Special Treatment, Jinan Stomatological Hospital, Jinan, Shandong, China.
Department of Prosthodontic, Tianjin Binhai New Area Tanggu Stomatology Hospital, China.
Comput Math Methods Med. 2021 Dec 30;2021:5802110. doi: 10.1155/2021/5802110. eCollection 2021.
The advance of new treatment strategies for more effective management of oral cancer requires identification of novel biological targets. Therefore, the purpose of this study is to identify novel biomarkers associated with oral tumorigenesis and prognostic signature by comparing gene expression profile of oral squamous cell carcinomas (OSCCs).
Four datasets including GSE25099, GSE30784, GSE37991, and GSE41613 were collected from Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Cox model analysis, identification of key genes, and Kaplan-Meier analysis were also performed. The xCell was utilized to analyze the infiltration levels of immune cells.
A total of 235 differentially expressed genes (DEGs) were found to be dysregulated in OSCC. These genes were mainly enriched in ECM receptor interaction and focal adhesion. Cox regression analysis identified 10 genes considered as key genes. Kaplan-Meier analysis showed that low expression of SERPINE1 (also known as PAI-1), high expression of CD1C, and C-X3-C motif chemokine receptor 1 (CX3CR1) were associated with well prognostic status in OSCC patients. In addition, we constructed a 3-immune-cell signature (myeloid dendritic cell, T cell CD4 central memory, and common myeloid progenitor) that may be used to predict the survival status of OSCC patients.
Three key genes and 3-immune-cell signature were potential biomarkers for the prognosis of OSCC, and they may serve as potential targets for the treatment of OSCC patients.
为了更有效地治疗口腔癌，需要采用新的治疗策略，这就需要确定新的生物学靶点。因此，本研究旨在通过比较口腔鳞状细胞癌（OSCC）的基因表达谱，鉴定与口腔肿瘤发生和预后相关的新型生物标志物和预后特征。
从基因表达综合数据库（GEO）中收集了包括 GSE25099、GSE30784、GSE37991 和 GSE41613 在内的 4 个数据集。进行了基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析、Cox 模型分析、关键基因识别和 Kaplan-Meier 分析。利用 xCell 分析免疫细胞的浸润水平。
共发现 235 个差异表达基因（DEGs）在 OSCC 中失调。这些基因主要富集在 ECM 受体相互作用和焦点粘连中。Cox 回归分析确定了 10 个被认为是关键基因的基因。Kaplan-Meier 分析显示，SERPINE1（也称为 PAI-1）低表达、CD1C 高表达和 C-X3-C 基序趋化因子受体 1（CX3CR1）高表达与 OSCC 患者的良好预后状态相关。此外，我们构建了一个 3-免疫细胞特征（髓样树突状细胞、T 细胞 CD4 中央记忆细胞和普通髓样祖细胞），可用于预测 OSCC 患者的生存状态。
三个关键基因和 3-免疫细胞特征可能是 OSCC 预后的潜在生物标志物，它们可能成为 OSCC 患者治疗的潜在靶点。
