SEC61G identified as a prognostic biomarker of head and neck squamous cell carcinoma

Abstract

Purpose: It is of obvious interest to identify clinical prognosis-related oncogenes in HNSCC (head and neck squamous cell carcinoma).

Methods: Based on the available datasets within the TCGA (The Cancer Genome Atlas) and the GEO (Gene Expression Omnibus) databases, the potential mechanism of action of the SEC61G (SEC61 translocon subunit gamma) gene in HNSCC tumorigenesis was explored by several bioinformatics approaches.

Results: There was a higher expression level of SEC61G in primary HNSCC tumor tissues than in normal tissues. Moreover, highly expressed SEC61G was statistically associated with the poor survival prognosis of HNSCC patients. When HPV (human papilloma virus) was considered, we also observed a relatively lower proportion of "arm-level gain" and "high amplification" types of CNA (copy-number alteration) in the HNSCC-HPV (+) group than in the HNSCC-HPV (-) group. Additionally, we identified SEC61G CAN-correlated genes, such as CCT6A (chaperonin-containing TCP1 subunit 6A) and HUS1 (HUS1 checkpoint clamp component), and found a correlation between SEC61G copy-number segments and prognosis related to overall and progression-free survival intervals of HNSCC patients. Moreover, the molecular regulation mechanisms of the spliceosome, ribosome, proteasome degradation, cell adhesion, and immune infiltration of B and CD8⁺ T cells may contribute to the involvement of SEC61G in the pathogenesis of HNSCC.

Conclusions: The SEC61G gene was identified for the first time as a prognostic biomarker of HNSCC. The detailed underlying mechanism merits further research.

Keywords: Head and neck squamous cell carcinoma; Prognosis; SEC61G; TCGA.

Fig. 1

The expression level of the SEC61G gene. a Expression differences in the SEC61G gene in normal and HNSCC tissues were detected based on the HNSCC dataset from the TCGA. Two factors, including, b HPV and c sex, were considered. d Through the Oncomine database, differential expression data of SEC61G between normal and different tumor tissues were provided. e Pooled analysis of SEC61G across five GEO studies was conducted

Fig. 2

Correlation between SEC61G expression and survival prognosis of HNSCC cases. a Survival maps of OS and DFS rates were obtained using the GEPIA2 approach. b Survival plots of HNSCC were displayed. c Based on the GSE2837 dataset, an RFS rate analysis of HNSCC patients was performed

Fig. 3

Genetic alteration analysis of SEC61G. a Association between SEC61G expression and CNA across all TCGA tumors was analyzed via TIMER2.0. b Correlation analysis between SEC11G log2 copy-number values and the mRNA expression Z score was performed via cBioPortal. c We identified potential SEC61G CNA-associated genes via LinkedOmics. d Potential correlations between the copy-number segments of SEC61G and the status of overall survival, disease-specific survival, progression-free interval, and disease-free interval rates were determined via UCSC-Xena

Fig. 4

SEC61G-correlated gene enrichment analysis. a Heat map of the significant genes positively or negatively correlated with SEC61G. b Expression correlation between SEC61G and the selected genes in a Spearman correlation test. c GO enrichment analysis

Fig. 5

SEC61G-correlated KEGG pathway enrichment analysis. GSEA data of “cell adhesion molecules”, “spliceosome”, and “ribosome”

Fig. 6

SEC61G-correlated Wikipathway enrichment analysis. GSEA data of the “B cell receptor signaling pathway”, “proteasome degradation”, and “cytoplasmic ribosomal proteins”

Fig. 7

Correlation analysis between SEC61G expression and immune cell infiltration in HNSCC. a Based on the HNSCC dataset of TCGA, the potential association between SEC61G expression and the infiltration status of B and T immune cells was studied via TIMER2.0. b One scatter plot of B cells or CD8⁺ T cells is shown as an example