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

ABSTRACT: 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.

SUBMITTER: Kerns SL

PROVIDER: S-EPMC5036513 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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

Kerns Sarah L SL Dorling Leila L Fachal Laura L Bentzen Søren S Pharoah Paul D P PD Barnes Daniel R DR Gómez-Caamaño Antonio A Carballo Ana M AM Dearnaley David P DP Peleteiro Paula P Gulliford Sarah L SL Hall Emma E Michailidou Kyriaki K Carracedo Ángel Á Sia Michael M Stock Richard R Stone Nelson N NN Sydes Matthew R MR Tyrer Jonathan P JP Ahmed Shahana S Parliament Matthew M Ostrer Harry H Rosenstein Barry S BS Vega Ana A Burnet Neil G NG Dunning Alison M AM Barnett Gillian C GC West Catharine M L CM

EBioMedicine 20160720

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 ...[more]

PMID: 27515689

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Project description:BackgroundA 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.MethodsWe 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.ResultsMeta-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.ConclusionsThis 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.

Project description:Radiation-induced normal-tissue toxicities are common, complex, and distressing side effects that affect 90% of patients receiving breast-cancer radiotherapy and 40% of patients post radiotherapy. In this study, the authors investigated the use of spectrophotometry and ultrasound to quantitatively measure radiation-induced skin discoloration and subcutaneous-tissue fibrosis. The study's purpose is to determine whether skin discoloration correlates with the development of fibrosis in breast-cancer radiotherapy.Eighteen breast-cancer patients were enrolled in our initial study. All patients were previously treated with a standard course of radiation, and the median follow-up time was 22 months. The treated and untreated breasts were scanned with a spectrophotometer and an ultrasound. Two spectrophotometer parameters-melanin and erythema indices-were used to quantitatively assess skin discoloration. Two ultrasound parameters-skin thickness and Pearson coefficient of the hypodermis-were used to quantitatively assess severity of fibrosis. These measurements were correlated with clinical assessments (RTOG late morbidity scores).Significant measurement differences between the treated and contralateral breasts were observed among all patients: 27.3% mean increase in skin thickness (p < 0.001), 34.1% mean decrease in Pearson coefficient (p < 0.001), 27.3% mean increase in melanin (p < 0.001), and 22.6% mean increase in erythema (p < 0.001). All parameters except skin thickness correlated with RTOG scores. A moderate correlation exists between melanin and erythema; however, spectrophotometer parameters do not correlate with ultrasound parameters.Spectrophotometry and quantitative ultrasound are objective tools that assess radiation-induced tissue injury. Spectrophotometer parameters did not correlate with those of quantitative ultrasound suggesting that skin discoloration cannot be used as a marker for subcutaneous fibrosis. These tools may prove useful for the reduction of radiation morbidities and improvement of patient quality of life.

Project description:Purpose: Dosimetric predictors of toxicity after Stereotactic Body Radiation Therapy (SBRT) are not well-established. We sought to develop a multivariate model that predicts Common Terminology Criteria for Adverse Events (CTCAE) late grade 2 or greater genitourinary (GU) toxicity by interrogating the entire dose-volume histogram (DVH) from a large cohort of prostate cancer patients treated with SBRT on prospective trials. Methods: Three hundred and thirty-nine patients with late CTCAE toxicity data treated with prostate SBRT were identified and analyzed. All patients received 40 Gy in five fractions, every other day, using volumetric modulated arc therapy. For each patient, we examined 910 candidate dosimetric features including maximum dose, volumes of each organ [CTV, organs at risk (OARs)], V100%, and other granular volumetric/dosimetric indices at varying volumetric/dosimetric values from the entire DVH as well as ADT use to model and predict toxicity from SBRT. Training and validation subsets were generated with 90 and 10% of the patients in our cohort, respectively. Predictive accuracy was assessed by calculating the area under the receiver operating curve (AROC). Univariate analysis with student t-test was first performed on each candidate DVH feature. We subsequently performed advanced machine-learning multivariate analyses including classification and regression tree (CART), random forest, boosted tree, and multilayer neural network. Results: Median follow-up time was 32.3 months (range 3-98.9 months). Late grade ?2 GU toxicity occurred in 20.1% of patients in our series. No single dosimetric parameter had an AROC for predicting late grade ?2 GU toxicity on univariate analysis that exceeded 0.599. Optimized CART modestly improved prediction accuracy, with an AROC of 0.601, whereas other machine learning approaches did not improve upon univariate analyses. Conclusions: CART-based machine learning multivariate analyses drawing from 910 dosimetric features and ADT use modestly improves upon clinical prediction of late GU toxicity alone, yielding an AROC of 0.601. Biologic predictors may enhance predictive models for identifying patients at risk for late toxicity after SBRT.

Project description:BackgroundRecent studies have shown that radiation-induced pelvic toxicity often requires urological consultation. However, the 10-year incidence of genitourinary toxicity following intensity-modulated radiotherapy (IMRT) amongst patients with localised prostate cancer remains unclear. Hence, we conducted a systematic review and meta-analysis to determine the incidence of late genitourinary toxicity relying on Radiation Therapy Oncology Group (RTOG) and Common Terminology Criteria for Adverse Events (CTCAE) grade as well as the incidence of specific genitourinary toxicity. Secondary objectives involved quantifing the number of studies reporting 120-month follow-up endpoints, time to event analysis, predictive factors or economic evaluation.MethodsArticles published from January 2008 to December 2021 describing prospective studies were systematically searched in MEDLINE, EMBASE and Cochrane (PROSPERO protocol CRD42019133320). Quality assessment was performed by use of the Cochrane Risk of Bias 2 Tool for RCTs and the Newcastle Ottowa Scale for non-RCTs. Meta-analysis was performed on the 60-month incidence of RTOG and CTCAE Grade ≥2 genitourinary toxicity, haematuria, urinary retention and urinary incontinence.ResultsWe screened 4721 studies and six studies met our inclusion criteria. All included studies involved normofractionation, three included a hypofractionation comparator arm and none involved nodal irradiation. The pooled 60-month cumulative incidence of RTOG and CTCAE Grade ≥2 genitourinary toxicity were 17% (95% CI: 5-20%, n = 678) and 33% (95% CI: 27-38%, n = 153), respectively. The pooled 60-month cumulative incidence of Haematuria was 5% (95% CI: -4-14%, n = 48), Urinary incontinence 12% (95% CI: 6-18%, n = 194), Urinary retention 24% (95% CI: 9-40%, n = 10). One study reported time to event analyses, one reported predictive factors, no studies reported economic analysis or 120-month toxicity. There was considerable heterogeneity amongst the studies.ConclusionThere are few high-quality studies reporting 60-month toxicity rates after IMRT. Conservative estimates of 60-month toxicity rates are high and there is need for longer follow-up and consistent toxicity reporting standards.

Dataset Information

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

Publications

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

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