Significance of tumor mutation burden and immune infiltration in thymic epithelial tumors

Abstract

Background: Thymic epithelial tumors (TETs) are relatively rare malignant thoracic tumors. Tumor mutation burden (TMB) and immune infiltration play important roles in tumorigenesis.

Methods: Research data was obtained using the Cancer Genome Atlas (TCGA) database to evaluate the landscape of tumor mutations, related factors, and relationship of prognosis. The CIBERSORT algorithm was used to evaluate immune cell infiltration in TETs and its relationship with TMB. Immune-related differentially expressed genes (irDEGs) were identified. Hub irDEGs independently related to prognosis were analyzed using univariate and multivariate Cox proportional hazard models. A survival signature was constructed from hub irDEGs.

Results: A total of 122 patients were included in this study. GTF2I was the most common gene mutation. Higher TMB was significantly associated with the later stage, more advanced pathological type, and older age. The overall survival (OS) of patients in the low-TMB group was significantly better. There was no significant correlation between TMB levels and PD-L1 expression. Enrichment analysis showed that DEGs were mainly involved in the P13K-Akt signaling pathway. There were significant differences in macrophage and other types of immune cell infiltration between the high- and low-TMB groups. CCR5, FASLG, and CD79A independently relating to prognosis were screened from 391 irDEGs. The low-risk group had a significantly better prognosis than the high-risk group based on the signature, which has a good predictive effect on OS.

Conclusions: In this study, TETs patients with high TMB had a significantly poor prognosis and an immune-related gene signature was found to effectively evaluate the long-term prognosis.

Keywords: immune infiltration; prognosis; thymic epithelial tumors; thymus; tumor mutation burden.

FIGURE 1

Summary of the genetic mutation information of thymic epithelial tumor (TET) patients. (a, b) Missense mutation accounts for the most fractions in the variant classification and SNP was the most common type of mutation; (c) the SNV class of TETs; (d, e) tumor mutation burden in specific samples; (f) the top 10 mutated genes in TETs; (g) water plot of mutation profiles in each TET sample. SNP, single nucleotide polymorphism; SNV, single nucleotide variants

FIGURE 2

The associations of tumor mutation burden (TMB) in thymic epithelial tumors (TETs) with different clinicopathological characteristics. (a, c, e) Higher TMB level was significantly associated with the older age, later stage and more advanced pathological type. (b, d, f) No significant difference was observed with gender, race, and MG history

FIGURE 3

Prognosis of tumor mutation burden (TMB) and associations with PD‐L1 expression. (a) Overall survival of patients with thymic epithelial tumors (TETs) in the high‐TMB group correlated with significantly poor survival outcomes compared with the low‐TMB group (log‐rank p < 0.001). (b) No significant difference of PD‐L1 expression level was observed between the high‐ and low‐TMB groups in TETs

FIGURE 4

The top 50 differentially expressed genes (DEGs) of the high‐ and low‐ TMB groups are shown in the heatmap plot

FIGURE 5

Pathway functional enrichment analysis of differentially expressed genes (DEGs). (a) KEGG enrichment analysis results of DEGs. (b) Gene ontology (GO) enrichment analysis results of DEGs. TMB, tumor mutation burden

FIGURE 6

The landscape of immune cells infiltration in thymic epithelial tumors (TETs). (a) The heatmap plot of immune cells infiltration in each sample. (b) The fractions of infiltrated immune cells in high‐ and low–TMB groups. TMB, tumor mutation burden

FIGURE 7

Identification of immune‐related differentially expressed genes (irDEGs) and core genes. (a) Venn plot of DEGs and immune‐related genes, and 391 irDEGs were identified from the two sets. (b) Box plot of top 25 core genes with the highest clustering

FIGURE 8

Protein‐to‐protein interaction network analysis of immune‐related differentially expressed genes (irDEGs). The upregulated genes are shown in red and the downregulated in blue

FIGURE 9

Survival analysis of thymic epithelial tumor (TET) patients with high and low expression of three core genes and survival analysis of gene signature and its predictive ability assessment. Kaplan–Meier curves of (a) FASLG, (b) CCR5, (c) CD79A, and (d) gene signature. The area under the ROC curve of three‐ and five‐year overall survival (OS) for the gene signature were 0.873 and 0.885, respectively (e, f). Receiver operating characteristic curve (ROC)