Dataset Information

Genome-Wide Identification and Analysis of the Methylation of lncRNAs and Prognostic Implications in the Glioma.

ABSTRACT: Glioma is characterized by rapid cell proliferation and extensive infiltration among brain tissues, but the molecular pathology has been still poorly understood. Previous studies found that DNA methylation modifications play a key role in contributing to the pathogenesis of glioma. On the other hand, long noncoding RNAs (lncRNAs) has been discovered to be associated with some key tumorigenic processes of glioma. Moreover, genomic methylation can influence expression and functions of lncRNAs, which contributes to the pathogenesis of many complex diseases. However, to date, no systematic study has been performed to detect the methylation of lncRNAs and its influences in glioma on a genome-wide scale. Here, we selected the methylation data, clinical information, expression of lncRNAs, and DNA methylation regulatory proteins of 537 glioma patients from TCGA and TANRIC databases. Then, we performed a differential analysis of lncRNA expression and methylated regions between low-grade glioma (LGG) and glioblastoma multiform (GBM) subjects, respectively. Next, we further identified and verified potential key lncRNAs contributing the pathogenesis of glioma involved in methylation modifications by an annotation and correlation analysis, respectively. In total, 18 such lncRNAs were identified, and 7 of them have been demonstrated to be functionally linked to the pathogenesis of glioma by previous studies. Finally, by the univariate Cox regression, LASSO regression, clinical correlation, and survival analysis, we found that all these 18 lncRNAs are high-risk factors for clinical prognosis of glioma. In summary, this study provided a strategy to explore the influence of lncRNA methylation on glioma, and our findings will be benefit to improve understanding of its pathogenesis.

SUBMITTER: He Y

PROVIDER: S-EPMC7820673 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Genome-Wide Identification and Analysis of the Methylation of lncRNAs and Prognostic Implications in the Glioma.

He Yijie Y Wang Lidan L Tang Jing J Han Zhijie Z

Frontiers in oncology 20210108

Glioma is characterized by rapid cell proliferation and extensive infiltration among brain tissues, but the molecular pathology has been still poorly understood. Previous studies found that DNA methylation modifications play a key role in contributing to the pathogenesis of glioma. On the other hand, long noncoding RNAs (lncRNAs) has been discovered to be associated with some key tumorigenic processes of glioma. Moreover, genomic methylation can influence expression and functions of lncRNAs, whi ...[more]

PMID: 33489915

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Project description:Previous studies have shown that the prognosis of patients with lower-grade glioma (LGG) is closely related to the infiltration of immune cells and the expression of long non-coding RNAs (lncRNAs). In this paper, we applied single-sample gene set enrichment analysis (ssGSEA) algorithm to evaluate the expression level of immune genes from tumor tissues in The Cancer Genome Atlas (TCGA) database, and divided patients into the high immune group and the low immune group, which were separately analyzed for differential expression. Venn analysis was taken to select 36 immune-related lncRNAs. To construct a prognostic model of LGG based on immune-related lncRNAs, we divided patients into a training set and a verification set at a ratio of 2:1. Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to select 11 immune-related lncRNAs associated with the prognosis of LGG, and based on these selected lncRNAs, the risk scoring model was constructed. Through Kaplan-Meier analysis, the overall survival (OS) of patients in the high-risk group was significantly lower than that of the low-risk group. Then, established a nomogram including age, gender, neoplasm histologic grade, and risk score. Meanwhile, the predictive performance of the model was evaluated by calculating the C-index, drawing the calibration chart, the clinical decision curve as well as the Receiver Operating Characteristic (ROC) curve. Similar results were obtained by utilizing the validation data to verify the above consequences. Based on the TIMER database, the correlation analysis showed that the 11 immune-related lncRNAs risk score of LGG were in connection with the infiltration of the subtypes of immune cells. Subsequently, we performed enrichment analysis, whose results showed that these immune-related lncRNAs played important roles in the progress of LGG. In conclusion, these 11 immune-related lncRNAs have the potential to predict the prognosis of patients with LGG, which may play a key role in the development of LGG.

Dataset Information

Genome-Wide Identification and Analysis of the Methylation of lncRNAs and Prognostic Implications in the Glioma.

Publications

Genome-Wide Identification and Analysis of the Methylation of lncRNAs and Prognostic Implications in the Glioma.

Similar Datasets

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