Nucleotide-Binding Oligomerization Domain (NOD)-Like Receptor Subfamily C (NLRC) as a Prognostic Biomarker for Glioblastoma Multiforme Linked to Tumor Microenvironment: A Bioinformatics, Immunohistochemistry, and Machine Learning-Based Study

Abstract

Purpose: Glioblastoma multiforme (GBM) remains the deadliest primary brain tumor. We aimed to illuminate the role of nucleotide-binding oligomerization domain (NOD)-like receptor subfamily C (NLRC) in GBM.

Patients and methods: Based on public database data (mainly The Cancer Genome Atlas [TCGA]), we performed bioinformatics analysis to visually evaluate the role and mechanism of NLRCs in GBM. Then, we validated our findings in a glioma tissue microarray (TMA) by immunohistochemistry (IHC), and the prognostic value of NOD1 was assessed via random forest (RF) models.

Results: In GBM tissues, the expression of NLRC members was significantly increased, which was related to the low survival rate of GBM. Additionally, Cox regression analysis revealed that the expression of NOD1 (among NLRCs) served as an independent prognostic marker. A nomogram based on multivariate analysis proved the effective predictive performance of NOD1 in GBM. Enrichment analysis showed that high expression of NOD1 could regulate extracellular structure, cell adhesion, and immune response to promote tumor progression. Then, immune infiltration analysis showed that NOD1 overexpression correlated with an enhanced immune response. Then, in a glioma TMA, the results of IHC revealed that the increase in NOD1 expression indicated high recurrence and poor prognosis of human glioma. Furthermore, the expression level of NOD1 showed good prognostic value in the TMA cohort via RF.

Conclusion: The value of NOD1 as a biomarker for GBM was demonstrated. The possible mechanisms may lie in the regulatory role of NLRC-related pathways in the tumor microenvironment.

Keywords: NLRC family; biomarker; glioblastoma multiforme; prognostic model; tissue microarray; tumor microenvironment.

Figure 1

NLRC expression in cancer. (A) According to Oncomine, Graph of the number of datasets showing statistically significant increase (red) or decrease (blue) of NLRC family mRNA expression in GBM samples and corresponding normal tissues. Heatmap (B) and Box plots (C) showing the relative expression level of NLRC family between GBM and normal samples in GTEx/TCGA. ***p < 0.001.

Figure 2

Analysis of NLRC alteration, methylation, and their associations with prognosis in GBM. (A) Summary plot displaying alterations of NLRC family in 141 GBM patients/samples. (B) Altered NLRC significantly linked to poor prognosis. (C) The Product-limit Estimate survival of the promoter methylation of NLRC family.

Figure 3

Influence of NLRC expression on GBM survival. (A) The DFS curves. (B) The OS curves. (C) Multivariate Cox analysis forest map summary. Nomogram (D) and calibration curve (E) were used to predict the probability of OS in GBM patients in 1, 2 and 3 years.

Figure 4

Identification and enrichment analysis of DEG. (A) DEG volcano map. (B) Heat map showing the top 10 DEGs. (C) Bubble map showing NOD1-GO results of DEG in low and high expression samples. (D) GSEA analysis of DEGs between low and high expression groups of NOD1.

Figure 5

Protein interaction of NOD1 in GBM. (A) PPI network. (B) The 10 hub genes presented from low (yellow) to high (red) degree value. (C) Cluster 1 consisting of 19 downregulated DEGs and 148 interactions, MCODE score  =  16.444. (D) Cluster 2 consisting of 9 upregulated DEGs and 36 interactions, MCODE score  =  9. (E) Cluster 3 consisting of 12 DEGs and 28 interactions, MCODE score  =  5.091. Orange represented up regulated genes and green represented downregulated genes.

Figure 6

Immune analysis of NOD1 in GBM patients. (A) NOD1 expression was positively correlated with CD4 + T lymphocyte and dendritic cell concentration, and negatively correlated with CD8 + T lymphocyte infiltration. (B) Correlation between NOD1 expression and immune cells. (C) Correlation analysis between NOD1 expression and corresponding immune cells in GBM. (D) Distribution of the immune, stromal, and ESTIMATE scores among groups with high and low levels of NOD1 expression in TCGA. *p<0.05; **p<0.01; ***p<0.001.

Figure 7

Immunohistochemical staining results of NOD1 in microarray cohort. (A) The immunohistochemical staining showing NOD1 expression were higher in WHO IV glioma tissues, compared to WHO I glioma tissues, bar=600μm. (B) Bar chart showing NOD1 expression score were significantly higher in WHO IV glioma tissues, compared to WHO I–III glioma tissues. (C) The ROC curve of microarray cohort. (D) Survival curve showing the high NOD1expression significantly related to the poor prognosis of glioma patients. ***p<0.001.

Figure 8

The prognostic value of NOD1 expression combining WHO classification in TMA cohort. (A) The ROC and AUC of NOD1 with WHO classification for 5-year DFS. (B) The ROC and AUC of NOD1 with WHO classification for 5-year OS.