Profiling the Tumor Immune Microenvironment of HPV-Associated Base of Tongue Squamous Cell Carcinoma

Abstract

Background: Base of tongue squamous cell carcinoma (BOTSCC) is a prevalent and aggressive form of oral cancer, often associated with poor patient outcomes. The tumor microenvironment (TME) of HPV-positive BOTSCC is critical in influencing cancer progression and treatment response.

Objective: This study aims to analyze the TME of HPV-positive BOTSCC by examining the expression of key genes involved in various biological processes.

Methods: We utilized the RT2 Profiler PCR Array to quantify the expression of 168 genes related to inflammation, immunity, oncogenesis, tumor suppression, apoptosis, and angiogenesis. Enrichment analysis of cancer hallmarks was performed on all upregulated genes. Additionally, we investigated the correlation between the expression levels of the ten most highly upregulated genes and survival prognosis in HPV-associated BOTSCC patients.

Results: Our analysis revealed dysregulation of 42 genes associated with tumor-immune interactions, with 20 genes upregulated and 22 downregulated. Furthermore, we identified 64 genes linked to cancer development, with 33 upregulated and 31 downregulated. High-risk HPV (hr-HPV) genotypes were found in 81% of patients, predominantly HPV-35 and HPV-16.

Conclusion: This study highlights the complexity of the HPV-positive BOTSCC TME, underscoring the need for further research into molecular pathways and immune interactions to identify new therapeutic targets for improved cancer treatment.

Keywords: HPV; base of tongue squamous cell carcinoma; gene expression; immunity crosstalk; inflammation; oncogenes; tumor microenvironment; tumor suppressor gene.

Graphical abstract

Figure 1

Heatmap of the 42 dysregulated genes’ expression profiles in patients with BOSTCC linked to HPV. Dysregulated tumor inflammation and immune crosstalk gene expression are displayed in the ring heatmap cluster gram. HPV-associated BOSTCC patients are represented by rings P1 through P8. While the color gradient depicts expression from low (blue) to high (red), the heatmap color scale shows the range of expression values. Co-expression is indicated by genes with comparable colors across samples. The hierarchical clustering of genes according to their patterns of expression is displayed by the dendrogram, or tree structure.

Figure 2

Mean fold-change expression of genes involved in tumor cell-to-tumor cell contact and cellular mediators of inflammation and immune crosstalk in two age groups of patients with HPV-associated BOTSCC. The data emphasize the effect of age on gene expression patterns in the context of HPV-associated BOTSCC by showing the difference in expression levels between patients under the age of 55 and those over 55.

Figure 3

The 64 dysregulated gene expression profiles in HPV-associated BOSTCC patients are shown in a heatmap. The cluster-gram of the ring heatmap of the expression of tumor suppressors and dysregulated oncogenes. Patients with BOSTCC linked to HPV are represented by rings (P1 to P8). The range of expression values is shown by the color scale of the heatmap. Expression is represented by the color gradient, which ranges from low (blue) to high (red). Co-expression is indicated by genes with comparable colors across samples. The hierarchical clustering of genes according to their expression patterns was displayed by the dendrogram, or tree structure.

Figure 4

Genes linked to tumor suppression and oncogenesis expressed at mean fold-change in two age groups of patients with HPV-associated BOTSCC. Age has an impact on gene expression profiles in the setting of HPV-associated BOTSCC, as seen by the data showing the varied expression levels between patients under and over the age of 55.

Figure 5

Analysis of Gene Expression Profile Clustering. Tumor suppressor genes, oncogenes, inflammation, and immunity-related gene expression profiles are grouped into different clusters by the study. The relationship between inflammation and immunity Groupings: Cluster 1: Antigen presentation, inflammatory enzymatic modulators, and immunostimulatory factors. Interleukins and chemokines make up Cluster 2. Cluster 3: Signaling from Toll-like receptors and chemokine receptors. Growth factors and receptors make up Cluster 4. Transcription factors are in cluster five. Cluster 6: Factors that prevent death. Oncogenes and Suppressors of Cancer Groupings: Group 1: Oncogenes. Cluster 2: Genes that inhibit tumor growth. Cluster 3 includes both tumor suppressor and carcinogenic genes. Cell cycle-related genes make up Cluster 4. Transition from epithelium to mesenchymal tissue is Cluster 5.

Figure 6

Protein-protein interactions with STRING PPI. Different colored lines indicate string PPI interactions. The protein-protein association is represented by the edges. Interactions with known co-occurrence evidence and experimental evidence are indicated by blue and purple borders. Text mining and co-expression are indicated by black and yellow margins. Various hues correspond to different kinds of interactions.

Figure 7

Using CancerHallmarks.com, the elevated gene set in HPV-associated BOTSCC is compared to established hallmark gene sets in a cancer hallmark enrichment plot. The red dotted line indicates an adjusted p-value threshold of less than 0.05, while colored slices indicate significantly enhanced characteristics. The distribution of elevated genes across several cancer hallmark pathways in HPV-associated BOTSCC is depicted by the dot plots. Markers with more mapped genes are indicated by black dots, and those with less mapped genes are indicated by grey dots.

Figure 8

The survival prognosis of cervical cancer is correlated with the expression levels of the 10 genes that are most substantially elevated in CSCC. Overall survival rate: The inadequate survival rate is shown by the red line; the opposite is shown by the blue line.