High eukaryotic initiation factor 5A2 expression predicts poor prognosis and may participate in the SNHG16/miR-10b-5p/EIF5A2 regulatory axis in head and neck squamous cell carcinoma

Abstract

Background: This study attempted to investigate the significance of eukaryotic initiation factor 5A2 (EIF5A2) in the prognosis and regulatory network of head and neck squamous cell carcinoma (HNSCC).

Methods: EIF5A2 expression, prognostic information, and methylation levels of HNSCC were collected from the Cancer Genome Atlas (TCGA) database. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot analyses were performed to determine EIF5A2 levels in HNSCC and normal tissue samples. R software was employed for expression analysis and prognosis assessment of EIF5A2 in HNSCC. A competing endogenous RNA (ceRNA) network was generated with the starBase database. Gene set enrichment analysis (GSEA) was used to determine the enriched physiological functions and network related to high expression of EIF5A2 in HNSCC. Immune infiltration-related outcomes were acquired from the CIBERSORT and Tumor Immune Estimation Resource (TIMER) database.

Results: EIF5A2 overexpression was observed in HNSCC and linked to poor progression-free survival and overall survival time. Cox regression analyses showed that EIF5A2 level was a stand-alone indicator of HNSCC patients' prognosis. A ceRNA network analysis highlighted the SNHG16/miR-10b-5p/EIF5A2 axis in EIF5A2 regulation. The GSEA results indicated that EIF5A2 was involved in complex signaling pathways. The CIBERSORT and TIMER databases revealed significant associations between EIF5A2 expression and immune cell infiltration.

Conclusion: EIF5A2 overexpression may be a risk factor for prognosis in HNSCC and may be regulated by the SNHG16/miR-10b-5p/EIF5A2 axis.

Keywords: The Cancer Genome Atlas; competing endogenous RNA (ceRNA) network; eukaryotic initiation factor 5A2; head and neck squamous cell carcinoma; prognosis.

FIGURE 1

Expression levels of EIF5A2. (A) Differential EIF5A2 expression levels in various types of cancers. T: tumor tissues, N, normal tissues. Red abbreviations represent EIF5A2 significantly upregulated cancer types. Green abbreviations represent EIF5A2 significantly downregulated cancer types. (B) High EIF5A2 expression in HNSCC samples based on TCGA database. (C) IHC staining images of EIF5A2 protein levels in HNSCC versus normal samples from HPA database. (D) The relative expression levels of EIF5A2 mRNA of 16 paired samples were markedly upregulated in HNSCC tissues. (E) The EIF5A2 protein levels of five paired tissues were markedly upregulated in HNSCC versus normal samples.

FIGURE 2

Underlying factors of EIF5A2 overexpression in HNSCC. (A) Genomic position of 10 available CpG in the EIF5A2 promoter by using UCSC Genome Browser. (B) Negative correlation between methylation modification and EIF5A2 expression in HNSCC. (C) Correlation between EIF5A2 expression and copy number variations.

FIGURE 3

EIF5A2 overexpression predicts poor OS in HNSCC. (A–C) Kaplan–Meier survival analysis indicates that EIF5A2 overexpression predicts lower survival rate in HNSCC base on the TCGA database, GSE65858 database, and GSE41613 database. (D–F) Cox regression analysis suggests EIF5A2 expression as a stand‐alone prognostic indicator of HNSCC patient OS.

FIGURE 4

EIF5A2 overexpression predicts poor PFS in HNSCC. (A, B) Kaplan–Meier survival analysis indicates that EIF5A2 overexpression predicts higher recurrence rate in HNSCC base on the TCGA and GSE65858 database. (C, D) Cox regression analysis suggests EIF5A2 expression as a stand‐alone prognostic indicator for recurrence in HNSCC patients.

FIGURE 5

EIF5A2‐related nomogram construction and validation. (A, B) Nomogram for estimating the likelihood of 1‐, 3‐, and 5‐year OS for HNSCC patients (C) ROC curve of the EIF5A2 expression with combined nomogram and clinical characteristics.

FIGURE 6

Potential regulatory mechanism of EIF5A2 in HNSCC. (A) Network mapping of EIF5A2‐related miRNAs from the starBase database. (B) Expression level of miR‐10b‐5p between the HNSCC samples and normal tissues. (C) Correlation between EIF5A2 and miR‐10b‐5p expression. (D) Kaplan–Meier survival analysis of miR‐10b‐5p levels with OS in HNSCC patients in TCGA database.

FIGURE 7

Construction of the EIF5A2‐centered ceRNA network. (A) lncRNAs upstream of hsa‐miR‐10b‐5p. (B) LINC02035 and SNHG16 and were both highly expressed in HNSCC. (C) LINC02035 and SNHG16 were found inversely associated with miR‐10b‐5p and directly associated with EIF5A2 levels. (D) Kaplan–Meier survival analysis demonstrated that elevated SNHG16 levels predicted worse OS time in HNSCC, and LINC02035 expression had no significant correlation with OS time.