Research Article Low GAS5 Levels As a Predictor of Poor Survival in Patients with Lower-Grade Gliomas

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Research Article Low GAS5 Levels As a Predictor of Poor Survival in Patients with Lower-Grade Gliomas Hindawi Journal of Oncology Volume 2019, Article ID 1785042, 15 pages https://doi.org/10.1155/2019/1785042 Research Article Low GAS5 Levels as a Predictor of Poor Survival in Patients with Lower-Grade Gliomas Yanfang Wang ,1 Shan Xin,1 Kai Zhang,2 Run Shi ,1 and Xuanwen Bao 3,4 1 Ludwig-Maximilians-Universitat¨ Munchen¨ (LMU), 80539 Munich, Germany 2Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 310016 Hangzhou, China 3Institute of Radiation Biology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany 4Technical University Munich (TUM), 80333 Munich, Germany Correspondence should be addressed to Run Shi; [email protected] and Xuanwen Bao; [email protected] Received 1 October 2018; Revised 18 December 2018; Accepted 3 January 2019; Published 3 February 2019 Academic Editor: Srikumar P. Chellappan Copyright © 2019 Yanfang Wang et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. Gliomas are infltrative neoplasms of a highly invasive nature. Diferent stages of gliomas feature distinct genomic, genetic, and epigenetic changes. Te long noncoding RNA Growth Arrest Specifc Transcript 5 (GAS5) is an identifed tumour suppressor involved in several cancers. However, the underlying roles of the GAS5 gene in lower-grade glioma (LGG) patients are not clear. Methods. Via bioinformatic analysis based on TCGA-LGG and TCGA-GBM data, we explored the mechanisms of GAS5 expression in LGG (grades II and III) and high-grade glioma (glioblastoma multiforme, grade IV). Te log-rank test and multivariate Cox analysis were performed to fnd the association between GAS5 and overall survival (OS) in LGG patients. Weighted gene coexpression network analysis (WGCNA) and RNA-Seq analysis were applied to fnd the key gene network associated with GAS5. Results. We found that GAS5 expression was downregulated in both LGG and glioblastoma multiforme (GBM) compared with normal brain tissue. Low methylation in the GAS5 promoter region was detected in both LGG and GBM tissues. Te amplifcation type was the predominant type of GAS5 gene alteration in both LGG and GBM. High GAS5 expression was more associated with long overall survival (OS) in LGG patients than in GBM patients. Te multivariate survival analysis of GAS5 and clinical and molecular characteristics in LGG patients further confrmed the association between GAS5 and OS in LGG patients. We then developed a nomogram for clinical use. WGCNA and RNA-Seq analysis indicated that ribosomal biogenesis and translation initiation were the predominant events regulated by GAS5 in LGG patients. Conclusion. Taken together, these results demonstrate that GAS5 expression is associated with OS in LGG patients and that its underlying roles involve the regulation of ribosomal biogenesis and translation initiation, which may aid in identifying a new target for the treatment of LGG. 1. Introduction children with central nervous system (CNS) neoplasms, and no efective therapies currently exist [5]. In most cases, Gliomas are commonly classifed as low-grade glioma (LGG, GBM will recur afer surgical resection, resulting in a poor grades II and III) or glioblastoma multiforme (GBM, grade prognosis. Hundreds of molecular alterations exist in LGG IV). LGGs are infltrative neoplasms that arise most ofen and GBM, making them react diferently to chemotherapy, in the cerebral hemispheres of adults, including oligoden- radiotherapy, and surgical resection. Identifying the key drogliomas, oligoastrocytomas, and astrocytomas [1]. A sub- genes or genome alterations that drive the progression of set of LGGs progress into GBM within a few months, and gliomas will contribute to the understanding of the molecular others may stay stable for several years, causing large varia- mechanism behind gliomas and help to improve the efects of tions in median survival [2, 3]. Hence, individual treatments therapy. should be performed based on the identifcation of histologic Long noncoding RNAs (lncRNAs) are non-protein- class, grade, and reactions to chemotherapy and radiotherapy coding transcripts that play essential roles in cellular regu- [4]. GBM is the most common cause of death among lation at various levels and in diverse biological functions, 2 Journal of Oncology including chromatin modifcation, transcriptional regula- Te salmon and blue modules, which had most signifcant tion, cell diferentiation, immune responses, and epigenetic adjusted p-values, were selected. Genes involved in the regulation [6–8]. GAS5 produces a spliced lncRNA, which salmon and blue modules and their weights as calculated by sensitizes cells to apoptosis by suppressing glucocorticoid- WGCNA were visualized by Cytoscape 3.4.0 [21]. GO analysis mediated induction of several responsive genes [9]. By was performed using the clusterProfler package [22] and binding to the DNA-binding domain of the glucocorticoid Metascape (http://metascape.org/gp/index.html) [23]. Gene receptor, GAS5 acts as a decoy glucocorticoid response ele- set enrichment analysis (GSEA) was applied by the GSEA ment (GRE), thus competing with DNA GREs to bind to the sofware from Broad Institute [24]. glucocorticoid receptor [9]. By analysing GAS5 level and clin- ical parameters, it has been found that GAS5 correlates with 2.3. Statistical Analysis. Statistical analysis was performed tumour progression and poor prognosis in many tumour using R (R: A language and environment for statistical types [10–13]. Some publications have also indicated that computing. R Foundation for Statistical Computing, Vienna, GAS5 is a predictor of survival in GBM patients [14, 15]. One Austria. URL http://www.R-project.org/). Te association study revealed an association between serum GAS5 level and between GAS5 expression and the clinicopathological fea- the OS of GBM patients [14]. However, the potential roles of tures was evaluated by the diferent mathematical methods GAS5 involvement in gliomas and the regulatory mechanism listed in the table [25]. Te log-rank test was performed to of GAS5 expression in gliomas are not clearly identifed. assess the diference between the Kaplan-Meier curves. Te Besides, the diference of GAS5 expression and the regulatory fold change and Q value for samples with high and low GAS5 mechanism of GAS5 expression in LGG and GBM patients expression were calculated using the limma package [26]. A have not been shown yet. In this study, via bioinformatic Qvalue< 0.05 was considered statistically signifcant. analysis, we explored the regulatory mechanisms of GAS5 expression in gliomas and compared its prognostic value in 3. Results LGG and GBM. In addition, based on TCGA-LGG RNA-Seq datasets, we also applied WGCNA and enrichment analysis 3.1. GAS5 Was Upregulated in Both LGG and GBM Compared to identify the pathways highly associated with GAS5 in LGG with Normal Brain Tissues. GAS5 expression levels were and the network of genes highly associated with GAS5. characterized in several types of solid tumours, including LGG and GBM (Figure 1). Te results indicated that GAS5 2. Materials and Methods was downregulated in both LGG and GBM tissue com- pared with the normal brain tissue. Ten, we compared the 2.1. Clinical and Omic Data Download. RNA-Seq and DNA expression level of GAS5 between LGG and GBM (Figures methylation datasets from patients with primary LGG or 2(a), 2(b), and S1a). No signifcant diference was identifed GBM were downloaded from the UCSC Xena browser between the LGG and GBM datasets. In addition, grade II, (https://xenabrowser.net/) [16]. GAS5 mRNA expressions grade III, and grade IV gliomas had similar expression levels in diferent types of solid tumours and in corresponding of GAS5, which were all higher than that of normal brain normal tissues were obtained from TCGA datasets and GTEx tissues. Te DNA methylation level of GAS5 was analysed datasets [17]. A box plot was created using ggplot2 [18]. by DNA methylation 450K chips, and the six probes were chosen from the CpG island in the promoter region of GAS5. All probes showed low � values (<0.1), and there 2.2. WGCNA of RNA-Seq Data from LGG Patients and � Network Visualization. Te WGCNA R package was used were no diferences in values from any of the six probes to evaluate the correlation of GAS5 expression and module between LGG and GBM tissues, indicating low methylation membership by the ‘p.weighted’ function [19]. An adjacency of the GAS5 promoter in both LGG and GBM patients matrix was generated to evaluate the weighted coexpression (Figure 2(c)). Te association between GAS5 methylation values between all the subjects in the probe set. Te coex- and GAS5 expression was tested, revealing no signifcant relationship in either GBM or LGG tissues (Figures S1B and pression similarity ��,� wasdefnedastheabsolutevalueofthe correlation coefcient between the profles of nodes � and �: S1C). Ten, to investigate the driver of high GAS5 expression in LGG and GBM tissues, we also examined copy number � � � � alterations (CNAs) in LGG and GBM (Figures 2(d) and 2(e)). ��,� = ���� (��,��)� (1) Te results showed that the amplifcation-type alteration where �� and �� were expression value of for genes � and � and contributed to the high expression of GAS5 in both LGG and ��,� represented Pearson’s correlation coefcient of gene � and GBM tissues (P = 0.044 and P = 0.047). gene �. A weighed network adjacency was defned by raising the 3.2.LowGAS5ExpressionWasaPredictorofPoorSurvival coexpression similarity to a power �: in LGG. Te associations between GAS5 expression and the pathological parameters of patients with primary LGG and � ��,� =��,� (2) GBM were summarized in Table 1. In patients with LGG, higher GAS5 expression was signifcantly correlated with with �≥1[20]. We selected the power of � =4and higher tumour purity (Table 1 and Figure S2). Nevertheless, 2 scale free R = 0.95 as the sof-thresholding parameter we could not fnd a similar tendency in patients with GBM. to ensure a signed scale-free coexpression gene network.
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