Identification of a six-gene prognostic signature for oral squamous cell carcinoma
Identification of a six-gene prognostic signature for oral squamous cell carcinoma
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DOI：
10.1002/jcp.29210
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发表时间：
2019-09-19
影响因子：
5.6
通讯作者：
Ma, Lei
中科院分区：
文献类型：
--
作者：
Wang, Jiaying;Wang, Yuanyong;Ma, Lei
口腔鳞状细胞癌（OSCC）是世界范围内最常见的恶性肿瘤之一，其发病率和死亡率近年来呈上升趋势。因此，本研究的目的是确定显着差异表达的基因（DEG）参与其发病机制，以获得新的生物标志物或潜在的治疗目标，口腔鳞癌。微阵列数据集GSE 85195、GSE 23558和GSE 10121的基因表达谱从Gene Expression Omnibus（GEO）数据库获得。在每个GEO数据集中筛选DEG后，获得249个OSCC组织的DEG。利用京都基因和基因组百科全书和基因本体论途径富集分析来探索上述DEG的生物学功能和途径。构建蛋白质-蛋白质相互作用网络以获得中心基因。从癌症基因组图谱（TCGA）中分析口腔癌患者相应的总生存信息。共筛选出与口腔癌患者生存率密切相关的6个候选基因（CXCL 10、OAS 2、IFIT 1、CCL 5、LRRK 2和PLAUR），并基于TCGA数据库对6个基因进行表达验证和总生存分析。时间依赖性受试者工作特征曲线分析可准确预测患者的总生存期。与此同时，这六个基因进一步验证了定量实时聚合酶链反应使用的样本从患者招募到本研究。本研究首次通过生物信息学分析确定了6个与口腔鳞癌预后相关的基因，这些基因有可能成为口腔鳞癌的潜在预后标志物，并为肿瘤的治疗提供潜在的靶点。
Oral squamous cell carcinoma (OSCC) is one of the most common types of malignancies worldwide, and its morbidity and mortality have increased in the near term. Consequently, the purpose of the present study was to identify the notable differentially expressed genes (DEGs) involved in their pathogenesis to obtain new biomarkers or potential therapeutic targets for OSCC. The gene expression profiles of the microarray datasets GSE85195, GSE23558, and GSE10121 were obtained from the Gene Expression Omnibus (GEO) database. After screening the DEGs in each GEO dataset, 249 DEGs in OSCC tissues were obtained. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathway enrichment analysis was employed to explore the biological functions and pathways of the above DEGs. A protein-protein interaction network was constructed to obtain a central gene. The corresponding total survival information was analyzed in patients with oral cancer from The Cancer Genome Atlas (TCGA). A total of six candidate genes (CXCL10, OAS2, IFIT1, CCL5, LRRK2, and PLAUR) closely related to the survival rate of patients with oral cancer were identified, and expression verification and overall survival analysis of six genes were performed based on TCGA database. Time-dependent receiver operating characteristic curve analysis yields predictive accuracy of the patient's overall survival. At the same time, the six genes were further verified by quantitative real-time polymerase chain reaction using samples obtained from the patients recruited to the present study. In conclusion, the present study identified the prognostic signature of six genes in OSCC for the first time via comprehensive bioinformatics analysis, which could become potential prognostic markers for OCSS and may provide potential therapeutic targets for tumors.