Bioinformatics analysis of laryngeal squamous cell carcinoma based on the high infection rate of HPV in Northwest China

Abstract

Background: An increasing number of studies have demonstrated that human papillomavirus (HPV) plays a crucial role in the occurrence and development of laryngeal cancer. The present study aims to identify the differentially expressed genes and pathways in HPV-positive and HPV-negative laryngeal squamous cell carcinoma (LSCC) cells for the diagnosis and treatment of HPV-related LSCC, and to determine the prevalence rate of HPV in laryngeal cancer in Northwest China.

Methods: PCR-reverse dot blot was used to detect HPV genotypes in 115 LSCC patients' paraffin sections from Jan 2022 to Jun 2024.HPV-positive TU212 cells (TU212HPV) were constructed via lentiviral transfection. RT-qPCR and Western blot detected mRNA and protein levels. RNA-seq and TMT sequenced gene and protein differences. DAVID database was used for Gene Ontology and pathway enrichment analyses. STRING and Cytoscape screened key genes and further analyzed pathways.

Results: Among 115 patients, 64 were HPV-positive (HPV16 being the most common, 57 cases). The TU212HPV cell line was successfully constructed. RNA-seq identified 1,336 differentially expressed genes (797 upregulated, 539 downregulated). TMT found 236 differentially expressed proteins (124 upregulated, 112 downregulated). The key genes were discovered to be EGFR, CDC42, PXN, SLC2A1, GAPDH, FGF2, ICAM1, ITGB1, SFN, PGK1, and ISG15. Pathway enrichment showed involvement in neuroactive ligand-receptor interaction, Cytoskeleton in muscle cell, transcriptional misregulation in cancer, etc. (P < 0.05).

Conclusion: HPV infection rate is 55.65% among laryngeal cancer patients in Northwest China. Ten key genes, namely EGFR, CDC42, PXN, SLC2A1, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), FGF2, ICAM1, ITGB1, PGK1 and ISG15, as well as pathways like proteoglycans in cancer, regulation of actin cytoskeleton and HIF-1 signaling pathway are demonstrated to be of significance in the occurrence and development of laryngeal squamous cell carcinoma. PXN, ITGB1, ISG15, SLC2A1 and ICAM1 are regarded as potential therapeutic targets for HPV-positive laryngeal cancer. PXN and PGK1 are considered as potential prognostic markers for HPV-positive laryngeal cancer.

Keywords: Bioinformatics analysis; HPV; KEGG pathway; Laryngeal squamous cell carcinoma; Tumor.

Figure 1. HPV genotyping statistical bar chart.

The horizontal axis represents HPV genotyping, and the vertical axis represents the number of patients; The barplot was generated using Adobe Photoshop 2024.

Figure 2. Successful transfection of HPV16E7 in TU212 cells.

(A) Fluorescence image after successful transfection of TU212HPV. (B) RT-qPCR was used to detect the content of E7 mRNA in TU212HPV and TU212CON (TU212 containing an empty plasmid) (***p < 0.001). (C) WB was used to detect the content of E7 protein in TU212HPV and TU212CON. The barplot was generated using Adobe Photoshop 2024.

Figure 3. RNA sequencing data analysis.

(A) Volcano plot of expression differences between the TU212HPV and TU212 groups. The horizontal axis represents the fold-change (log2 (B/A)) value of gene expression differences between different groups of samples, and the vertical axis represents the statistical significance P-value of gene expression changes. The smaller the P-value, the larger the −log10 (P-value), and the more significant the difference. Each point in the figure represents a gene, where red indicates up-regulated genes, green indicates down-regulated genes, and black indicates non-differential genes. (B) Bar chart of GO annotation classification for differential genes between TU212HPV and TU212; the horizontal axis represents functional classification, and the vertical axis represents the number of genes in this classification; different colors represent different classifications. Red represents molecular function, green represents cellular component, and blue represents biological process. (C) Bar chart of KEGG annotation classification for differential genes between TU212HPV and TU212; the horizontal axis represents KEGG term, and the vertical axis represents the number of genes in this term. The P-values of all enrichment analyses are less than 0.05.

Figure 4. Quantitative proteomic analysis.

(A) Volcano plot of TU212HPV vs. TU212 expression differences. Horizontal axis: fold-change (log2 (B/A)) of gene expression. Vertical axis: p value of gene expression change (−log10). Red dots: genes up-regulated in TU212HPV vs. TU212. Blue dots: genes down-regulated in TU212HPV vs. TU212. Black dots: non-differential genes. (B–C) GO annotation classification bar chart of TU212HPV vs. TU212 differential proteins. Horizontal axis: functional classification. Vertical axis: number of genes in each classification. Red: molecular function. Green: cellular component. Blue: biological process. (D–E) KEGG annotation classification bar chart of TU212HPV vs. TU212 differential proteins. The horizontal axis represents the KEGG term, and the vertical axis represents the number of genes in this term. (F) The PPI (Protein-Protein Interaction) graph of differentially expressed genes with increased expression. (G) KEGG enrichment pathways of Key Genes with up-regulated differential expression. The P-values of all enrichment analyses are less than 0.05.

Figure 5. Expression of key genes in HNSC based on HPV status.

(A) CDC42; (B) PXN; (C) ITGB1; (D) PGK1; (E) SLC2A1; (F) ISG15; (G) ICAM1; (H) FGF2; (I) EGFR; (J) GAPDH.

Figure 6. Expression of key genes in HNSC based on tissue types.

Red represents tumor tissues, and gray represents normal tissues. (A) CDC42; (B) PXN; (C) ITGB1; (D) PGK1; (E) SLC2A1; (F) ISG15; (G) ICAM1; (H) FGF2; (I) EGFR; (J) GAPDH. (*p < 0.05).

Figure 7. Effect of key genes expression level on HNSC patient survival.

(A) CDC42; (B) PXN; (C) PGK1; (D) FGF2; (E) ISG15; (F) ITGB1; (G) SLC2A1; (H) EGFR; (I) ICAM1; (J) GAPDH.