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.

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.

Use of angiotensin converting enzyme inhibitors is associated with reduced risk of late bladder toxicity following radiotherapy for prostate cancer.

BACKGROUND AND PURPOSE: Genome-wide association studies (GWAS) of late hematuria following prostate cancer radiotherapy identified single nucleotide polymorphisms (SNPs) near AGT, encoding angiotensinogen. We tested the hypothesis that patients taking angiotensin converting enzyme inhibitors (ACEi) have a reduced risk of late hematuria. We additionally tested genetically-defined hypertension. MATERIALS AND METHODS: Prostate cancer patients undergoing potentially-curative radiotherapy were enrolled onto two multi-center observational studies, URWCI (N = 256) and REQUITE (N = 1,437). Patients were assessed pre-radiotherapy and followed prospectively for development of toxicity for up to four years. The cumulative probability of hematuria was estimated by the Kaplan-Meier method. Multivariable grouped relative risk models assessed the effect of ACEi on time to hematuria adjusting for clinical factors and stratified by enrollment site. A polygenic risk score (PRS) for blood pressure was tested for association with hematuria in REQUITE and our Radiogenomics Consortium GWAS. RESULTS: Patients taking ACEi during radiotherapy had a reduced risk of hematuria (HR 0.51, 95%CI 0.28 to 0.94, p = 0.030) after adjusting for prior transurethral prostate and/or bladder resection, heart disease, pelvic node radiotherapy, and bladder volume receiving 70 Gy, which are associated with hematuria. A blood pressure PRS was associated with hypertension (odds ratio per standard deviation 1.38, 95%CI 1.31 to 1.46, n = 5,288, p < 0.001) but not hematuria (HR per standard deviation 0.96, 95%CI 0.87 to 1.06, n = 5,126, p = 0.41). CONCLUSIONS: Our study is the first to show a radioprotective effect of ACEi on bladder in an international, multi-site study of patients receiving pelvic radiotherapy. Mechanistic studies are needed to understand how targeting the angiotensin pathway protects the bladder.

A SARS-CoV-2 sequence submission tool for the European Nucleotide Archive.

SUMMARY: Many aspects of the global response to the COVID-19 pandemic are enabled by the fast and open publication of SARS-CoV-2 genetic sequence data. The European Nucleotide Archive (ENA) is the European recommended open repository for genetic sequences. In this work, we present a tool for submitting raw sequencing reads of SARS-CoV-2 to ENA. The tool features a single-step submission process, a graphical user interface, tabular-formatted metadata and the possibility to remove human reads prior to submission. A Galaxy wrap of the tool allows users with little or no bioinformatics knowledge to do bulk sequencing read submissions. The tool is also packed in a Docker container to ease deployment. AVAILABILITY AND IMPLEMENTATION: CLI ENA upload tool is available at github.com/usegalaxy-eu/ena-upload-cli (DOI 10.5281/zenodo.4537621); Galaxy ENA upload tool at toolshed.g2.bx.psu.edu/view/iuc/ena_upload/382518f24d6d and github.com/galaxyproject/tools-iuc/tree/master/tools/ena_upload (development); and ENA upload Galaxy container at github.com/ELIXIR-Belgium/ena-upload-container (DOI 10.5281/zenodo.4730785).

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.

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts.

PURPOSE: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate. METHODS AND MATERIALS: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas under the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs). RESULTS: Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely. CONCLUSIONS: Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.

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.

Factors Associated With Early Mortality in Patients Treated With Concurrent Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer.

PURPOSE: Concurrent chemoradiation therapy (con-CRT) is recommended for fit patients with locally advanced non-small cell lung cancer (LA-NSCLC) but is associated with toxicity, and observed survival continues to be limited. Identifying factors associated with early mortality could improve patient selection and identify strategies to improve prognosis. METHODS AND MATERIALS: Analysis of a multi-institutional LA-NSCLC database consisting of 1245 patients treated with con-CRT in 13 institutions was performed to identify factors predictive of 180-day survival. Recursive partitioning analysis (RPA) was performed to identify prognostic groups for 180-day survival. Multivariate logistic regression analysis was used to create a clinical nomogram predicting 180-day survival based on important predictors from RPA. RESULTS: Median follow-up was 43.5 months (95% confidence interval [CI]: 40.3-48.8) and 127 patients (10%) died within 180 days of treatment. Median, 180-day, and 1- to 5-year (by yearly increments) actuarial survival rates were 20.9 months, 90%, 71%, 45%, 32%, 27%, and 22% respectively. Multivariate analysis adjusted by region identified gross tumor volume (GTV) (odds ratio [OR] ≥100 cm(3): 2.61; 95% CI: 1.10-6.20; P=.029) and pulmonary function (forced expiratory volume in 1 second [FEV1], defined as the ratio of FEV1 to forced vital capacity [FVC]) (OR <80%: 2.53; 95% CI: 1.09-5.88; P=.030) as significant predictors of 180-day survival. RPA resulted in a 2-class risk stratification system: low-risk (GTV <100 cm(3) or GTV ≥100 cm(3) and FEV1 ≥80%) and high-risk (GTV ≥100 cm(3) and FEV1 <80%). The 180-day survival rates were 93% for low risk and 79% for high risk, with an OR of 4.43 (95% CI: 2.07-9.51; P<.001), adjusted by region. A clinical nomogram predictive of 180-day survival, incorporating FEV1, GTV, N stage, and maximum esophagus dose yielded favorable calibration (R(2) = 0.947). CONCLUSIONS: This analysis identified several risk factors associated with early mortality and suggests that future research in the optimization of pretreatment pulmonary function and/or functional lung avoidance treatment may alter the therapeutic ratio in this patient population.

Focus on 16p13.3 Locus in Colon Cancer.

BACKGROUND: With one million new cases of colorectal cancer (CRC) diagnosed annually in the world, CRC is the third most commonly diagnosed cancer in the Western world. Patients with stage I-III CRC can be cured with surgery but are at risk for recurrence. Colorectal cancer is characterized by the presence of chromosomal deletions and gains. Large genomic profiling studies have however not been conducted in this disease. The number of a specific genetic aberration in a tumour sample could correlate with recurrence-free survival or overall survival, possibly leading to its use as biomarker for therapeutic decisions. At this point there are not sufficient markers for prediction of disease recurrence in colorectal cancer, which can be used in the clinic to discriminate between stage II patients who will benefit from adjuvant chemotherapy. For instance, the benefit of adjuvant chemotherapy has been most clearly demonstrated in stage III disease with an approximately 30 percent relative reduction in the risk of disease recurrence. The benefits of adjuvant chemotherapy in stage II disease are less certain, the risk for relapse is much smaller in the overall group and the specific patients at risk are hard to identify. MATERIALS AND METHODS: In this study, array-comparative genomic hybridization analysis (array-CGH) was applied to study high-resolution DNA copy number alterations in 93 colon carcinoma samples. These genomic data were combined with parameters like KRAS mutation status, microsatellite status and clinicopathological characteristics. RESULTS: Both large and small chromosomal losses and gains were identified in our sample cohort. Recurrent gains were found for chromosome 1q, 7, 8q, 13 and 20 and losses were mostly found for 1p, 4, 8p, 14, 15, 17p, 18, 21 and 22. Data analysis demonstrated that loss of chromosome 4 is linked to a worse prognosis in our patients series. Besides these alterations, two interesting small regions of overlap were identified, which could be associated with disease recurrence. Gain of the 16p13.3 locus (including the RNA binding protein, fox-1 homolog gene, RBFOX1) was linked with a worse recurrence-free survival in our patient cohort. On the other hand, loss of RBFOX1 was only found in patients without disease recurrence. Most interestingly, above mentioned characteristics were also found in stage II patients, for whom there is a high medical need for the identification of new prognostic biomarkers. CONCLUSIONS: In conclusion, copy number variation of the 16p13.3 locus seems to be an important parameter for prediction of disease recurrence in colon cancer.

Effect of the rs1051730-rs16969968 variant and smoking cessation treatment: a meta-analysis.

OBJECTIVE: To assess if the allelic variations of rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene cluster are associated with smoking cessation after nicotine replacement therapy (NRT). METHODS: We searched for NRT studies published from 2000-2013 that reported counts for allelic variation of rs16969968/rs1051730 and measured abstinence rates at the end of NRT treatment. We identified four studies which met the criteria, giving us a test sample of 2036 participants. RESULTS: There was no effect of rs16969968/rs1051730 in influencing the success rate at the end of NRT (n = 6, effect size [ES]: 0.969, 95% CI: 0.77 to 1.23, z = 0.27, p = 0.791). CONCLUSION: There is no robust evidence that allelic variations of rs16969968 or rs1051730 are associated with smoking cessation after NRT. Original submitted 26 November 2014; Revision submitted 9 March 2015.

Factors modifying the risk for developing acute skin toxicity after whole-breast intensity modulated radiotherapy.

BACKGROUND: After breast-conserving radiation therapy most patients experience acute skin toxicity to some degree. This may impair patients' quality of life, cause pain and discomfort. In this study, we investigated treatment and patient-related factors, including genetic polymorphisms, that can modify the risk for severe radiation-induced skin toxicity in breast cancer patients. METHODS: We studied 377 patients treated at Ghent University Hospital and at ST.-Elisabeth Clinic and Maternity in Namur, with adjuvant intensity modulated radiotherapy (IMRT) after breast-conserving surgery for breast cancer. Women were treated in a prone or supine position with normofractionated (25 × 2 Gy) or hypofractionated (15 × 2.67 Gy) IMRT alone or in combination with other adjuvant therapies. Patient- and treatment-related factors and genetic markers in regulatory regions of radioresponsive genes and in LIG3, MLH1 and XRCC3 genes were considered as variables. Acute dermatitis was scored using the CTCAEv3.0 scoring system. Desquamation was scored separately on a 3-point scale (0-none, 1-dry, 2-moist). RESULTS: Two-hundred and twenty patients (58%) developed G2+ dermatitis whereas moist desquamation occurred in 56 patients (15%). Normofractionation (both p < 0.001), high body mass index (BMI) (p = 0.003 and p < 0.001), bra cup size ≥ D (p = 0.001 and p = 0.043) and concurrent hormone therapy (p = 0.001 and p = 0.037) were significantly associated with occurrence of acute dermatitis and moist desquamation, respectively. Additional factors associated with an increased risk of acute dermatitis were the genetic variation in MLH1 rs1800734 (p=0.008), smoking during RT (p = 0.010) and supine IMRT (p = 0.004). Patients receiving trastuzumab showed decreased risk of acute dermatitis (p < 0.001). CONCLUSIONS: The normofractionation schedule, supine IMRT, concomitant hormone treatment and patient related factors (high BMI, large breast, smoking during treatment and the genetic variation in MLH1 rs1800734) were associated with increased acute skin toxicity in patients receiving radiation therapy after breast-conserving surgery. Trastuzumab seemed to be protective.

A let-7 microRNA polymorphism in the KRAS 3'-UTR is prognostic in oropharyngeal cancer.

INTRODUCTION: This study aimed to investigate the effect of genetic polymorphisms in miRNA sequences, miRNA target genes and miRNA processing genes as additional biomarkers to HPV for prognosis in oropharyngeal squamous cell carcinoma (OPSCC) patients. Secondarily, the prevalence of HPV-associated OPSCC in a European cohort was mapped. METHODS: OPSCC patients (n=122) were genotyped for ten genetic polymorphisms in pre-miRNAs (pre-mir-146a, pre-mir-196a2), in miRNA biosynthesis genes (Drosha, XPO5) and in miRNA target genes (KRAS, SMC1B). HPV status was assessed by p16 immunohistochemistry (IHC) and high-risk HPV in situ hybridization (ISH) or by p16 IHC and PCR followed by enzyme-immunoassay (EIA). Overall and disease specific survival were analysed using Kaplan-Meier plots (log-rank test). Cox proportional hazard model was used to calculate hazard ratios (HR). RESULTS: The overall HPV prevalence rate in our Belgian/Dutch cohort was 27.9%. Patients with HPV(+) tumours had a better 5-years overall survival (78% vs. 46%, p=0.001) and a better 5-years disease specific survival (90% vs. 70%, p=0.016) compared to patients with HPV(-) tumours. In multivariate Cox analysis including clinical, treatment and genetic parameters, HPV negativity (HR=3.89, p=0.005), advanced T-stage (HR=1.81, p=0.050), advanced N-stage (HR=5.86, p=0.001) and >10 pack-years of smoking (HR=3.45, p=0.012) were significantly associated with reduced overall survival. The variant G-allele of the KRAS-LCS6 polymorphism was significantly associated with a better overall survival (HR=0.40, p=0.031). CONCLUSIONS: Our results demonstrate that OPSCC patients with the KRAS-LCS6 variant have a better outcome and suggest that this variant may be used as a prognostic biomarker for OPSCC.

Integrated models for the prediction of late genitourinary complaints after high-dose intensity modulated radiotherapy for prostate cancer: making informed decisions.

BACKGROUND AND PURPOSE: To develop predictive models for late radiation-induced hematuria and nocturia allowing a patient individualized estimation of pre-treatment risk. MATERIALS AND METHODS: We studied 262 PCa patients treated with curative intensity modulated radiotherapy to the intact prostate or prostate bed. A total of 372 variables were used for prediction modeling, among which 343 genetic variations. Toxicity was scored using an in-house developed toxicity scale. Predictor selection is achieved by the EMLasso procedure, a penalized logistic regression method with an EM algorithm handling missing data and crossvalidation avoiding overfit. Model performance was expressed by the area under the curve (AUC) and by sensitivity and specificity. RESULTS: Variables of the model predicting late hematuria (36/262) are bladder volume receiving ⩾75 Gy, prostatic transurethral resection and four polymorphisms. (AUC = 0.80, sensitivity = 83.3%, specificity = 61.5%). The AUC drops to 0.67 when the genetic markers are left out. The model that predicts for late nocturia (29/262) contains the minimal clinical target volume (CTV) dose, the CTV volume and three polymorphisms (AUC = 0.76, sensitivity = 75.9%, specify = 67.4%). This model is a better predictor for nocturia compared to the nongenetic model (AUC of 0.60). CONCLUSIONS: We were able to develop models that predict for the occurrence of late radiation-induced hematuria and nocturia, including genetic factors which might improve the prediction of late urinary toxicity.

Predicting esophagitis after chemoradiation therapy for non-small cell lung cancer: an individual patient data meta-analysis.

PURPOSE: Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE. METHODS AND MATERIALS: After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade≥2 and grade≥3) were assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model. RESULTS: The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c>.60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade≥2 and grade≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60<0.07%), intermediate (V60 0.07% to 16.99%), and high (V60≥17%). With use of the validation set, the predictive model performed inferiorly for the grade≥2 endpoint (c=.58) but performed well for the grade≥3 endpoint (c=.66). CONCLUSIONS: Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.

Quantification of radiation-induced lung damage with CT scans: the possible benefit for radiogenomics.

BACKGROUND: Radiation-induced lung damage (RILD) is an important problem. Although physical parameters such as the mean lung dose are used in clinical practice, they are not suited for individualised radiotherapy. Objective, quantitative measurements of RILD on a continuous instead of on an ordinal, semi-quantitative, semi-subjective scale, are needed. METHODS: Hounsfield unit (HU) changes before versus three months post-radiotherapy were correlated per voxel with the radiotherapy dose in 95 lung cancer patients. Deformable registration was used to register pre- and post-CT scans and the density increase was quantified for various dose bins. The dose-response curve for increased HU was quantified using the slope of a linear regression (HU/Gy). The end-point for the toxicity analysis was dyspnoea ≥ grade 2. RESULTS: Radiation dose was linearly correlated with the change in HU (mean R(2) = 0.74 ± 0.28). No differences in HU/Gy between groups treated with stereotactic radiotherapy, conventional radiotherapy alone, sequential or concurrent chemo- radiotherapy were observed. In the whole patient group, 33/95 (34.7%) had dyspnoea ≥ G2. Of the 48 patients with a HU/Gy below the median, 16 (33.3%) developed dyspnoea ≥ G2, while in the 47 patients with a HU/Gy above the median, 17 (36.1%) had dyspnoea ≥ G2 (not significant). Individual patients showed a nearly 21-fold difference in radiosensitivity, with HU/Gy ranging from 0 to 10 HU/Gy. CONCLUSIONS: HU changes identify objectively the whole range of individual radiosensitivity on a continuous, quantitative scale. CT density changes may allow more robust and accurate radiogenomics studies.

A predictive model for dysphagia following IMRT for head and neck cancer: introduction of the EMLasso technique.

BACKGROUND AND PURPOSE: Design a model for prediction of acute dysphagia following intensity-modulated radiotherapy (IMRT) for head and neck cancer. Illustrate the use of the EMLasso technique for model selection. MATERIAL AND METHODS: Radiation-induced dysphagia was scored using CTCAE v.3.0 in 189 head and neck cancer patients. Clinical data (gender, age, nicotine and alcohol use, diabetes, tumor location), treatment parameters (chemotherapy, surgery involving the primary tumor, lymph node dissection, overall treatment time), dosimetric parameters (doses delivered to pharyngeal constrictor (PC) muscles and esophagus) and 19 genetic polymorphisms were used in model building. The predicting model was achieved by EMLasso, i.e. an EM algorithm to account for missing values, applied to penalized logistic regression, which allows for variable selection by tuning the penalization parameter through crossvalidation on AUC, thus avoiding overfitting. RESULTS: Fifty-three patients (28%) developed acute ≥ grade 3 dysphagia. The final model has an AUC of 0.71 and contains concurrent chemotherapy, D2 to the superior PC and the rs3213245 (XRCC1) polymorphism. The model's false negative rate and false positive rate in the optimal operation point on the ROC curve are 21% and 49%, respectively. CONCLUSIONS: This study demonstrated the utility of the EMLasso technique for model selection in predictive radiogenetics.

Acute radiation-induced nocturia in prostate cancer patients is associated with pretreatment symptoms, radical prostatectomy, and genetic markers in the TGFß1 gene.

PURPOSE: After radiation therapy for prostate cancer, approximately 50% of the patients experience acute genitourinary symptoms, mostly nocturia. This may be highly bothersome with a major impact on the patient's quality of life. In the past, nocturia is seldom reported as a single, physiologically distinct endpoint, and little is known about its etiology. It is assumed that in addition to dose-volume parameters and patient- and therapy-related factors, a genetic component contributes to the development of radiation-induced damage. In this study, we investigated the association among dosimetric, clinical, and TGFß1 polymorphisms and the development of acute radiation-induced nocturia in prostate cancer patients. METHODS AND MATERIALS: Data were available for 322 prostate cancer patients treated with primary or postoperative intensity modulated radiation therapy (IMRT). Five genetic markers in the TGFß1 gene (-800 G>A, -509 C>T, codon 10 T>C, codon 25 G>C, g.10780 T>G), and a high number of clinical and dosimetric parameters were considered. Toxicity was scored using an symptom scale developed in-house. RESULTS: Radical prostatectomy (P<.001) and the presence of pretreatment nocturia (P<.001) are significantly associated with the occurrence of radiation-induced acute toxicity. The -509 CT/TT (P=.010) and codon 10 TC/CC (P=.005) genotypes are significantly associated with an increased risk for radiation-induced acute nocturia. CONCLUSIONS: Radical prostatectomy, the presence of pretreatment nocturia symptoms, and the variant alleles of TGFß1 -509 C>T and codon 10 T>C are identified as factors involved in the development of acute radiation-induced nocturia. These findings may contribute to the research on prediction of late nocturia after IMRT for prostate cancer.

No association between TGF-ß1 polymorphisms and radiation-induced lung toxicity in a European cohort of lung cancer patients.

This study aimed at validating the previously published association between TGF-ß1 single nucleotide polymorphisms and a reduced risk for radiation-induced lung toxicity. We were not able to confirm the reported association, neither using maximum dyspnea score nor after correction for baseline dyspnea score.

Epigenetic changes in lymphocytes of solvent-exposed individuals.

AIM: We investigated global DNA methylation alterations in lymphocytes of solvent workers and chronic toxic encephalopathy (CTE) patients and explored potential gene-environment interactions for GST. POPULATION & METHODS: A cross-sectional study was set up in 41 referents, 128 solvent workers and 23 CTE patients. RESULTS: We found a global DNA hypermethylation in the solvent-exposed population compared with the referents (p = 0.001, r = -0.544). Global DNA methylation was negatively associated with exposure. Furthermore, GSTP1 genotypic polymorphism was found to be significantly associated (p = 0.033) with global DNA hypomethylation, which indicates a potential role for gene-environment interaction in the etiology of solvent-induced neurobehavioral disorders. CONCLUSION: This study indicates that solvent-induced DNA methylation alterations have an impact on neurotoxicity and development of CTE.