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Background  To identify the association between somatic ataxia-telangiectasia mutated ( ATM ) mutations and improved radio-sensitivity, we retrospectively reviewed next-generation sequencing data from patients diagnosed with isocitrate dehydrogenase (IDH)-wildtype high-grade glioma.    Methods  We included 39 individuals with (IDH)-wildtype high-grade glioma (diffuse astrocytoma  n  = 2, anaplastic astrocytoma  n  = 10, and glioblastoma  n  = 27) not subjected to gross tumor resection and undergoing radiation therapy with a median total dose of 60 Gy in 30 fractions. The mutational status of the  ATM  gene was obtained through next-generation sequencing using a TruSight Tumor 170 cancer panel. Disease progression was defined according to the Response Assessment in Neuro-Oncology (RANO) criteria as well as neurologic and clinical findings.    Results  Among the 39 samples,  ATM  mutations ( ATM  mut(+)) were detected in 26% of cases ( n  = 10). No significant differences were observed in the characteristics of the patients or tumors. Among the 10 patients in the  ATM  mut(+) group, there were 6 patients with glioblastoma and 4 patients with anaplastic astrocytoma. Most mutations were missense mutations ( n  = 8, 80%). With a median follow-up of 16.5 mo (interquartile range, 11.4–19.8),  ATM  mut(+) exhibited 1-year in-field control of 100% compared with 44.1% in the  ATM  mut(−) group ( p  = 0.002). There was no difference in the out-field control rate or overall survival between the two groups ( p  = 0.861 and  p  = 0.247, respectively).    Conclusions  Our results demonstrated that  ATM  mutations might be involved in the increased radio-sensitivity with excellent in-field control despite the aggressive nature of IDH-wildtype high-grade glioma. Further studies are necessary to uncover the potential role of  ATM  as a biomarker and candidate therapeutic target in high-grade gliomas.

radiation oncology

ATM mutations improve radio-sensitivity in wild-type isocitrate dehydrogenase-associated high-grade glioma: retrospective analysis using next-generation sequencing data