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.

Comparison of Coding Transcriptomes in Fibroblasts Irradiated With Low and High LET Proton Beams and Cobalt-60 Photons.

PURPOSE: To identify differential cellular responses after proton and photon irradiation by comparing transcriptomes of primary fibroblasts irradiated with either radiation type. METHODS AND MATERIALS: A panel of primary dermal fibroblast cultures was irradiated with low and higher linear energy transfer (LET) proton beams. Cobalt-60 photon irradiation was used as reference. Dose was delivered in 3 fractions of 3.5 Gy (relative biological effectiveness) using a relative biological effectiveness of 1.1 for proton doses. Cells were harvested 2 hours after the final fraction was delivered, and RNA was purified. RNA sequencing was performed using Illumina NextSeq 500 with high-output kit. The edgeR package in R was used for differential gene expression analysis. RESULTS: Pairwise comparisons of the transcriptomes in the 3 treatment groups showed that there were 84 and 56 differentially expressed genes in the low LET group compared with the Cobalt-60 group and the higher LET group, respectively. The higher LET proton group and the Cobalt-60 group had the most distinct transcriptome profiles, with 725 differentially regulated genes. Differentially regulated canonical pathways and various regulatory factors involved in regulation of biological mechanisms such as inflammation, carcinogenesis, and cell cycle control were identified. CONCLUSIONS: Inflammatory regulators associated with the development of normal tissue complications and malignant transformation factors seem to be differentially regulated by higher LET proton and Cobalt-60 photon irradiation. The reported transcriptome differences could therefore influence the progression of adverse effects and the risk of developing secondary cancers.

Optimal reference genes for normalization of qPCR gene expression data from proton and photon irradiated dermal fibroblasts.

The transcriptional response of cells exposed to proton radiation is not equivalent to the response induced by traditional photon beams. Changes in cellular signalling is most commonly studied using the method Quantitative polymerase chain reaction (qPCR). Stable reference genes must be used to accurately quantify target transcript expression. The study aim was to identify suitable reference genes for normalisation of gene expression levels in normal dermal fibroblasts irradiated with either proton or photon beams. The online tool RefFinder was used to analyse and identify the most stably expressed genes from a panel of 22 gene candidates. To assess the reliability of the identified reference genes, a selection of the most and least stable reference genes was used to normalise target transcripts of interest. Fold change levels varied considerably depending on the used reference gene. The top ranked genes IPO8, PUM1, MRPL19 and PSMC4 produced highly similar target gene expression, while expression using the worst ranked genes, TFRC and HPRT1, was clearly modified due to reference gene instability.

Differential gene expression in primary fibroblasts induced by proton and cobalt-60 beam irradiation.

INTRODUCTION: Proton beam therapy delivers a more conformal dose distribution than conventional radiotherapy, thus improving normal tissue sparring. Increasing linear energy transfer (LET) along the proton track increases the relative biological effectiveness (RBE) near the distal edge of the Spread-out Bragg peak (SOBP). The severity of normal tissue side effects following photon beam radiotherapy vary considerably between patients. AIM: The dual study aim was to identify gene expression patterns specific to radiation type and proton beam position, and to assess whether individual radiation sensitivity influences gene expression levels in fibroblast cultures irradiated in vitro. METHODS: The study includes 30 primary fibroblast cell cultures from patients previously classified as either radiosensitive or radioresistant. Cells were irradiated at three different positions in the proton beam profile: entrance, mid-SOBP and at the SOBP distal edge. Dose was delivered in three fractions × 3.5 Gy(RBE) (RBE 1.1). Cobalt-60 (Co-60) irradiation was used as reference. Real-time qPCR was performed to determine gene expression levels for 17 genes associated with inflammation response, fibrosis and angiogenesis. RESULTS: Differences in median gene expression levels were observed for multiple genes such as IL6, IL8 and CXCL12. Median IL6 expression was 30%, 24% and 47% lower in entrance, mid-SOBP and SOBP distal edge groups than in Co-60 irradiated cells. No genes were found to be oppositely regulated by different radiation qualities. Radiosensitive patient samples had the strongest regulation of gene expression; irrespective of radiation type. CONCLUSIONS: Our findings indicate that the increased LET at the SOBP distal edge position did not generally lead to increased transcriptive response in primary fibroblast cultures. Inflammatory factors were generally less extensively upregulated by proton irradiation compared with Co-60 photon irradiation. These effects may possibly influence the development of normal tissue damage in patients treated with proton beam therapy.

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 - current status, challenges and future directions.

Radiogenomics designates a scientific field that addresses possible associations between genetic germline alterations and normal tissue toxicity after radiotherapy. The ultimate aim of this research is to establish a gene-based predictive test for normal tissue radiosensitivity. During the last 5 years, substantial progress has been achieved in this field. Several compelling associations for SNPs have been demonstrated in large candidate gene studies as well as genome wide association studies. These findings shed new light on radiobiology and expand our understanding of the processes that lead to side effects after radiotherapy. Despite this, certain fundamental challenges still relate to genomic approaches. Based on the latest insights into complex trait genetics and molecular genetics, we provide an analysis of these challenges and propose putative strategies to further advance the field. These strategies include 'big data approaches' and collaborative research within international consortia. Furthermore, research that combines the study of radiation-induced gene expression and genome-wide SNP genotype may discover genetic alterations that regulate the biological response to ionizing radiation. Thus, such integrative approaches may lead to genetic alterations that affect risk of normal tissue toxicity.

A simulated SNP experiment indicates a high risk of over-fitting and false positive results when a predictive multiple SNP model is established and tested within the same dataset.

Several relatively small studies have established predictive models for normal tissue radiosensitivity based on multiple SNPs. Even though these models yielded statistically significant results, the models were often inconsistent with each other. This can presumably be attributed to certain methodological problems related to the way these models were established and tested. In order to explore this potential problem, we conducted 10 simulated SNP experiments based on randomly assigned 'SNP genotypes' applied to a set of real clinical data. In 8 out of 10 times, a significant result was found for the model. This clearly demonstrates that the process of fitting the model to the dataset is indeed per se capable of producing nominally significant results. Thus, great caution should be taken when a multiple SNP model is established and tested within the same patient cohort.

Independent prospective validation of a predictive test for risk of radiation induced fibrosis based on the gene expression pattern in fibroblasts irradiated in vitro.

PURPOSE: In a previously published study, we established a predictive test for the risk of radiation-induced fibrosis based on the gene expression pattern in cultured fibroblast irradiated in vitro. The present study was conducted to seek an independent prospective validation of the predictive test in a cohort of patients given curative radiotherapy for head and neck cancer. MATERIALS AND METHODS: The study cohort comprised 160 consecutive head and neck cancer patients given curative radiotherapy between 2000 and 2004. The patients were treated according to the DAHANCA protocols. The patients were scored for subcutaneous fibrosis as part of routine follow up. Fibroblast culture was established from skin biopsies. The fibroblasts were irradiated in vitro using a fractionation scheme of 3 times 3.5 Gy. The expression of 9 genes was assessed before and after irradiation of the cells using real time PCR. RESULTS: Based on the radiation-induced expression of the assessed genes, the material was divided into 136 patients having the 'sensitive expression profile' and 24 patients having the 'resistant expression profile'. Within the subset of patients with the 'sensitive profile', the cumulative risk of severe fibrosis was 34% at 9 years (Kaplan-Meier) whereas no patients with the 'resistant profile' developed severe fibrosis (p = 0.035). CONCLUSION: Our study provided an independent prospective validation of the previously established predictive test for radiation induced fibrosis. In agreement with our initial findings, the classifier was able to identify a smaller subset of patients that seems to be rather radioresistant and could therefore potentially be considered for dose escalation.

The psychosocial work environment among physicians employed at Danish oncology departments in 2009. A nationwide cross-sectional study.

UNLABELLED: Working as a physician at an oncology department has some distinctive characteristics that may lead to a stressful work environment. The present study was conducted to provide a nationwide description of the work conditions of all oncologists in Denmark. By comparing the results of the present study with those of a similar study carried out in 2006, the aim was furthermore to elucidate changes in the psychosocial work environment over time. MATERIAL AND METHODS: From May to September 2009, 330 physicians employed at six oncology centres and seven community based oncology departments were invited to participate in a survey based on the short version of the COPSOQ II questionnaire. The results were compared with data from a representative section of Danish employees and with data from the 2006 survey. RESULTS: Two hundred and twenty of the 330 invited physicians returned the questionnaire (response rate 67%). Concerning the aspects quantitative demands, work pace, emotional demands, influence, burnout and stress, the oncologists reported worse work conditions than the average Danish employee. However, with regard to possibilities for development, meaning of work and commitment to workplace, the oncologists reported better work conditions. Between 2006 and 2009, substantial improvement was seen concerning several of the assessed work environment aspects within the group of young physicians at the oncology centres. CONCLUSION: Though substantial improvement of the work conditions has been achieved between 2006 and 2009, certain aspects of the psychosocial work environment at Danish oncology departments still require attention.

Will SNPs be useful predictors of normal tissue radiosensitivity in the future?

The ability to predict individual risk of radiation-induced normal tissue complications is a long sought goal in radiobiology. The last decade saw increasing interest in identifying associations between single nucleotide polymorphisms (SNPs) and normal tissue complication risk. Nevertheless, it remains controversial whether SNPs will be useful predictors of normal tissue radiosensitivity. This paper provides a summary of a scientific debate held at the 31st ESTRO conference in which four scientists argued in favor or against the motion that SNPs will be useful predictors of normal tissue radiosensitivity in the future.

Conducting radiogenomic research--do not forget careful consideration of the clinical data.

The field of radiogenomics has evolved substantially over the last few years. Cooperative research groups have been established and high throughput genotyping has become increasingly feasible and affordable. Nevertheless, a number of clinical and dosimetric issues need to be carefully considered in order to fully exploit these new possibilities.

Genetic variants and normal tissue toxicity after radiotherapy: a systematic review.

During the last decade, nearly 60 studies have addressed possible associations between various genetic sequence alterations and risk of adverse reactions after radiotherapy. We report here an overview of these studies with information on the genetic variants, tumour type, number of patients included, the endpoint studied, the mechanism(s) by which the candidate genes are involved in the pathogenesis of normal tissue toxicity, and odds ratios (ORs) for candidate variants. Though many positive results have been reported, inconsistent findings and non-replication of previous results have frequently occurred. This can presumably be attributed to certain methodological shortcomings including lack of statistical power to detect small effect sizes. Based on theoretical considerations and experiences from other scientific fields, we discuss how future studies should be designed in order to successfully unravel the genetics of normal tissue radiosensitivity. We propose a model of the allelic architecture that may underlie differences in normal tissue radiosensitivity. Genome wide association studies have proven a powerful tool to identify novel loci that affect various phenotypes. Nonetheless, genome wide association studies are extremely demanding in terms of sample size. Furthermore, certain limitations still relate to this kind of studies, emphasizing the need for international consortia such as the ESTRO GENEPI.

Genetic markers for prediction of normal tissue toxicity after radiotherapy.

During the last decade, a number of studies have supported the hypothesis that there is an important genetic component to the observed interpatient variability in normal tissue toxicity after radiotherapy. This review summarizes the candidate gene association studies published so far on the risk of radiation-induced morbidity and highlights some recent successful whole-genome association studies showing feasibility in other research areas. Future genetic association studies are discussed in relation to methodological problems such as the characterization of clinical and biological phenotypes, genetic haplotypes, and handling of confounding factors. Finally, candidate gene studies elucidating the genetic component of radiation-induced morbidity and the functional consequences of single nucleotide polymorphisms by studying intermediate phenotypes will be discussed.

Can risk of radiotherapy-induced normal tissue complications be predicted from genetic profiles?

Over the last decade, increasing efforts have been taken to establish associations between various genetic germline alterations and risk of normal tissue complications after radiotherapy. Though the studies have been relatively small and methodologically heterogeneous, preliminary indications have been provided that single nucleotide polymorphisms in the genes TGFB1 and ATM may modulate risk of particularly late toxicity. In addition, rare ATM alterations may enhance complication susceptibility. Nevertheless, we are still far from having an exhaustive understanding of the genetics that may underlie differences in clinical normal tissue radiosensitivity. Recent technical advances and emerging insights to the structure of inter-individual genetic variation open up unprecedented opportunities to dissect the molecular and genetic basis of normal tissue radiosensitivity. However, to fully exploit these new possibilities well-planed large-scale clinical studies are mandatory. Currently, international initiatives are taken to establish the bio banks and databases needed for this task.