中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Long non-coding RNA TP73-AS1 is a potential immune related prognostic biomarker for glioma

文献类型:期刊论文

作者Zhang, Bo2,3; Li, Qinglin3,5; Wu, Bin1,3,4; Zhang, Shuyuan1,3,4; Li, Liwen1,3,4; Jin, Kai1,3,4; Li, Sheng3,6; Li, Kai3,6; Wang, Zeng3,5; Lu, Yi2,3
刊名AGING-US
出版日期2021-02-28
卷号13
ISSN号1945-4589
关键词glioma TP73-AS1 immune prognostic biomarker
通讯作者Xia, Liang(xialiang@zjcc.org.cn) ; Sun, Caixing(2226124552@qq.com)
英文摘要Glioma is one of the most common primary brain tumors, and is divided into low-grade and high-grade gliomas. Long non-coding RNAs have been increasingly implicated in the pathogenesis and prognosis of glioma. Here, we demonstrated that the long non-coding RNA TP73-AS1 is differentially expressed among gliomas with different clinicopathological features in The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and GEO glioma datasets; high expression of TP73-AS1 was associated with poor clinical features, including age, stage, IDH mutation status, 1p/19q co-deletion status and overall survival. Measuring TP73-AS1 expression using real-time PCR showed the same result for 76 glioma tissue samples from our hospital. The infiltration levels of various immune cells in the tumor microenvironment were found to be significantly higher in patients with high expression of TP73-AS1. Taken together, our results suggest that TP73-AS1 has potential as a prognostic glioma biomarker. Moreover, the knowledge that TP73-AS1 affects the glioma immune microenvironment may provide new information for the immunological research and treatment of glioma.
WOS关键词RESISTANCE
资助项目National Natural Science Foundation of China[81502147] ; Zhejiang Medical Science and Technology Project[2017KY260] ; Zhejiang Medical Science and Technology Project[2018KY292] ; Zhejiang Medical Science and Technology Project[2019RC127] ; Zhejiang Medical Science and Technology Project[2018KY291] ; Zhejiang Provincial National Science Foundation of China[Y21H160038] ; Zhejiang Provincial National Science Foundation of China[LQ18H290002] ; Zhejiang Provincial National Science Foundation of China[LQ20H290001] ; Chinese Medicine Science and Technology Plan of Zhejiang Province[2016ZA039] ; Youth Scientific Innovation Foundation of Zhejiang Cancer Hospital[QN201402] ; Youth Scientific Innovation Foundation of Zhejiang Cancer Hospital[QN201902] ; third term new medical talents of Zhejiang province project
WOS研究方向Cell Biology ; Geriatrics & Gerontology
语种英语
出版者IMPACT JOURNALS LLC
WOS记录号WOS:000624599800009
资助机构National Natural Science Foundation of China ; Zhejiang Medical Science and Technology Project ; Zhejiang Provincial National Science Foundation of China ; Chinese Medicine Science and Technology Plan of Zhejiang Province ; Youth Scientific Innovation Foundation of Zhejiang Cancer Hospital ; third term new medical talents of Zhejiang province project
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/120887]  
专题中国科学院合肥物质科学研究院
通讯作者Xia, Liang; Sun, Caixing
作者单位1.Zhejiang Canc Hosp, Dept Neurosurg, Hangzhou 310022, Peoples R China
2.Zhejiang Canc Hosp, Dept Integrat Chinese & Western Med, Hangzhou 310022, Peoples R China
3.Chinese Acad Sci, Inst Canc & Basic Med, Hangzhou 310022, Peoples R China
4.Univ Chinese Acad Sci, Canc Hosp, Dept Neurosurg, Hangzhou 310022, Peoples R China
5.Zhejiang Canc Hosp, Sci Res Dept, Hangzhou 310022, Peoples R China
6.Zhejiang Canc Hosp, Dept Med Imaging, Hangzhou 310022, Peoples R China
7.Key Lab Head & Neck Canc Translat Res Zhejiang Pr, Hangzhou 310022, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Bo,Li, Qinglin,Wu, Bin,et al. Long non-coding RNA TP73-AS1 is a potential immune related prognostic biomarker for glioma[J]. AGING-US,2021,13.
APA Zhang, Bo.,Li, Qinglin.,Wu, Bin.,Zhang, Shuyuan.,Li, Liwen.,...&Sun, Caixing.(2021).Long non-coding RNA TP73-AS1 is a potential immune related prognostic biomarker for glioma.AGING-US,13.
MLA Zhang, Bo,et al."Long non-coding RNA TP73-AS1 is a potential immune related prognostic biomarker for glioma".AGING-US 13(2021).

入库方式: OAI收割

来源:合肥物质科学研究院

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