Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas

被引:8
|
作者
Yan, Derui [1 ,2 ]
Zhao, Qi [3 ]
Du, Zixuan [1 ,2 ]
Li, Huijun [1 ,2 ]
Geng, Ruirui [1 ,2 ]
Yang, Wei [4 ,5 ]
Zhang, Xinyan [6 ]
Cao, Jianping [4 ,5 ]
Yi, Nengjun [7 ]
Zhou, Juying [3 ]
Tang, Zaixiang [1 ,2 ]
机构
[1] Soochow Univ, Sch Publ Hlth, Dept Biostat, Med Coll, Suzhou 215123, Jiangsu, Peoples R China
[2] Soochow Univ, Jiangsu Key Lab Prevent & Translat Med Geriatr Di, Med Coll, Suzhou, Peoples R China
[3] Soochow Univ, Dept Radiat Oncol, Affiliated Hosp 1, Suzhou 215000, Jiangsu, Peoples R China
[4] Soochow Univ, Sch Radiat Med & Protect, Suzhou 215006, Peoples R China
[5] Soochow Univ, Collaborat Innovat Ctr Radiat Med Jiangsu Higher, Suzhou 215006, Peoples R China
[6] Kennesaw State Univ, Dept Biostat, Kennesaw, GA 30144 USA
[7] Univ Alabama Birmingham, Dept Biostat, Birmingham, AL 35294 USA
基金
中国国家自然科学基金;
关键词
TUMOR MICROENVIRONMENT; RADIATION ONCOLOGY; SURVIVAL; CLASSIFICATION; MODEL; ERA;
D O I
10.1038/s41598-022-10601-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
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页数:12
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