Downregulation of Brain Enriched Type 2 MAGEs Is Associated With Immune Infiltration and Poor Prognosis in Glioma

Abstract

Melanoma associated antigen (MAGE) is an extensively studied family of tumor-associated genes that share a common MAGE homology domain (MHD). Based upon their expression pattern, MAGE genes have been broadly classified into type 1 MAGEs (T1Ms) and type 2 MAGEs (T2Ms) categories. Interestingly, several T2Ms are highly expressed in the brain and involved in the regulation of neuronal development, differentiation, and survival. Available literature suggests possible tumor suppressor functions of a few T2Ms, while information available about their expression, regulation, and clinical significance in glioma is scanty. This prompted us to perform a comprehensive analysis of T2M expression in glioma. Gene expression data from glioma datasets: Oncomine, TCGA, and REMBRANDT study, were used to assess the mRNA expression of T2M genes (MAGED1, MAGED2, MAGED3, MAGED4, MAGED4B, MAGEE1, MAGEE2, MAGEF1, MAGEH1, MAGEL2, NSMCE3, and NDN), and their association with clinical characteristics and composition of the tumor microenvironment. Further, mutation, copy number alteration, and DNA methylation data from TCGA were assessed for determining potential mechanisms of T2Ms expression in glioma. Expression analysis revealed overexpression of MAGED subfamily genes in glioma, while other genes of this family exhibited reduced expression in advanced grades of this malignancy. Further, the expression of T2Ms exhibited varying extent of positive correlations with each other. Amongst downregulated T2Ms, MAGEH1 expression exhibited negative correlations with DNA methylation. Additionally, genes associated with MAGEH1 were enriched in Myc and Hedgehog signaling. Furthermore, T2Ms downregulation was associated with immune infiltration in glioma tissues and poor overall survival of glioma patients. In multivariate Cox regression analysis, MAGEH1 emerged as an independent prognosticator in lower grade glioma. Conclusively, these results suggest that expression of T2Ms is associated with important clinical and molecular features in glioma. Mechanistic studies may further provide novel insights into their role in glioma progression.

Keywords: DNA methylation; The Cancer Genome Atlas (TCGA); epigenetics; glioblastoma; glioma; melanoma associated antigen.

Figure 1

Type 2 MAGE expression in glioma. (A) Outline of the current study. (B) Oncomine analysis showing the general pattern of overexpression (red color)/downregulation (blue color) of T2Ms in cancer vs. normal tissues in different cancers. (C) Correlation matrix of T2Ms in a combined group of TCGA lower grade glioma and glioblastoma dataset. The distribution of variables is shown in left while Pearson correlation coefficients along with the level of significance have been shown on right. (***p<0.001; **p<0.01; *p<0.05).

Figure 2

MAGEH1 gene expression in glioma datasets, Rembrandt (left) and TCGA-LGG-GBM dataset (right) for (A, B) Different glioma grades, (C, D) Histological subtypes of LGG with GBM, (E, F) Molecular subtypes of GBM, (G) G-CIMP status in Rembrandt dataset, (H) IDH and 1p19q codeletion status in TCGA dataset. ****p<0.0001, ***p<0.001; **p<0.01; *p<0.05; ns, not significant.

Figure 3

Genetic regulation of T2Ms expression in glioma. (A) Mutation and copy number alteration profile of glioma patients from TCGA dataset. (B, C) Association of copy number alterations and expression of MAGEH1 and MAGEE1 in TCGA-GBM dataset. (D, E) Association of copy number alteration and expression of MAGEH1 and MAGEE1 in TCGA-LGG dataset. ***p<0.001; results with p>0.05 have not been indicated.

Figure 4

DNA methylation and its correlation with MAGEH1 expression (A) DNA methylation of the MAGEH1 promoter region in TCGA-LGG dataset (B) Correlation of DNA methylation at cg22604777 and cg22574818 with MAGEH1 expression in TCGA-LGG dataset. (C) Effect of 5-Azacytidine treatment on MAGEH1 expression in GBM cell line U87MG and LN229. ***p<0.001; **p<0.01; *p<0.05. Faded correlation values shows non significant associations.

Figure 5

Kaplan Meier survival analysis in REMBRANDT dataset (Left panel) and TCGA dataset (right panel) for selected type 2 MAGE genes including all cases. (A, B) MAGEH1 (C, D) TRO (E, F) MAGEE1 (G, H) MAGEL2 (I, J) NDN. Patients were divided into two groups based on maximally selected rank statistics function available in the GlioVis web server (see Materials and Methods for detail). The Log-rank p-value has been depicted in each graph. ***p<0.001; **p<0.01; *p<0.05.

Figure 6

Kaplan Meier survival analysis for MAGEH1 in different histological subtypes of lower grade glioma from Rembrandt and TCGA dataset (A, B) Astrocytoma (C, D) oligodendroglioma (E, F) mixed glioma. Patients were divided into two groups based on maximally selected rank statistics function available in the GlioVis web server (see Materials and Methods for detail). The Log-rank p-value has been depicted in each graph. ***p<0.001; **p<0.01; *p<0.05.

Figure 7

Kaplan Meier survival analysis for MAGEH1 in Rembrandt and TCGA dataset (A) GBM tissues from REMBRANDT (B) GBM tissues from TCGA (C) IDH wild type from TCGA dataset (D) IDH mutant type from TCGA dataset. Patients were divided into two groups based on maximally selected rank statistics function available in the GlioVis web server (see Materials and Methods for detail). The Log-rank p-value has been depicted in each graph. ***p<0.001; **p<0.01; *p<0.05.

Figure 8

Gene set enrichment analysis for MAGEH1 associations in lower grade glioma from TCGA dataset. (A–C) positively associated pathways, (D–L) negatively associated pathways. NES, normalized enrichment score; FDR q, false detection rate corrected p value.

Figure 9

Association of T2M expression with immune infiltration in glioma. TIMER analysis for Type 2 MAGE genes in TCGA-LGG and TCGA-GBM dataset. Analysis outputs for (A) MAGEH1 (B) MAGEE1 (C) MAGEL2 (D) TRO (E) NDN.