Abstract

Accumulating evidence has revealed that dysregulated lncRNA expression contributes to the onset and progression of cancer. However, the mechanistic role of lncRNA in glioma progression and tumor immunology remains largely unknown. This study aimed to evaluate the significance of maternally expressed gene 3 (MEG3) in the prognosis of and its immune-related roles in gliomas. The expression levels of MEG3 were analyzed using Oncomine and TIMER database. As an important imprinted gene, the copy number variation (CNV) of MEG3 in both glioblastoma multiforme (GBM) and low-grade glioma (LGG) were analyzed using GSCALite database, whereas its prognostic significance was assessed using PrognoScan and GEPIA databases. The relationship between MEG3 and tumor-infiltrated immune cells was analyzed using TIMER. Results showed that MEG3 expression was lower in most of the human cancer tissues than in the normal tissues. We also found that heterozygous deletion of MEG3 occurred more frequent than heterozygous amplification in gliomas, and mRNA expression of MEG3 was significantly positively correlated with its CNV in both the GBM and LGG group. Survival analysis showed that the CNV level of MEG3 had significant correlation with overall survival (OS) and progression-free survival (PFS) compared with wild type in LGG. Lower MEG3 expression was related with poor prognosis. Further analysis showed that in GBM, MEG3 expression level was significantly positively correlated with that of infiltrating CD8+ T cells and significantly negatively correlated with that of infiltrating dendritic cells. In LGG, MEG3 expression level was significantly negatively correlated with levels of infiltrating B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. Univariate Cox survival analysis demonstrated that only the level of infiltrating dendritic cells significantly affected the survival time of patients with GBM, while all six types of immune cells had a significant effect on the survival time of patients with LGG. Furthermore, MEG3 expression showed strong correlations with multiple immune markers in gliomas, especially in LGG. The current findings suggest that MEG3 expression might serve as a possible prognostic marker and potential immunotherapeutic target for gliomas.

Highlights

  • Glioma is the most common primary malignant tumor of the brain

  • We evaluated the Maternally expressed gene 3 (MEG3) expression level through the Tumor Immune Estimation Resource (TIMER) database, finding that MEG3 expression was significantly lower in BLCA, BRCA, ESCA, glioblastoma multiforme (GBM), KICH, KIRP, PRAD, UCEC, than in normal controls

  • We further analyzed the expression of MEG3 in different grades of gliomas, finding that the expression level of MEG3 in grade 4 was significantly lower than that in other grades of gliomas and normal control, it decreased with the increasing of malignant degree of gliomas (Figure 1C)

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Summary

Introduction

Glioma is the most common primary malignant tumor of the brain. Despite many breakthrough analyses deciphering the underlying molecular mechanisms of gliomas, comprehensive treatment options are still lacking and the long-term survival rate of glioma patients remains poor. The molecular complexity and unique microenvironment in the brain that lead to therapeutic resistance, disease progression, and tumor recurrence add to the challenges of glioma treatment. Accumulating evidence has revealed that dysregulated lncRNA expression contributes to the development and metastasis of tumors (Pan et al, 2020). The mechanistic role of lncRNA in glioma progression and tumor immunology remains largely unknown. Expressed gene 3 (MEG3), known as gene-trap locus 2 (GTL2), is an imprinted gene. It is highly expressed in the brain, pituitary gland, placenta, and adrenal gland. The first evidences of the contribution of MEG3 in human cancers were obtained from pituitary non-functioning adenomas (Zhou et al, 2012). A recent meta-analysis has shown a correlation between MEG3 downregulation and poor patient outcomes (Binabaj et al, 2018)

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