Identification of Immune-Related lncRNA Prognostic Signature and Molecular Subtypes for Glioblastoma

被引:31
|
作者
Yu, Wanli [1 ,2 ]
Ma, Yanan [3 ]
Hou, Wenbin [4 ]
Wang, Fang [5 ]
Cheng, Wan [6 ]
Qiu, Feng [7 ]
Wu, Pengfei [8 ,9 ,10 ,11 ]
Zhang, Guohua [12 ]
机构
[1] Nanchang Univ, Dept Neurosurg, Gaoxin Hosp, Affiliated Hosp 1, Nanchang, Jiangxi, Peoples R China
[2] Nanchang Univ, Dept Neurosurg, Affiliated Hosp 1, Nanchang, Jiangxi, Peoples R China
[3] Harbin Med Univ, Lab Med Genet, Harbin, Peoples R China
[4] Harbin Med Univ, Dept Urol, Affiliated Hosp 2, Harbin, Peoples R China
[5] Harbin Med Univ, Dept Neurosurg, Affiliated Hosp 2, Harbin, Peoples R China
[6] Nanjing Med Univ, Lab Artificial Intelligence & Bigdata Ophthalmol, Affiliated Eye Hosp, Nanjing, Peoples R China
[7] Nanchang Univ, Onal Dept, Gaoxin Hosp, Affiliated Hosp 1, Nanchang, Jiangxi, Peoples R China
[8] Univ Sci & Technol China, Affiliated Hosp USTC 1, Dept Neurosurg, Div Life Sci & Med, Hefei, Peoples R China
[9] Anhui Prov Stereotact Neurosurg Inst, Hefei, Peoples R China
[10] Anhui Prov Key Lab Brain Funct & Brain Dis, Hefei, Peoples R China
[11] Anhui Prov Clin Res Ctr Neurosurg Dis, Hefei, Peoples R China
[12] Nanchang Univ, Cent Lab, Gaoxin Hosp, Affiliated Hosp 1, Nanchang, Jiangxi, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2021年 / 12卷
关键词
glioblastoma; immune-related lncRNAs; biomarker; prognostic signature; immune infiltration; LONG NONCODING RNA; CANCER; CELLS; GENE; TRANSCRIPTION; MECHANISMS;
D O I
10.3389/fimmu.2021.706936
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: Glioblastoma multiforme (GBM) is extensively genetically and transcriptionally heterogeneous, which poses challenges for classification and management. Long noncoding RNAs (lncRNAs) play a critical role in the development and progression of GBM, especially in tumor-associated immune processes. Therefore, it is necessary to develop an immune-related lncRNAs (irlncRNAs) signature. Methods: Univariate and multivariate Cox regression analyses were utilized to construct a prognostic model. GBM-specific CeRNA and PPI network was constructed to predict lncRNAs targets and evaluate the interactions of immune mRNAs translated proteins. GO and KEGG pathway analyses were used to show the biological functions and pathways of CeRNA network-related immunity genes. Consensus Cluster Plus analysis was used for GBM gene clustering. Then, we evaluated GBM subtype-specific prognostic values, clinical characteristics, genes and pathways, immune infiltration access single cell RNA-seq data, and chemotherapeutics efficacy. The hub genes were finally validated. Results: A total of 17 prognostically related irlncRNAs were screened to build a prognostic model signature based on six key irlncRNAs. Based on GBM-specific CeRNAs and enrichment analysis, PLAU was predicted as a target of lncRNA-H19 and mainly enriched in the malignant related pathways. GBM subtype-A displayed the most favorable prognosis, high proportion of genes (IDH1, ATRX, and EGFR) mutation, chemoradiotherapy, and low risk and was characterized by low expression of four high-risk lncRNAs (H19, HOTAIRM1, AGAP2-AS1, and AC002456.1) and one mRNA KRT8. GSs with poor survival were mainly infiltrated by mesenchymal stem cells (MSCs) and astrocyte, and were more sensitive to gefitinib and roscovitine. Among GSs, three hub genes KRT8, NGFR, and TCEA3, were screened and validated to potentially play feasible oncogenic roles in GBM. Conclusion: Construction of lncRNAs risk model and identification of GBM subtypes based on 17 irlncRNAs, which suggesting that irlncRNAs had the promising potential for clinical immunotherapy of GBM.
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页数:15
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