使用生物信息学方法识别舌鳞状细胞癌的诊断生物标志物和免疫细胞浸润

In this study, we employed a bioinformatics approach to identify diagnostic biomarkers for tongue squamous cell carcinoma (TSCC) and investigate the infiltration of immune cells in TSCC, as well as the relationship between biomarkers and immune cells.

We obtained the TSCC expression dataset from a database and conducted differential gene expression analysis between TSCC and adjacent normal tissues using R software. Enrichment analysis of the differentially expressed genes (DEGs) was performed using the DAVID website. Protein interaction networks for the DEGs were constructed, and hub genes were identified using tools such as STRING and Cytoscape. Survival analysis was conducted to identify diagnostic biomarkers and the infiltration of immune cells in TSCC was analyzed using the inverse convolution algorithm with Cibersort software. Finally, the expression of the discovered molecules was verified through clinical pathological sections.

We identified 24 DEGs in TSCC, primarily associated with signal transduction, substance metabolism, innate immune response, and other related signaling pathways. Among the 24 hub genes screened through the construction of a protein-protein interaction (PPI) network, seven (MMP13, POSTN, MMP9, MMP10, MMP3, SPP1, MMP1) exhibited prognostic value. Survival analysis indicated that SPP1 demonstrated diagnostic potential. The expression level of the SPP1 gene showed a correlation with TSCC as well as several immune cell types, including macrophage M0, M1, M2, CD8 + T cell, activated NK cell, and monocyte (p < 0.05). Histological results confirmed higher expression of SPP1 in TSCC tissues compared to adjacent non-cancerous tissues, particularly in CD68-expressing macrophages.

Our findings suggest that SPP1 serves as a diagnostic biomarker for TSCC and is involved in immune cell infiltration within TSCC tissues. The correlation between SPP1 and macrophages may offer new insights for targeted therapeutic research on TSCC.