gy (SF2). SNPs in 10 radiation responsive genes were genotyped by direct sequencing.

RESULTS

The wide variation in SF2 (0.12-0.50; mean=0.33) was significantly associated with 3 SNPs: TP53 G72C (P=0.007), XRCC1 G399A (P=0.002) and ATM G1853A (P=0.01). Females and males differed significantly in radiosensitivity (P=0.004) that impacted genetic association where only XRCC1 remained significant in both gender (P<0.05). Meanwhile, discordant association was observed for TP53 that was significant in females (P=0.012) and ATM that was significant in males (P=0.0006). When gender-specific SF2-mean (0.31 and 0.35 for females and males; respectively) was considered, further discordance was observed where XRCC1 turned out not to be associated with radiosensitivity in males (P>0.05).

CONCLUSIONS

Although the variation in individual radiosensitivity was associated with certain SNPs, gender bias for both endpoints was evident. Therefore, assessing the risk of radiation exposure in females and males should be considered separately in order to achieve the ultimate goal of personalized radiation medicine.

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments

Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression.

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Aim to enable image-based tracking of progression in Parkinson's disease

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Texture analysis of clinical dopamine transporter (DAT) SPECT images (DaTscans)

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Significant correlations with clinical, motor and cognitive outcomes

Radiation-induced CD8 T-lymphocyte Apoptosis as a Predictor of Breast Fibrosis After Radiotherapy: Results of the Prospective Multicenter French Trial

BACKGROUND

Monocentric cohorts suggested that radiation-induced CD8 T-lymphocyte apoptosis (RILA) can predict late toxicity after curative intent radiotherapy (RT). We assessed the role of RILA as a predictor of breast fibrosis (bf +) after adjuvant breast RT in a prospective multicenter trial.

METHODS

A total of 502 breast-cancer patients (pts) treated by conservative surgery and adjuvant RT were recruited at ten centers. RILA was assessed before RT by flow cytometry. Impact of RILA on bf + (primary endpoint) or relapse was assessed using a competing risk method. Receiver-operator characteristic (ROC) curve analyses were also performed in intention to treat. This study is registered with ClinicalTrials.gov, number NCT00893035 and final analyses are presented here.

FINDINGS

Four hundred and fifty-six pts (90.8%) were included in the final analysis. One hundred and eight pts (23.7%) received whole breast and node irradiation. A boost dose of 10-16 Gy was delivered in 449 pts (98.5%). Adjuvant hormonotherapy was administered to 349 pts (76.5%). With a median follow-up of 38.6 months, grade ≥ 2 bf + was observed in 64 pts (14%). A decreased incidence of grade ≥ 2 bf + was observed for increasing values of RILA (p = 0.012). No grade 3 bf + was observed for patients with RILA ≥ 12%. The area under the ROC curve was 0.62. For cut-off values of RILA ≥ 20% and < 12%, sensitivity and specificity were 80% and 34%, 56% and 67%, respectively. Negative predictive value for grade ≥ 2 bf + was equal to 91% for RILA ≥ 20% and positive predictive value was equal to 22% for RILA < 12% where the overall prevalence of grade ≥ 2 bf + was estimated at 14%. A significant decrease in the risk of grade ≥ 2 bf + was found if patients had no adjuvant hormonotherapy (sHR = 0.31, p = 0.007) and presented a RILA ≥ 12% (sHR = 0.45, p = 0.002).

INTERPRETATION

RILA significantly predicts the risk of breast fibrosis. This study validates the use of RILA as a rapid screening test before RT delivery and will change definitely our daily clinical practice in radiation oncology.

FUNDING

The French National Cancer Institute (INCa) through the "Program Hospitalier de Recherche Clinique (PHRC)".

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.

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.

Single nucleotide polymorphisms in DNA repair genes as risk factors associated to prostate cancer progression

Background

Besides serum levels of PSA, there is a lack of prostate cancer specific biomarkers. It is need to develop new biological markers associated with the tumor behavior which would be valuable to better individualize treatment. The aim of this study was to elucidate the relationship between single nucleotide polymorphisms (SNPs) in genes involved in DNA repair and prostate cancer progression.

Methods

A total of 494 prostate cancer patients from a Spanish multicenter study were genotyped for 10 SNPs in XRCC1, ERCC2, ERCC1, LIG4, ATM and TP53 genes. The SNP genotyping was made in a Biotrove OpenArray® NT Cycler. Clinical tumor stage, diagnostic PSA serum levels, and Gleason score at diagnosis were obtained for all participants. Genotypic and allelic frequencies were determined using the web-based environment SNPator.

Results

SNPs rs11615 (ERCC1) and rs17503908 (ATM) appeared as risk factors for prostate cancer aggressiveness. Patients wild homozygous for these SNPs (AA and TT, respectively) were at higher risk for developing cT2b – cT4 (OR = 2.21 (confidence interval (CI) 95% 1.47 – 3.31), p < 0.001) and Gleason scores ≥ 7 (OR = 2.22 (CI 95% 1.38 – 3.57), p < 0.001), respectively. Moreover, those patients wild homozygous for both SNPs had the greatest risk of presenting D’Amico high-risk tumors (OR = 2.57 (CI 95% 1.28 – 5.16)).

Conclusions

Genetic variants at DNA repair genes are associated with prostate cancer progression, and would be taken into account when assessing the malignancy of prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-014-0143-0) contains supplementary material, which is available to authorized users.

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.