Genome-wide association study of treatment-related toxicity two years following radiotherapy for breast cancer

Càncer de mama; Toxicitat crònica; RadiogenòmicaBreast cancer; Chronic toxicity; RadiogenomicsCáncer de mama; Toxicidad crónica; RadiogenómicaBackground 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.REQUITE received funding from the European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreement no. 601826. We thank all patients who participated in the REQUITE study and all the *members of the REQUITE project consortium in: Belgium: Ghent University Hospital; KU Leuven. France: ICM Montpellier, CHU Nîmes (Department of Radiation Oncology, CHU Nîmes, Nîmes, France). Germany: Zentrum für Strahlentherapie Freiburg (Dr. Petra Stegmaier); Städtisches Klinikum Karlsruhe (Dr. Bernhard Neu); ViDia Christliche Kliniken Karlsruhe (Prof. Johannes Claßen); Klinikum der Stadt Ludwigshafen GmbH (PD Dr. Thomas Schnabel); Universitätsklinikum Mannheim: Anette Kipke, Stefanie Kolb, Anke Keller and Christiane Zimmermann; Strahlentherapie Speyer (Dr. Jörg Schäfer). The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, and Sabine Behrens. Petra Seibold was supported by ERA PerMed JCT2018 funding (ERAPERMED2018-244, BMBF #01KU1912) and BfS funding (#3619S42261). Italy: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano; Candiolo Cancer Institute – FPO, IRCCS. Tiziana Rancati was partially funded by Fondazione Italo Monzino. Spain: Barcelona: Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus; VHIO acknowledge the Cellex Foundation for providing research facilities and the CERCA Programme/Generalitat de Catalunya for institutional support. Sara Gutiérrez-Enríquez is supported by ERAPerMed JTC2018 funding (ERAPERMED2018-244 and SLT011/18/00005) and the Government of Catalonia (2021SGR01112). Santiago: Complexo Hospitalario Universitario de Santiago. Ana Vega is supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI22/00589, PI19/01424, PI16/00046, PI13/ 02030, PI10/00164; INT20/00071, INT17/00133, INT16/00154, INT15/00070), through the Autonomous Government of Galicia (Consolidation and structuring program: IN607B), by ERAPerMed JTC2018 funding (ERAPERMED2018-244) and by the AECC (PRYES211091VEGA). UK: University Hospitals of Leicester NHS Trust: Theresa Beaver, Sara Barrows, Monika Kaushik, Frances Kenny, Jaroslaw Krupa, Kelly V Lambert, Simon M Pilgrim, Sheila Shokuhi, Kalliope Valassidou, Kiran Kancherla, Kufre Sampson, Ahmed Osman and Kaitlin Walker. Harkeran K Jandu is supported by the Wellcome Trust Genetic Epidemiology and Public Health Genomics Doctoral Training Partnership (Grant Number: 218505/Z/19/Z). Tim Rattay was funded by a National Institute of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002). He was previously funded by an NIHR Doctoral Research Fellowship (DRF 2014-07-079). This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. University of Manchester: Catharine West and Rebecca Elliott are supported by the NIHR Manchester Biomedical Research Centre and Catharine West is supported by Cancer Research UK (C1094/A18504, C147/A25254). USA: Mount Sinai Hospital, New York

Evaluation of DNA Single and Double Strand Breaks in Women with Cervical Neoplasia Based on Alkaline and Neutral Comet Assay Techniques

A hospital-based unmatched case-control study was performed in order to determine the relation of DNA single (ssb) and double (dsb) strand breaks in women with and without cervical neoplasia. Cervical epithelial cells of 30 women: 10 with low grade squamous intraepithelial lesions (LG-SIL), 10 with high-grade SIL (HG-SIL), and 10 without cervical lesions were evaluated using alkaline and neutral comet assays. A significant increase in global DNA damage (ssb + dsb) and dsb was observed in patients with HG-SIL (48.90 ± 12.87 and 23.50 ± 13.91), patients with LG-SIL (33.60 ± 14.96 and 11.20 ± 5.71), and controls (21.70 ± 11.87 and 5.30 ± 5.38; resp.). Pearson correlation coefficient reveled a strong relation between the levels ssb and dsb (2=0.99, =0.03, and 2=0.94, =0.16, resp.) and progression of neoplasia. The increase of dsb damage in patients with HG-SIL was confirmed by DNA breakage detection-FISH (DBD-FISH) on neutral comets. Our results argue in favor of a real genomic instability in women with cervical neoplasia, which was strengthened by our finding of a higher proportion of DNA dsb

Treatment time and circadian genotype interact to influence radiotherapy side-effects. A prospective European validation study using the REQUITE cohort

Breast cancer; Circadian rhythm; RadiotherapyCáncer de mama; Ritmo circadiano; RadioterapiaCàncer de mama; Ritme circadià; RadioteràpiaBackground Circadian rhythm impacts broad biological processes, including response to cancer treatment. Evidence conflicts on whether treatment time affects risk of radiotherapy side-effects, likely because of differing time analyses and target tissues. We previously showed interactive effects of time and genotypes of circadian genes on late toxicity after breast radiotherapy and aimed to validate those results in a multi-centre cohort. Methods Clinical and genotype data from 1690 REQUITE breast cancer patients were used with erythema (acute; n=340) and breast atrophy (two years post-radiotherapy; n=514) as primary endpoints. Local datetimes per fraction were converted into solar times as predictors. Genetic chronotype markers were included in logistic regressions to identify primary endpoint predictors. Findings Significant predictors for erythema included BMI, radiation dose and PER3 genotype (OR 1.27(95%CI 1.03-1.56); P < 0.03). Effect of treatment time effect on acute toxicity was inconclusive, with no interaction between time and genotype. For late toxicity (breast atrophy), predictors included BMI, radiation dose, surgery type, treatment time and SNPs in CLOCK (OR 0.62 (95%CI 0.4-0.9); P < 0.01), PER3 (OR 0.65 (95%CI 0.44-0.97); P < 0.04) and RASD1 (OR 0.56 (95%CI 0.35-0.89); P < 0.02). There was a statistically significant interaction between time and genotypes of circadian rhythm genes (CLOCK OR 1.13 (95%CI 1.03-1.23), P < 0.01; PER3 OR 1.1 (95%CI 1.01-1.2), P < 0.04; RASD1 OR 1.15 (95%CI 1.04-1.28), P < 0.008), with peak time for toxicity determined by genotype. Interpretation Late atrophy can be mitigated by selecting optimal treatment time according to circadian genotypes (e.g. treat PER3 rs2087947C/C genotypes in mornings; T/T in afternoons). We predict triple-homozygous patients (14%) reduce chance of atrophy from 70% to 33% by treating in mornings as opposed to mid-afternoon. Future clinical trials could stratify patients treated at optimal times compared to those scheduled normally.EU-FP7

(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer

Breast cancer; Fatigue; RadiotherapyCáncer de mama; Fatiga; RadioterapiaCàncer de mama; Fatiga; RadioteràpiaFatigue is common in breast-cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long-term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI-20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post-RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI-20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P < .05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI-20 fatigue dimensions (ORGeneralFatigue = 3.81, P < .001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered.We thank all patients who participated in the REQUITE study and all the REQUITE staff involved in this project. Belgium: Ghent University Hospital; KU Leuven. France: ICM Montpellier, CHU Nîmes (Department of Radiation Oncology, CHU Nîmes, Nîmes, France). Germany: Zentrum für Strahlentherapie Freiburg (Dr. Petra Stegmaier); Städtisches Klinikum Karlsruhe (Dr. Bernhard Neu); ViDia Christliche Kliniken Karlsruhe (Prof. Johannes Claßen); Klinikum der Stadt Ludwigshafen GmbH (PD Dr. Thomas Schnabel); Universitätsklinikum Mannheim: Anette Kipke and Christiane Zimmermann; Strahlentherapie Speyer (Dr. Jörg Schäfer). The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Axel Benner, Nicholas Schreck. Petra Seibold is supported by ERA PerMed 2018 funding (BMBF #01KU1912) and BfS funding (#3619S42261). Italy: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano; Candiolo Cancer Institute – FPO, IRCCS. Tiziana Rancati was partially funded by Fondazione Italo Monzino. The Netherlands: Sylvie Canisius at Maastro Clinics, Maastricht. Spain: Barcelona: Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus; VHIO acknowledge the Cellex Foundation for providing research facilities and thank CERCA Programme/Generalitat de Catalunya for institutional support. Sara Gutiérrez-Enríquez is supported by ERAPerMed JTC2018 funding (ERAPERMED2018-244 and SLT011/18/00005). Santiago: Complexo Hospitalario Universitario de Santiago. Ana Vega: supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI22/00589, PI19/01424; INT20/00071); the ERAPerMed JTC2018 funding (AC18/00117); the Autonomous Government of Galicia (Consolidation and structuring program: IN607B), by the Fundación Mutua Madrileña (call 2018) and by the AECC (PRYES211091VEGA); UK: University Hospitals of Leicester NHS Trust; Theresa Beaver, Kaitlin Walker and Sara Barrows. Dr Tim Rattay was funded by a National Institute of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002) and is currently supported by the NIHR Leicester Biomedical Research Centre. He was previously funded by a National Institute of Health Research (NIHR) Doctoral Research Fellowship (DRF 2014-07-079). This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Manchester: Catharine West and Rebecca Elliott are supported by NIHR Manchester Biomedical Research Centre and Catharine West is supported by Cancer Research UK (C1094/A18504, C147/A25254). USA: Mount Sinai Hospital, New York. Open Access funding enabled and organized by Projekt DEAL

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

Meta-genome; Toxicities; CancerMetagenoma; Toxicidades; CáncerMetagenoma; Toxicitats; CàncerBackground 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.E.N. was supported by a scholarship for a PhD from the University of Groningen, Groningen, The Netherlands. T.D. is funded as an Academic Clinical Fellow by the National Institute for Health Research, UK. D.J.T. is supported by a grant from The Taylor Family Foundation and Cancer Research UK [C19941/A30286]. M.L.K.C. is supported by the National Medical Research Council Singapore Clinician Scientist Award (NMRC/CSA-INV/0027/2018), National Research Foundation Proton Competitive Research Program (NRF-CRP17-2017-05), Ministry of Education Tier 3 Academic Research Fund (MOE2016-T3-1-004), the Duke-NUS Oncology Academic Program Goh Foundation Proton Research Programme, NCCS Cancer Fund, and the Kua Hong Pak Head and Neck Cancer Research Programme. G.C.B. is supported by Cancer research UK RadNet Cambridge [C17918/A28870]. RADIOGEN research was supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (INT20/00071, INT15/00070, INT17/00133, INT16/00154; PI19/01424; PI16/00046; PI13/02030; PI10/00164); by AECC grant PRYES211091VEGA and through the Autonomous Government of Galicia (Consolidation and structuring program: IN607B). C.N.A. and L.M.H.S. received funding from the Danish Cancer Society (grant R231-A14074-B2537). T.R. was funded by a National Institutes of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002) and is supported by the NIHR Leicester Biomedical Research Centre. This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. REQUITE received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement No. 601826. S.G.E. is supported by the government of Catalonia 2021SGR01112. L.D. was supported by the European Union Horizon 2020 research and innovation programs BRIDGES (grant No. 634935)

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

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

Background and purpose: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). Materials and methods: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. Results: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified “3′-5'-exoribonuclease activity” (FDR = 1.6e-10) for dysphagia, “inositol phosphate-mediated signalling” for mucositis (FDR = 2.20e-09), and “drug catabolic process” for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). Conclusion: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies

High weekly integral dose and larger fraction size increase risk of fatigue and worsening of functional outcomes following radiotherapy for localized prostate cancer

IntroductionWe hypothesized that increasing the pelvic integral dose (ID) and a higher dose per fraction correlate with worsening fatigue and functional outcomes in localized prostate cancer (PCa) patients treated with external beam radiotherapy (EBRT). MethodsThe study design was a retrospective analysis of two prospective observational cohorts, REQUITE (development, n=543) and DUE-01 (validation, n=228). Data were available for comorbidities, medication, androgen deprivation therapy, previous surgeries, smoking, age, and body mass index. The ID was calculated as the product of the mean body dose and body volume. The weekly ID accounted for differences in fractionation. The worsening (end of radiotherapy versus baseline) of European Organisation for Research and Treatment of Cancer EORTC) Quality of Life Questionnaire (QLQ)-C30 scores in physical/role/social functioning and fatigue symptom scales were evaluated, and two outcome measures were defined as worsening in >= 2 (WS2) or >= 3 (WS3) scales, respectively. The weekly ID and clinical risk factors were tested in multivariable logistic regression analysis. ResultsIn REQUITE, WS2 was seen in 28% and WS3 in 16% of patients. The median weekly ID was 13.1 L center dot Gy/week [interquartile (IQ) range 10.2-19.3]. The weekly ID, diabetes, the use of intensity-modulated radiotherapy, and the dose per fraction were significantly associated with WS2 [AUC (area under the receiver operating characteristics curve) =0.59; 95% CI 0.55-0.63] and WS3 (AUC=0.60; 95% CI 0.55-0.64). The prevalence of WS2 (15.3%) and WS3 (6.1%) was lower in DUE-01, but the median weekly ID was higher (15.8 L center dot Gy/week; IQ range 13.2-19.3). The model for WS2 was validated with reduced discrimination (AUC=0.52 95% CI 0.47-0.61), The AUC for WS3 was 0.58, ConclusionIncreasing the weekly ID and the dose per fraction lead to the worsening of fatigue and functional outcomes in patients with localized PCa treated with EBRT

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Large-Scale Meta-GWAS Reveals Common Genetic Factors Linked to Radiation-Induced Acute Toxicities across Cancers

BACKGROUND: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity (RIT) across four cancer types (prostate, head and neck, breast, and lung).METHODS: A GWAS meta-analysis was performed using 19 cohorts including 12,042 patients. Acute standardized total average toxicity (rSTATacute) was modelled using a generalized linear regression model for additive effect of genetic variants adjusted for demographic and clinical covariates. LD score regression estimated shared SNP-based heritability of rSTATacute in all patients and for each cancer type.RESULTS: Shared SNP-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 SNPs with rSTATacute (5.0x10-8&lt;P-value&lt;1.0x10-5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size -0.17; P-value=1.7x10-7), 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 x10-6, Pcorrected =0.079) as the top gene set associated with rSTATacute among all patients. In-silico gene expression analysis showed the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed Pcorrected=0.004; sun exposed Pcorrected=0.026).CONCLUSIONS: There is shared SNP-based heritability for acute RIT across and within individual cancer sites. Future meta-GWAS among large radiotherapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.</p