Impact of ATM rs1801516 on late skin reactions of radiotherapy for breast cancer: Evidences from a cohort study and a trial sequential meta-analysis

Autoři: Salvatore Terrazzino aff001;  Sarah Cargnin aff001;  Letizia Deantonio aff002;  Carla Pisani aff003;  Laura Masini aff003;  Pier Luigi Canonico aff001;  Armando A. Genazzani aff001;  Marco Krengli aff003
Působiště autorů: Department of Pharmaceutical Sciences and Centro di Ricerca Interdipartimentale di Farmacogenetica e Farmacogenomica (CRIFF), University of Piemonte Orientale, Novara, Italy aff001;  Radiation Oncology Clinic, Oncology Institute of Southern Switzerland, Bellinzona-Lugano, Bellinzona, Switzerland aff002;  Radiotherapy, University Hospital Maggiore della Carità, Novara, Italy aff003;  Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy aff004
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225685


The relationship between the ataxia-telangiectasia mutated (ATM) rs1801516 gene polymorphism and risk of radiation-induced late skin side effects remains a highly debated issue. In the present study, we assessed the role of ATM rs1801516 as risk factor for radiation-induced fibrosis and telangiectasia, using the LENT-SOMA scoring scale in 285 breast cancer patients who received radiotherapy after breast conserving surgery. A systematic review with meta-analysis and trial sequential analysis (TSA) was then conducted to assess reliability of the accumulated evidence in breast cancer patients. In our cohort study, no association was found between ATM rs1801516 and grade ≥ 2 telangiectasia (GA+AA vs GG, HRadjusted: 0.699; 95%CI: 0.273–1.792, P = 0.459) or grade ≥ 2 fibrosis (GA+AA vs GG, HRadjusted: 1.175; 95%CI: 0.641–2.154, P = 0.604). Twelve independent cohorts of breast cancer patients were identified through the systematic review, of which 11 and 9 cohorts focused respectively on the association with radiation-induced fibrosis and radiation-induced telangiectasia. Pooled analyses of 10 (n = 2928 patients) and 12 (n = 2783) cohorts revealed, respectively, no association of ATM rs1801516 with radiation-induced telangiectasia (OR: 1.14; 95%CI: 0.88–1.48, P = 0.316) and a significant correlation with radiation-induced fibrosis (OR: 1.23; 95%CI: 1.00–1.51, P = 0.049), which however did not remain significant after TSA adjustment (TSA-adjusted 95%CI: 0.85–1.78). These results do not support an impact of ATM rs1801516 on late skin reactions of radiotherapy for breast cancer, nevertheless further large studies are still required for conclusive evidences.

Klíčová slova:

Breast cancer – Fibrosis – Radiation therapy – Systematic reviews – Toxicity – Vascular diseases – Booster doses


1. Wallgren A. Late effects of radiotherapy in the treatment of breast cancer. Acta Oncol. 1992; 31: 237–242. doi: 10.3109/02841869209088909 1622640

2. Bray FN, Simmons BJ, Wolfson AH, Nouri K. Acute and Chronic Cutaneous Reactions to Ionizing Radiation Therapy. Dermatol Ther. (Heidelb) 2016;6: 185–206.

3. Deantonio L, Gambaro G, Beldì D, Masini L, Tunesi S, Magnani C, et al. Hypofractionated radiotherapy after conservative surgery for breast cancer: analysis of acute and late toxicity. Radiat Oncol. 2010;5:112. doi: 10.1186/1748-717X-5-112 21092288

4. Lilla C, Ambrosone CB, Kropp S, Helmbold I, Schmezer P, von Fournier D, et al. Predictive factors for late normal tissue complications following radiotherapy for breast cancer. Breast Cancer Res Treat. 2007;106: 143–150. doi: 10.1007/s10549-006-9480-9 17221151

5. Andreassen CN, Alsner J. Genetic variants and normal tissue toxicity after radiotherapy: a systematic review. Radiother Oncol. 2009;92: 299–309. doi: 10.1016/j.radonc.2009.06.015 19683821

6. Barnett GC, Thompson D, Fachal L, Kerns S, Talbot C, Elliott RM, et al. A genome wide association study (GWAS) providing evidence of an association between common genetic variants and late radiotherapy toxicity. Radiother Oncol. 2014;111: 178–185. doi: 10.1016/j.radonc.2014.02.012 24785509

7. Wang TM, Shen GP, Chen MY, Zhang JB, Sun Y, He J, et al. Genome-Wide Association Study of Susceptibility Loci for Radiation-Induced Brain Injury. J Natl Cancer Inst. 2018 Oct 8. doi: 10.1093/jnci/djy150 30299488

8. Wray NR, Yang J, Hayes BJ, Price AL, Goddard ME, Visscher PM. Pitfalls of predicting complex traits from SNPs. Nat Rev Genet. 2013;14: 507–515. doi: 10.1038/nrg3457 23774735

9. Zhu ML, Wang M, Shi TY, Li QX, Xi P, Xia KQ, et al. No association between TGFB1 polymorphisms and late radiotherapy toxicity: a meta-analysis. PLoS One. 2013;8: e76964. doi: 10.1371/journal.pone.0076964 24130819

10. Song YZ, Duan MN, Zhang YY, Shi WY, Xia CC, Dong LH. ERCC2 polymorphisms and radiation-induced adverse effects on normal tissue: systematic review with meta-analysis and trial sequential analysis. Radiat Oncol. 2015;10: 247. doi: 10.1186/s13014-015-0558-6 26627042

11. Zhao J, Zhi Z, Zhang M, Li Q, Li J, Wang X, et al. Predictive value of single nucleotide polymorphisms in XRCC1 for radiation-induced normal tissue toxicity. Onco Targets Ther. 2018;11: 3901–3918. doi: 10.2147/OTT.S156175 30013370

12. Shiloh Y. ATM and related protein kinases: safeguarding genome integrity. Nat Rev Cancer. 2003; 3: 155–168. doi: 10.1038/nrc1011 12612651

13. Bakkenist CJ, Kastan MB. DNA damage activates ATM through intermolecular autophosphorylation and dimer dissociation. Nature. 2003;421: 499–506. doi: 10.1038/nature01368 12556884

14. Amirifar P, Ranjouri MR, Yazdani R, Abolhassani H, Aghamohammadi A. Ataxia-telangiectasia: A review of clinical features and molecular pathology. Pediatr Allergy Immunol. 209; 30: 277–288. doi: 10.1111/pai.13020 30685876

15. DahlBerg WK, Little JB. Response of dermal fibroblast cultures from patients with unusually severe responses to radiotherapy and from ataxia telangiectasia heterozygotes to fractionated radiation. Clin Cancer Res. 1995;1: 785–790. 9816046

16. Cole J, Arlett CF, Green MH, Harcourt SA, Priestley A, Henderson L, et al. Comparative human cellular radiosensitivity: II. The survival following gamma-irradiation of unstimulated (G0) T-lymphocytes, T-lymphocyte lines, lymphoblastoid cell lines and fibroblasts from normal donors, from ataxia-telangiectasia patients and from ataxia-telangiectasia heterozygotes. Int J Radiat Biol. 1988;54: 929–943. doi: 10.1080/09553008814552331 2903890

17. Iannuzzi CM, Atencio DP, Green S, Stock RG, Rosenstein BS. ATM mutations in female breast cancer patients predict for an increase in radiation-induced late effects. Int J Radiat Oncol Biol Phys. 2002;52: 606–613. doi: 10.1016/s0360-3016(01)02684-0 11849780

18. Angèle S, Romestaing P, Moullan N, Vuillaume M, Chapot B, Friesen M, et al. ATM haplotypes and cellular response to DNA damage: association with breast cancer risk and clinical radiosensitivity. Cancer Res. 2003;63: 8717–8725. 14695186

19. Tanteles GA, Murray RJ, Mills J, Barwell J, Chakraborti P, Chan S, et al. Variation in telangiectasia predisposing genes is associated with overall radiation toxicity. Int J Radiat Oncol Biol Phys. 2012;84: 1031–1036. doi: 10.1016/j.ijrobp.2012.02.018 22677372

20. Dong L, Cui J, Tang F, Cong X, Han F. Ataxia telangiectasia-mutated gene polymorphisms and acute normal tissue injuries in cancer patients after radiation therapy: a systematic review and meta-analysis. Int J Radiat Oncol Biol Phys. 2015;91: 1090–1098. doi: 10.1016/j.ijrobp.2014.12.041 25832699

21. Zhang Y, Liu Z, Wang M, Tian H, Su K, Cui J, et al. Single Nucleotide Polymorphism rs1801516 in Ataxia Telangiectasia-Mutated Gene Predicts Late Fibrosis in Cancer Patients After Radiotherapy: A PRISMA-Compliant Systematic Review and Meta-Analysis. Medicine. 2016;95: e3267. doi: 10.1097/MD.0000000000003267 27057881

22. Su M, Yin ZH, Wu W, Li XL, Zhou BS. Meta-analysis of associations between ATM Asp1853Asn and TP53 Arg72Pro polymorphisms and adverse effects of cancer radiotherapy. Asian Pac J Cancer Prev. 2014;15: 10675–10681. doi: 10.7314/apjcp.2014.15.24.10675 25605158

23. Wetterslev J, Jakobsen JC, Gluud C. Trial Sequential Analysis in systematic reviews with meta-analysis. BMC Med Res Methodol. 2017;17: 39. doi: 10.1186/s12874-017-0315-7 28264661

24. Pavy JJ, Denekamp J, Letschert J, Littbrand B, Mornex F, Bernier J, et al. EORTC Late Effects Working Group. Late effects toxicity scoring: the SOMA scale. Int J Radiat Oncol Biol Phys. 1995;31: 1043–1047. doi: 10.1016/0360-3016(95)00059-8 7713775

25. Furukawa TA, Guyatt GH, Griffith LE. Can we individualize the number needed to treat? An empirical study of summary effect measures in meta-analyses. Int J Epidemiol. 2002;31: 72–76. doi: 10.1093/ije/31.1.72 11914297

26. Zintzaras E, Lau J. Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches. J Clin Epidemiol. 2008;61: 634–645. doi: 10.1016/j.jclinepi.2007.12.011 18538260

27. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327: 557–560. doi: 10.1136/bmj.327.7414.557 12958120

28. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315: 629–634. doi: 10.1136/bmj.315.7109.629 9310563

29. Brok J, Thorlund K, Gluud C, Wetterslev J. Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses. J Clin Epidemiol. 2008;61: 763–769. doi: 10.1016/j.jclinepi.2007.10.007 18411040

30. Thorlund K, Engstrøm J, Wetterslev J, Brok J, Imberger G, Gluud C. User manual for trial sequential analysis (TSA). Copenhagen Trial Unit, Centre for Clinical Intervention Research, Copenhagen, Denmark. 2011. pp. 1–115. Available from

31. Brok J, Thorlund K, Wetterslev J, Gluud C. Apparently conclusive meta-analyses may be inconclusive–Trial sequential analysis adjustment of random error risk due to repetitive testing of accumulating data in apparently conclusive neonatal meta-analyses. Int J Epidemiol. 2009;38: 287–298. doi: 10.1093/ije/dyn188 18824466

32. Edvardsen H, Tefre T, Jansen L, Vu P, Haffty BG, Fosså SD, et al. Linkage disequilibrium pattern of the ATM gene in breast cancer patients and controls; association of SNPs and haplotypes to radio-sensitivity and post-lumpectomy local recurrence. Radiat Oncol. 2007; 2: 25. doi: 10.1186/1748-717X-2-25 17623063

33. Zschenker O, Raabe A, Boeckelmann IK, Borstelmann S, Szymczak S, Wellek S, et al. Association of single nucleotide polymorphisms in ATM, GSTP1, SOD2, TGFB1, XPD and XRCC1 with clinical and cellular radiosensitivity. Radiother Oncol. 2010;97: 26–32. doi: 10.1016/j.radonc.2010.01.016 20170971

34. Andreassen CN, Rosenstein BS, Kerns SL, Ostrer H, De Ruysscher D, Cesaretti JA, et al. 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. Radiother Oncol. 2016;121: 431–439. doi: 10.1016/j.radonc.2016.06.017 27443449

35. Fachal L, Gómez-Caamaño A, Peleteiro P, Carballo A, Calvo-Crespo P, Sánchez-García M, et al. Association of a XRCC3 polymorphism and rectum mean dose with the risk of acute radio-induced gastrointestinal toxicity in prostate cancer patients. Radiother Oncol. 2012;105: 321–328. doi: 10.1016/j.radonc.2012.09.013 23075580

36. Cintra HS, Pinezi JC, Machado GD, de Carvalho GM, Carvalho AT, dos Santos TE, et al. Investigation of genetic polymorphisms related to the outcome of radiotherapy for prostate cancer patients. Dis Markers. 2013;35: 701–710. doi: 10.1155/2013/762685 24324286

37. Alsbeih G, El-Sebaie M, Al-Rajhi N, Al-Harbi N, Al-Hadyan K, Al-Qahtani S, et al. Among 45 variants in 11 genes, HDM2 promoter polymorphisms emerge as new candidate biomarker associated with radiation toxicity. 3Biotech. 2014;4: 137–148.

38. Gu Y, Shi J, Qiu S, Qiao Y, Zhang X, Cheng Y, et al. Association between ATM rs1801516 polymorphism and cancer susceptibility: a meta-analysis involving 12,879 cases and 18,054 controls. BMC Cancer. 2018;18: 1060. doi: 10.1186/s12885-018-4941-1 30384829

39. Berthel E, Foray N, Ferlazzo ML. The nucleoshuttling of the ATM protein: a unified model to describe the individual response to high- and low-dose of radiation? Cancers (Basel). 2019;11(7).

40. Pereira S, Bodgi L, Duclos M, Canet A, Ferlazzo ML, Devic C, et al. Fast and Binary Assay for Predicting Radiosensitivity Based on the Theory of ATM Nucleo-Shuttling: Development, Validation, and Performance. Int J Radiat Oncol Biol Phys. 2018;100: 353–360. doi: 10.1016/j.ijrobp.2017.10.029 29353653

41. Borghini A, Vecoli C, Mercuri A, Petruzzelli MF, D'Errico MP, Portaluri M, et al. Genetic risk score and acute skin toxicity after breast radiation therapy. Cancer Biother Radiopharm. 2014;29: 267–272. doi: 10.1089/cbr.2014.1620 25099761

42. Cargnin S, Viana M, Sances G, Cantello R, Tassorelli C, Terrazzino S. Using a Genetic Risk Score Approach to Predict Headache Response to Triptans in Migraine Without Aura. J Clin Pharmacol. 2019;59: 288–294. doi: 10.1002/jcph.1320 30256423

43. Terrazzino S, Deantonio L, Cargnin S, Donis L, Pisani C, Masini L, et al. DNA Methyltransferase Gene Polymorphisms for Prediction of Radiation-Induced Skin Fibrosis after Treatment of Breast Cancer: A Multifactorial Genetic Approach. Cancer Res Treat. 2017;49: 464–472. doi: 10.4143/crt.2016.256 27554481

Článek vyšel v časopise


2019 Číslo 11