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分析神经前体细胞向间充质细胞的转变可确定胶质瘤中的一个长链非编码RNA特征。

Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma.

作者信息

Liang Qingyu, Guan Gefei, Li Xue, Wei Chunmi, Wu Jianqi, Cheng Peng, Wu Anhua, Cheng Wen

机构信息

Department of Neurosurgery, The First Hospital of China Medical University, Nanjing Street 155, Heping District, Shenyang, 110001, Liaoning, China.

Department of Radiotherapy, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi, China.

出版信息

J Transl Med. 2020 Oct 7;18(1):378. doi: 10.1186/s12967-020-02552-0.

Abstract

BACKGROUND

Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated.

METHODS

Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed.

RESULTS

According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma.

CONCLUSIONS

We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

摘要

背景

分子分类为探索胶质瘤生物学和治疗策略奠定了框架。已知胶质瘤的神经前体细胞向间充质细胞转变(PMT)与侵袭性表型、不良预后和治疗抵抗相关。最近的研究强调,长链非编码RNA(lncRNA)是癌症间充质细胞转变的关键调节因子。然而,lncRNA与胶质瘤中PMT之间的关系尚未得到系统研究。

方法

使用来自癌症基因组图谱(TCGA)、中国胶质瘤基因组图谱(CGGA)、GSE16011和Rembrandt且带有可用临床和基因组信息的基因表达谱进行分析。进行了加权基因共表达网络分析(WGCNA)、基因集富集分析(GSEA)、Cox分析和最小绝对收缩和选择算子(LASSO)分析等生物信息学方法。

结果

根据PMT评分,我们证实PMT状态与胶质瘤的危险行为和不良预后呈正相关。通过WGCNA分析鉴定出149个与PMT相关的lncRNA,其中进一步筛选出10个(LINC01057、TP73-AS1、AP000695.4、LINC01503、CRNDE、OSMR-AS1、SNHG18、AC145343.2、RP11-25K21.6、RP11-38L15.2)具有显著预后价值的lncRNA,以构建与PMT相关的lncRNA风险特征,该特征可将病例分为两组,预后不同。多变量Cox回归分析表明,该特征是高级别胶质瘤的独立预后因素。高风险病例更有可能被归类为间充质亚型,通过招募巨噬细胞、中性粒细胞和调节性T细胞赋予增强的免疫抑制状态。此外,该特征中的6个lncRNA可作为竞争性内源RNA促进胶质母细胞瘤中的PMT。

结论

我们分析了胶质瘤中的PMT状态,并建立了一种与PMT相关的、可独立预测胶质瘤生存并触发PMT(从而增强免疫抑制)的10-lncRNA特征用于胶质瘤。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a10b/7539462/50ea893ef393/12967_2020_2552_Fig1_HTML.jpg

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