舌鳞状细胞癌（TSCC）的病因、分子机制和致癌途径的鉴定对于制定新的诊断和治疗策略至关重要。本研究利用生物信息学方法识别TSCC的关键基因，探讨与TSCC恶性生物学行为相关的潜在功能和通路机制。基因芯片数据集（即GSE13601和GSE34106）包含TSCC患者和正常对照者的数据选自基因表达综合（GEO）数据库。使用GEO数据库的基因表达分析工具（GEO2R），使用以下标准鉴定差异表达基因（DEG）：|日志倍数变化| >1，且 P<0.05。 GEO2R 工具还用于根据 P 值 <0.05 选择芯片候选中上调的 DEG。然后进行京都基因和基因组百科全书（KEGG）通路分析、基因本体（GO）功能分析和蛋白质-蛋白质相互作用（PPI）网络分析。结果使用R语言包显示，包括火山图、维恩图、热图和丰富的路径气泡图。将 MalaCards 数据库中的基因与候选基因进行比较，并对文献进行彻底审查，以确定这些基因的临床意义。最后，利用比较毒理学基因组数据库（CTD）预测特征基因导向的化学药物或靶向药物。总共从GSE13601中鉴定出767个上调的DEG，从GSE34106中鉴定出695个上调的DEG。通过使用维恩图对两个数据集中上调的 DEG 进行交叉，确定了 100 个与 TSCC 相关的 DEG。 KEGG信号通路富集分析确定了与上调DEGs相关的大部分通路，包括Toll样受体信号通路、细胞外基质-受体相互作用、肿瘤坏死因子（TNF）信号通路、细胞因子-细胞因子受体相互作用、趋化因子信号通路、白介素-17 信号通路和自然杀伤细胞介导的细胞毒性。对共享 DEG 的 PPI 网络和模块分析最终产生了 5 个簇和 55 个候选基因。通过维恩图对 MalaCards 数据库中的 TSCC 相关基因进行进一步交叉分析，确定了三个重要的共享 DEG；即基质金属蛋白酶-1 (MMP1)、MMP9 和 MMP13。在CTD中，确定了七种与MMP13相关的药物用于治疗舌肿瘤。本研究确定了与TSCC相关的关键基因和信号通路，从而加深了对TSCC发生和进展的分子机制的理解。此外，本研究表明MMP13可能通过TNF信号通路影响TSCC的恶性生物学行为。这一发现可为早期鉴别诊断和靶向治疗的研究提供理论依据。2024转化癌症研究。版权所有。

Identification of the etiology, molecular mechanisms, and carcinogenic pathways of tongue squamous cell carcinoma (TSCC) is crucial for developing new diagnostic and therapeutic strategies. This study used bioinformatics methods to identify key genes in TSCC and explored the potential functions and pathway mechanisms related to the malignant biological behavior of TSCC.Gene chip data sets (i.e., GSE13601 and GSE34106) containing the data of both TSCC patients and normal control subjects were selected from the Gene Expression Omnibus (GEO) database. Using a gene expression analysis tool (GEO2R) of the GEO database, the differentially expressed genes (DEGs) were identified using the following criteria: |log fold change| >1, and P<0.05. The GEO2R tool was also used to select the upregulated DEGs in the chip candidates based on a P value <0.05. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Ontology (GO) function analysis, and a protein-protein interaction (PPI) network analysis were then conducted. The results were displayed using R language packages, including volcano plots, Venn diagrams, heatmaps, and enriched pathway bubble charts. Genes from the MalaCards database were compared with the candidate genes, and a thorough review of the literature was conducted to determine the clinical significance of these genes. Finally, feature gene-directed chemical drugs or targeted drugs were predicted using the Comparative Toxicogenomics Database (CTD).In total, 767 upregulated DEGs were identified from GSE13601 and 695 from GSE34106. By intersecting the upregulated DEGs from both data sets using a Venn diagram, 100 DEGs related to TSCC were identified. The enrichment analysis of the KEGG signaling pathways identified the majority of the pathways associated with the upregulated DEGs, including the Toll-like receptor signaling pathway, the extracellular matrix-receptor interaction, the tumor necrosis factor (TNF) signaling pathway, cytokine-cytokine receptor interaction, the chemokine signaling pathway, the interlukin-17 signaling pathway, and natural killer cell-mediated cytotoxicity. The PPI network and module analyses of the shared DEGs ultimately resulted in five clusters and 55 candidate genes. A further intersection analysis of the TSCC-related genes in the MalaCards database via a Venn diagram identified three important shared DEGs; that is, matrix metalloproteinase-1 (MMP1), MMP9, and MMP13. In the CTD, seven drugs related to MMP13 were identified for treating tongue tumors.This study identified key genes and signaling pathways involved in TSCC and thus extended understandings of the molecular mechanisms that underlie the development and progression of TSCC. Additionally, this study showed that MMP13 may influence the malignant biological behavior of TSCC through the TNF signaling pathway. This finding could provide a theoretical basis for research into early differential diagnosis and targeted treatment.2024 Translational Cancer Research. All rights reserved.