使用生物信息学方法鉴定舌鳞状细胞癌的诊断生物标志物和免疫细胞浸润。
Identification of diagnostic biomarkers and immune cell infiltration in tongue squamous cell carcinoma using bioinformatic approaches.
机构信息
Department of Stomatology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, People's Republic of China.
Department of Periodontology, Fujian Key Laboratory of Oral Diseases, Fujian Provincial Engineering Research Center of Oral Biomaterial, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350004, Fujian, China.
出版信息
Eur J Med Res. 2024 Aug 21;29(1):428. doi: 10.1186/s40001-024-01998-y.
OBJECTIVE
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.
METHODS
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.
RESULTS
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.
CONCLUSION
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.
目的
本研究采用生物信息学方法鉴定舌鳞状细胞癌（TSCC）的诊断生物标志物，并研究 TSCC 中免疫细胞的浸润情况以及生物标志物与免疫细胞之间的关系。
方法
从数据库中获取 TSCC 表达数据集，使用 R 软件对 TSCC 和相邻正常组织进行差异基因表达分析。使用 DAVID 网站对差异表达基因（DEGs）进行富集分析。使用 STRING 和 Cytoscape 等工具构建 DEGs 的蛋白质相互作用网络，并识别枢纽基因。通过逆卷积算法和 Cibersort 软件进行生存分析，以鉴定 TSCC 的诊断生物标志物和免疫细胞的浸润情况。最后，通过临床病理切片验证所发现分子的表达。
结果
我们在 TSCC 中鉴定出 24 个 DEGs，这些基因主要与信号转导、物质代谢、先天免疫反应和其他相关信号通路有关。通过构建蛋白质-蛋白质相互作用（PPI）网络筛选出的 24 个枢纽基因中，有 7 个（MMP13、POSTN、MMP9、MMP10、MMP3、SPP1、MMP1）具有预后价值。生存分析表明 SPP1 具有诊断潜力。SPP1 基因的表达水平与 TSCC 以及几种免疫细胞类型（包括巨噬细胞 M0、M1、M2、CD8 T 细胞、活化 NK 细胞和单核细胞）相关（p<0.05）。组织学结果证实，SPP1 在 TSCC 组织中的表达水平高于相邻非癌组织，尤其是在表达 CD68 的巨噬细胞中。
结论
我们的研究结果表明，SPP1 可作为 TSCC 的诊断生物标志物，参与 TSCC 组织中免疫细胞的浸润。SPP1 与巨噬细胞之间的相关性可能为 TSCC 的靶向治疗研究提供新的思路。
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