Siyuan Wu, Xiaozhi Lv, Jialin Wu, Wei Haigang, Liu Shiwei, Zou Chen, Song Jing, Xia Li, Yilong Ai
Foshan Stomatological Hospital, School of Medicine, Foshan University, Foshan, Guangdong, China.
Department of Oral and Maxillofacial Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Int J Genomics. 2023 Oct 14;2023:8860321. doi: 10.1155/2023/8860321. eCollection 2023.
This study explores the effects of curcumin as a therapeutic agent against oral squamous cell carcinoma (OSCC).
We acquired the targets of curcumin from three digital databases, including the Comparative Toxicogenomics Database, Search Tool for Interactions of Chemicals, and SwissTargetPrediction. Then, we identified the differentially expressed genes (DEGs) and the weighted gene coexpression network analysis-based key modules using the expression profiles of GSE23558 to acquire the OSCC-related genes. Additionally, the GeneCards and Online Mendelian Inheritance in Man databases were also used to identify the OSCC-related genes. Finally, curcumin-OSCC interaction genes were obtained by overlapping curcumin targets and OSCC-related genes. The enrichment analysis was performed by the ClusterProfiler algorithm and Metascape, respectively. Then, a protein-protein interaction network was created, and the maximal clique centrality algorithm was used to identify the top 10 hub genes. Besides, we examined the expression levels of hub genes in OSCC using The Cancer Genome Atlas database.
927 DEGs were identified, including 308 upregulated ones and 619 downregulated ones. The cluster one-step network construction function of the WGCNA algorithm recognized a soft-thresholding power of 6, and 9083 genes were acquired. 2591 OSCC-related genes were obtained by overlapping the GSE23558-identified genes and the OSCC-related genes from disease target bases. Finally, we identified 70 candidate drug-disease interaction genes by overlapping the disease-related genes with the curcumin target. The enrichment analysis suggested that response to oxidative stress, epithelial cell proliferation, and AGE/RAGE pathway might involve in the effect of curcumin on OSCC. The topologic study identified the ten hub genes, including , , , , , , , , , and . A significant difference was observed in VEGFA, AKT1, TNF, HIF1A, EGFR, MMP9, EGF, and MAPK3 expression levels between head and neck squamous cell carcinoma and the normal controls. However, no significant difference was observed in ( = 0.14) and ( = 0.054).
This study provided an overview and basis for the potential mechanism of curcumin against OSCC. The following experiments should be performed to further understand the effectiveness and safety of curcumin in treating OSCC.
本研究探讨姜黄素作为治疗口腔鳞状细胞癌（OSCC）药物的效果。
我们从三个数字数据库获取姜黄素的靶点，包括比较毒理基因组学数据库、化学物质相互作用搜索工具和瑞士靶点预测数据库。然后，我们使用GSE23558的表达谱鉴定差异表达基因（DEG）和基于加权基因共表达网络分析的关键模块，以获取OSCC相关基因。此外，还使用了基因卡片和人类孟德尔遗传在线数据库来鉴定OSCC相关基因。最后，通过重叠姜黄素靶点和OSCC相关基因获得姜黄素 - OSCC相互作用基因。分别通过ClusterProfiler算法和Metascape进行富集分析。然后，创建蛋白质 - 蛋白质相互作用网络，并使用最大团中心性算法鉴定前10个枢纽基因。此外，我们使用癌症基因组图谱数据库检查了OSCC中枢纽基因的表达水平。
鉴定出927个DEG，包括308个上调基因和619个下调基因。WGCNA算法的聚类一步网络构建功能识别出软阈值功率为6，并获得9083个基因。通过重叠GSE23558鉴定的基因和疾病靶点库中的OSCC相关基因，获得2591个OSCC相关基因。最后，通过将疾病相关基因与姜黄素靶点重叠，鉴定出70个候选药物 - 疾病相互作用基因。富集分析表明，对氧化应激的反应、上皮细胞增殖和AGE/RAGE途径可能参与姜黄素对OSCC的作用。拓扑学研究鉴定出10个枢纽基因，包括 ， ， ， ， ， ， ， ， ，和 。头颈部鳞状细胞癌与正常对照之间在VEGFA、AKT1、TNF、HIF1A、EGFR、MMP9、EGF和MAPK3表达水平上观察到显著差异。然而，在 （ = 0.14）和 （ = 0.054）中未观察到显著差异。
本研究为姜黄素抗OSCC的潜在机制提供了概述和依据。应进行以下实验以进一步了解姜黄素治疗OSCC的有效性和安全性。
