Oral squamous cell carcinoma (OSCC) carcinogenesis involves heterogeneous tumor cells, and the tumor microenvironment (TME) is highly complex with many different cell types. Cancer cell–TME interactions are crucial in OSCC progression. Candida albicans (C. albicans)—frequently pre-sent in the oral potentially malignant disorder (OPMD) lesions and OSCC tissues—promotes malignant transformation. The aim of the study is to verify the mechanisms underlying OSCC car-cinogenesis with C. albicans infection and identify the biomarker for the early detection of OSCC and as the treatment target. The single-cell RNA sequencing analysis (scRNA-seq) was performed to explore the cell subtypes in normal oral mucosa, OPMD, and OSCC tissues. The cell composi-tion changes and oncogenic mechanisms underlying OSCC carcinogenesis with C. albicans infec-tion were investigated. Gene Set Variation Analysis (GSVA) was used to survey the mechanisms underlying OSCC carcinogenesis with and without C. albicans infection. The results revealed spe-cific cell clusters contributing to OSCC carcinogenesis with and without C. albicans infection. The major mechanisms involved in OSCC carcinogenesis without C. albicans infection are the IL2/STAT5, TNFα/NFκB, and TGFβ signaling pathways, whereas those involved in OSCC carcinogenesis with C. albicans infection are the KRAS signaling pathway and E2F target down-stream genes. Finally, stratifin (SFN) was validated to be a specific biomarker of OSCC with C. albicans infection. Thus, the detailed mechanism underlying OSCC carcinogenesis with C. albicans infection was determined and identified the treatment biomarker with potential precision medicine applications.

Cancer-associated fibroblasts (CAFs) and partial epithelial–mesenchymal transition (p-EMT) tumor cells are closed together and contribute to the tumor progression of oral squamous cell carcinoma (OSCC). In the present study, we deeply analyzed and integrated OSCC single-cell RNA sequencing datasets to define OSCC CAFs and p-EMT subpopulations. We highlighted the cell–cell interaction network of CAFs and p-EMT tumor cells and suggested biomarkers for the diagnosis and prognosis of OSCC during the metastasis condition. The analysis discovered four subtypes of CAFs: one p-EMT tumor cell population, and cycling tumor cells as well as TNFSF12-TNFRSF25/TNFRSF12A interactions between CAFs and p-EMT tumor cells during tumor metastasis. This suggests the prediction of therapeutically targetable checkpoint receptor–ligand interactions between CAFs and p-EMT tumor cells in OSCC regarding the metastasis status.