通过巨型数据生物信息学分析揭示鼻咽癌的新型预后生物标志物

Yishuai Tan, Jiao Zhou, Kai Liu, Ruowu Liu, Jing Zhou, Zhenru Wu, Linke Li, Jiaqi Zeng, Xuxian Feng, Biao Dong, Jintao Du
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引用次数: 0

摘要

鼻咽癌(NPC)通常在晚期才被确诊,在东南亚和中国东南部发病率较高。然而,由于公共数据库中鼻咽癌患者的生存数据有限,因此通过构建卡普兰-梅耶曲线来预测鼻咽癌生存期的研究不够严谨。这些研究主要依赖于有无病程生存(PFS)信息的鼻咽癌患者小样本,或几乎没有鼻咽癌患者的头颈部鳞状细胞癌(HNSCC)研究数据。因此,我们共同分析了从基因表达总库(GEO)数据库下载的11个数据集(46个正常人(对照组)与160个肿瘤(鼻咽癌))中的RNA表达谱,以及中山大学马骏提供的生存数据。然后,利用 STRING 数据库进行了差异分析、基因本体(GO)富集、京都基因组百科全书(KEGG)通路分析和网络分析。随后,筛选出了2142个上调差异表达基因(DEGs)和3857个下调差异表达基因(DEGs)。其中25个基因被鉴定为中枢基因,它们在多个通路(纤毛运动、细胞外基质结构成分、同源重组和细胞周期)中富集。利用我们从 GEO 数据库中收集的综合数据集,我们对 DEGs 进行了生存分析,并随后构建了生存模型。我们发现了七个 DEGs(RASGRP2、MOCOS、TTC9、ARHGAP4、DPM3、CD37 和 CD72)与鼻咽癌的生存预后密切相关。最后,通过 qRT-PCR、WB 和 IHC 检测证实,RASGRP2 表达升高,TTC9、CD37、DPM3 和 ARHGAP4 表达降低,这与 DEG 分析结果一致。最后,我们的研究结果通过巨型数据生物信息学分析为鼻咽癌的新型预后生物标志物提供了见解,这表明它们可能成为治疗鼻咽癌的特殊靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel prognostic biomarkers in nasopharyngeal carcinoma unveiled by mega-data bioinformatics analysis
Nasopharyngeal carcinoma (NPC) is commonly diagnosed at an advanced stage with a high incidence rate in Southeast Asia and Southeast China. However, the limited availability of NPC patient survival data in public databases has resulted in less rigorous studies examining the prediction of NPC survival through construction of Kaplan-Meier curves. These studies have primarily relied on small samples of NPC patients with progression-free survival (PFS) information or data from head and neck squamous cell carcinoma (HNSCC) studies almost without NPC patients. Thus, we coanalyzed RNA expression profiles in eleven datasets (46 normal (control) vs 160 tumor (NPC)) downloaded from the Gene Expression Omnibus (GEO) database and survival data provided by Jun Ma from Sun Yat-sen University. Then, differential analysis, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and network analysis were performed using STRING database. After that, 2142 upregulated differentially expressed genes (DEGs) and 3857 downregulated DEGs were screened. Twenty-five of them were identified as hub genes, which were enriched in several pathways (cilium movement, extracellular matrix structural constituent, homologous recombination and cell cycle). Utilizing the comprehensive dataset we amassed from GEO database, we conducted a survival analysis of DEGs and subsequently constructed survival models. Seven DEGs (RASGRP2, MOCOS, TTC9, ARHGAP4, DPM3, CD37, and CD72) were identified and closely related to the survival prognosis of NPC. Finally, qRT-PCR, WB and IHC were performed to confirm the elevated expression of RASGRP2 and the decreased expression of TTC9, CD37, DPM3 and ARHGAP4, consistent with the DEG analysis. Conclusively, our findings provide insights into the novel prognostic biomarkers of NPC by mega-data bioinformatics analysis, which suggests that they may serve special targets in the treatment of NPC.
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