基于生物信息学分析的头颈部鳞状细胞癌新型预后生物标志物的鉴定。
Identification of Novel Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma using Bioinformatics Analysis.
机构信息
Department of Histology and Embryology, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang, China.
Department of Pharmacology, School of Pharmacy College, Xinjiang Medical University, Urumqi, Xinjiang, China.
出版信息
Comb Chem High Throughput Screen. 2021;24(9):1351-1363. doi: 10.2174/1386207323666201027120855.
BACKGROUND
Head and neck squamous cell carcinoma (HNSCC) is a common cancer that is characterized by a complex pathogenesis. Only limited data are available on the primary pathogenic genes and pathways in HNSCC.
OBJECTIVE
This study aimed to identify potential biomarkers of HNSCC and explore its underlying mechanisms.
METHODS
We screened differentially expressed genes (DEGs) using the Gene Expression Omnibus(GEO) database. Gene Ontology (GO) and Reactome pathway enrichment were analyzed using the STRING database. The protein-protein interaction network of the DEGs was reconstructed using Cytoscape software in STRING. The ONCOMINE and UNLCAN databases were used to identify the expression of hub genes. In addition, we employed UNLCAN to correlate tumor grade with key genes.
RESULTS
Finally, the effect of hub genes on overall survival (OS) was analyzed using the Kaplan- Meier method. In total, 22 DEGs were identified. These were related to the mitotic cell cycle, mitotic G1-G1, and S phases, G2/M transition, NOTCH signaling, and regulation of TP53 activity. Seven hub genes were screened with Cytoscape. Increased expression of five hub genes (AURKA, BIRC5, MKI67, UBE2C, and TOP2A) was related to a higher tumor grade and worse OS.
CONCLUSION
We have identified five key genes that may help us understand the carcinogenic mechanisms related to the cell cycle in HNSCC. These genes may be used as biomarkers for survival and treatment of HNSCC.
背景
头颈部鳞状细胞癌（HNSCC）是一种常见的癌症，其发病机制复杂。目前关于 HNSCC 的主要致病基因和途径的有限数据。
目的
本研究旨在鉴定 HNSCC 的潜在生物标志物，并探讨其潜在机制。
方法
我们使用基因表达综合（GEO）数据库筛选差异表达基因（DEGs）。使用 STRING 数据库进行基因本体论（GO）和反应途径富集分析。使用 STRING 中的 Cytoscape 软件重建 DEG 的蛋白质-蛋白质相互作用网络。使用 ONCOMINE 和 UNLCAN 数据库识别枢纽基因的表达。此外，我们还使用 UNLCAN 将肿瘤分级与关键基因相关联。
结果
最后，使用 Kaplan-Meier 方法分析了枢纽基因对总生存期（OS）的影响。共鉴定出 22 个 DEGs。这些基因与有丝分裂细胞周期、有丝分裂 G1-G1 和 S 期、G2/M 转换、NOTCH 信号转导和 TP53 活性调节有关。使用 Cytoscape 筛选出 7 个枢纽基因。五个枢纽基因（AURKA、BIRC5、MKI67、UBE2C 和 TOP2A）的表达增加与肿瘤分级较高和 OS 较差有关。
结论
我们已经鉴定出五个关键基因，它们可能有助于我们了解 HNSCC 中与细胞周期相关的致癌机制。这些基因可能作为 HNSCC 生存和治疗的生物标志物。
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