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. 2022 May 12:13:903634.
doi: 10.3389/fgene.2022.903634. eCollection 2022.

Identification of Two m6A Readers YTHDF1 and IGF2BP2 as Immune Biomarkers in Head and Neck Squamous Cell Carcinoma

Affiliations

Identification of Two m6A Readers YTHDF1 and IGF2BP2 as Immune Biomarkers in Head and Neck Squamous Cell Carcinoma

Shaojie Li et al. Front Genet. .

Abstract

Background: N6-methyladenosine (m6A) is the most abundant internal modification pattern in mammals that a plays critical role in tumorigenesis and immune regulations. However, the effect of m6A modification on head and neck squamous cell carcinoma (HNSCC) has not been clearly studied. Methods: We screened m6A regulators that were significantly correlated with tumor immune status indicated by ImmuneScore using The Cancer Genome Atlas (TCGA) dataset and obtained distinct patient clusters based on the expression of these m6A regulators with the R package "CensusClusterPlus." We then performed gene set enrichment analysis (GSEA), CIBERSORT, and single-sample gene set enrichment analysis (ssGSEA) to assess the differences in gene function enrichment and tumor immune microenvironment (TIME) among these clusters. We further conducted differently expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) and constructed a protein-protein interaction (PPI) network to determine hub genes among these clusters. Finally, we used the GSE65858 dataset as an external validation cohort to confirm the immune profiles related to the expression of m6A regulators. Results: Two m6A readers, YTHDF1 and IGF2BP2, were found to be significantly associated with distinct immune status in HNSCC. Accordingly, patients were divided into two clusters with Cluster 1 showing high expression of YTHDF1 and IGF2BP2 and Cluster 2 showing low expression levels of both genes. Clinicopathologically, patients from Cluster 1 had more advanced T stage and pathological grades than those from Cluster 2. GSEA showed that Cluster 1 was closely related to the RNA modification process and Cluster 2 was significantly correlated with immune regulations. Cluster 2 had a more active TIME characterized by a more relative abundance of CD8+ T cells and CD4+ T cells and higher levels of MHC I and MHC II molecules. We constructed a PPI network composed of 16 hub genes between the two clusters, which participated in the T-cell receptor signaling pathway. These results were externally validated in the GSE65858 dataset. Conclusions: The m6A readers, YTHDF1 and IGF2BP2, were potential immune biomarkers in HNSCC and could be potential treatment targets for cancer immunotherapy.

Keywords: HNSCC; IGF2BP2; YTHDF1; immune microenvironment; immunotherapy; m6A modification.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The correlation of m6A regulators with the results of ESTIMATE and CIBERSORT.
FIGURE 2
FIGURE 2
Clustering of patients with HNSCC in TCGA cohort based on expression of YTHDF1 and IGF2BP2. (A) Consensus clustering matrix for k = 2. (B) The results of PCA of clustering based on 21 m6A regulators as well as YTHDF1 and IGF2BP2. (C) Comparison the expression levels of YTHDF1 and IGF2BP2 between Cluster 1 and Cluster 2. (D) Comparison of the expression levels of YTHDF1 and IGF2BP2 between tumor samples and normal samples. (E) Kaplan–Meier curves of the overall survival in two clusters. ****p < 0.0001.
FIGURE 3
FIGURE 3
Differences of GSEA and immune cells infiltration between two clusters. (A) The tendency of enrichment of biological pathways between two clusters. (B) ssGSEA indicated different immune cells infiltration between two clusters. (C) Comparison of immune-related molecules between Cluster 1 and Cluster 2. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
FIGURE 4
FIGURE 4
Expression level comparison of HNSCC-related genes. (A) TCGA cohort and (B) GEO cohort. ***p < 0.001, ****p < 0.0001.
FIGURE 5
FIGURE 5
Screening of hub genes related to clustering and ImmuneScore in two clusters. (A) The volcano plot for results of differentially expressed genes. (B) The heatmap of differentially expressed genes. (C) Correlation of gene modules with results of clustering and ESTIMATE.
FIGURE 6
FIGURE 6
Analysis of functional enrichment and construction of PPI network. (A) Selected enriched terms for a network, colored by cluster group ID. (B) Functional enrichment analysis in various ontology sources. (C) Protein-protein interaction network analysis for whole selected genes and two highlighted MCODE components.
FIGURE 7
FIGURE 7
Validation of clustering based on YTHDF1 and IGF2BP2 in GSE65858. (A) Consensus clustering matrix for k = 2. (B) The results of PCA of clustering based on 21 m6A regulators as well as YTHDF1 and IGF2BP2. (C) Comparison of expression level of YTHDF1 and IGF2BP2 between Cluster 1 and Cluster 2. (D) ssGSEA indicated different immune cells infiltration between two clusters. (E) Comparison of immune-related molecules between Cluster 1 and Cluster 2. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

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