Glioma genetic profiles associated with electrophysiologic hyperexcitability.
Glioma genetic profiles associated with electrophysiologic hyperexcitability.
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神经胶质瘤遗传特征与电生理过度兴奋相关。
DOI：
10.1101/2023.02.22.23285841
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Lee,JongWoo
中科院分区：
文献类型：
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作者：
Tobochnik,Steven;Dorotan,MariaKristinaC;Ghosh,HiaS;Lapinskas,Emily;Vogelzang,Jayne;Reardon,DavidA;Ligon,KeithL;Bi,WenyaLinda;Smirnakis,SteliosM;Lee,JongWoo
背景不同的基因改变决定了胶质瘤的侵袭性，然而，体细胞突变的多样性在整个疾病过程中导致瘤周过度兴奋和癫痫发作尚不确定。本研究旨在确定肿瘤体细胞突变谱与临床显着hyperexcitation.MethodsA单中心队列的成人WHO等级1-4胶质瘤和有针对性的外显子组测序（n= 1716）进行了分析和交叉引用与验证的EEG数据库，以确定谁进行连续EEG监测（n= 206）的个人的子集。 过度兴奋定义为存在偏侧周期性放电和/或电描记癫痫发作。交叉验证的判别分析模型专门训练的经常性体细胞突变被用来识别与hyperexcitation.ResultsThe分布的WHO等级和肿瘤突变的负担与hyperexcitability患者和不hyperexcitability之间的变异。判别分析模型分类的存在或不存在的EEG超兴奋性的总体准确率为70.9%，无论IDH 1 R132 H的列入。预测性变异包括ATRX和TP 53的无义突变，RBBP 8和CREBBP的indel突变，以及EGFR、KRAS、PIK 3CA、TP 53和USP 28中具有预测损害后果的非同义错义突变。在控制年龄、性别、肿瘤位置、综合病理诊断、复发状态和术前癫痫的多变量分析中，该特征改善了对过度兴奋的估计。预测的体细胞突变的变体是过度兴奋的患者相比，没有hyperexcitability和那些谁没有经历连续EEG.ConclusionThese研究结果牵连不同的胶质瘤体细胞突变的癌基因与瘤周hyperexcitability。肿瘤遗传学分析可能有助于胶质瘤相关癫痫的诊断和治疗。
BackgroundDistinct genetic alterations determine glioma aggressiveness, however, the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures over the course of the disease is uncertain. This study aimed to identify tumor somatic mutation profiles associated with clinically significant hyperexcitability.MethodsA single center cohort of adults with WHO grades 1–4 glioma and targeted exome sequencing (n= 1716) was analyzed and cross-referenced with a validated EEG database to identify the subset of individuals who underwent continuous EEG monitoring (n= 206). Hyperexcitability was defined by the presence of lateralized periodic discharges and/or electrographic seizures. Cross-validated discriminant analysis models trained exclusively on recurrent somatic mutations were used to identify variants associated with hyperexcitability.ResultsThe distribution of WHO grades and tumor mutational burdens were similar between patients with and without hyperexcitability. Discriminant analysis models classified the presence or absence of EEG hyperexcitability with an overall accuracy of 70.9%, regardless ofIDH1 R132Hinclusion. Predictive variants included nonsense mutations inATRXandTP53, indel mutations inRBBP8andCREBBP, and nonsynonymous missense mutations with predicted damaging consequences inEGFR,KRAS,PIK3CA,TP53, andUSP28. This profile improved estimates of hyperexcitability in a multivariate analysis controlling for age, sex, tumor location, integrated pathologic diagnosis, recurrence status, and preoperative epilepsy. Predicted somatic mutation variants were over-represented in patients with hyperexcitability compared to individuals without hyperexcitability and those who did not undergo continuous EEG.ConclusionThese findings implicate diverse glioma somatic mutations in cancer genes associated with peritumoral hyperexcitability. Tumor genetic profiling may facilitate glioma-related epilepsy prognostication and management.