Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas.
Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas.
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用于预测低级别胶质瘤放射敏感性的免疫相关基因特征的开发和验证
DOI：
10.1038/s41598-022-10601-5
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发表时间：
2022-04-23
影响因子：
4.6
通讯作者：
Tang, Zaixiang
中科院分区：
文献类型：
--
作者：
Yan, Derui;Zhao, Qi;Du, Zixuan;Li, Huijun;Geng, Ruirui;Yang, Wei;Zhang, Xinyan;Cao, Jianping;Yi, Nengjun;Zhou, Juying;Tang, Zaixiang
放射治疗是低级别胶质瘤（LGG）患者的重要治疗方式。进行该分析的目的是开发免疫相关的放射敏感性基因特征，以预测接受放射治疗的 LGG 患者的生存率。 LGGs的临床和RNA测序数据来自癌症基因组图谱（TCGA）和中国胶质瘤基因组图谱（CGGA）。 Lasso 回归分析用于构建 21 个基因特征，以确定可以从放射治疗中受益的 LGG 患者。根据这种放射敏感性特征，患者被分为放射敏感性（RS）组和放射抗性（RR）组。根据TCGA数据集和两个CGGA验证数据集的Kaplan-Meier分析结果，RS组的总体生存率高于RR组。该基因特征是 RT 特异性的，并且是一个独立的预后指标。通过该基因特征和其他临床因素（年龄、性别、级别、IDH 突变、1p/19q 编码缺失），列线图模型在预测 LGG 患者放疗后 3 年和 5 年生存方面表现良好。总之，这一特征是对放疗 LGG 患者预后因素的有力补充，并可能提供将个体肿瘤生物学纳入放射肿瘤学临床决策的机会。
Radiotherapy is an important treatment modality for lower-grade gliomas (LGGs) patients. This analysis was conducted to develop an immune-related radiosensitivity gene signature to predict the survival of LGGs patients who received radiotherapy. The clinical and RNA sequencing data of LGGs were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Lasso regression analyses were used to construct a 21-gene signature to identify the LGGs patients who could benefit from radiotherapy. Based on this radiosensitivity signature, patients were classified into a radiosensitive (RS) group and a radioresistant (RR) group. According to the Kaplan–Meier analysis results of the TCGA dataset and the two CGGA validation datasets, the RS group had a higher overall survival rate than that of the RR group. This gene signature was RT-specific and an independent prognostic indicator. The nomogram model performed well in predicting 3-, and 5-year survival of LGGs patients after radiotherapy by this gene signature and other clinical factors (age, sex, grade, IDH mutations, 1p/19q codeletion). In summary, this signature is a powerful supplement to the prognostic factors of LGGs patients with radiotherapy and may provide an opportunity to incorporate individual tumor biology into clinical decision making in radiation oncology.
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影响因子：
1.7
作者：
Orth M;Lauber K;Niyazi M;Friedl AA;Li M;Maihöfer C;Schüttrumpf L;Ernst A;Niemöller OM;Belka C
通讯作者：
Belka C
放射组学特征作为低级别神经胶质瘤患者无进展生存的非侵入性预测因子。
DOI：
10.1016/j.nicl.2018.10.014
发表时间：
2018
期刊：
NeuroImage. Clinical
影响因子：
--
作者：
Liu X;Li Y;Qian Z;Sun Z;Xu K;Wang K;Liu S;Fan X;Li S;Zhang Z;Jiang T;Wang Y
通讯作者：
Wang Y
基于肿瘤免疫微环境探索鉴定上皮性卵巢癌的预后特征
影响因子：
4.4
作者：
Liu, Jinhui;Meng, Huangyang;Cheng, Wenjun
通讯作者：
Cheng, Wenjun
影响因子：
11.5
作者：
Eschrich, Steven A.;Fulp, William J.;Torres-Roca, Javier F.
通讯作者：
Torres-Roca, Javier F.
DOI：
10.1158/1078-0432.ccr-18-0825
发表时间：
2018-10-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Cui Y;Li B;Pollom EL;Horst KC;Li R
通讯作者：
Li R