Abstract
BACKGROUND: Oral cancer is one of the most prevalent malignant neoplasms globally, with its microenvironment being extremely complicated and heterogeneous with regard to distribution of different types of cells, which creates a barrier against treatment. We integrated single-cell RNA sequencing, pseudotime analysis, and intercellular communication to identify subtypes, state transitions, and interactions in the development of oral cancer and their roles in tumor progression and immune response. METHODS: Principal component analysis (PCA) followed by dimensionality reduction techniques (UMAP and t-SNE) revealed multiple populations in the single-cell data from oral cancer. Analysis of gene expression patterns associated individual genes with distinct principal components that described features of cell subtypes or states in the oral cancer microenvironment. We also conducted gene set enrichment analysis (GSEA) and cell-cell communication network analysis to investigate the important signaling pathways as well as potential cell-cell communications. RESULTS: Gene expression patterns linked to oral cancer cell subtypes and states in this study included cell membrane, signal transduction and immune response in different biological processes. Pseudotime analysis showed differentiation trajectories and expression of essential differentiation genes were also altered. Cell-cell communication network analysis revealed that myeloid cells interacted heavily with myeloid cells and they also had strong interactions with endothelial cells. Analysis of the MIF signaling pathway network showed participation of various cell types in MIF signaling, suggesting its potential significance in the oral cancer microenvironment. CONCLUSION: The intercellular communication complexity of TME in oral cancer is reported here with the first-ever single cell analysis and data providing new perspective regarding the heterogeneity of oral cancer.