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转录组学数据挖掘以发现头部和部状细胞癌的特征基因:基于生物信息学分析和RNA测序的验证

Wenjie Yu^1,2, Xiaoling He^1,2, Chunming Zhang^1,2

¹First School of Clinical Medcine, Shanxi Medical University Taiyuan 030001, Shanxi, China.

American journal of cancer research

|December 7, 2023

概括

用四个关键基因开发了一种新的头支状细胞癌 (HNSC) 诊断和预后模型:UBE2C,BUB1B,MCM4和KIF23. 该模型旨在改善HNSC患者的疾病管理.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

头部和部状细胞癌 (HNSC) 呈现异质性和不良预后,需要新的诊断和预后工具.
对HNSC的有效疾病管理需要改进早期检测和预测结果的模型.

研究的目的:

确定HNSC.的新型诊断和预后生物标志物.
开发和验证使用已识别的生物标志物对HNSC患者进行预测模型.

主要方法:

使用干实验室 (对GEO数据集GSE6631的生物信息分析) 和湿实验室 (细胞系和临床样本中的验证) 方法.
采用R语言"limma"包用于差异基因表达分析和Cytohubba用于枢纽基因识别.
使用TCGA,GEO数据集,HNSC组织和细胞系 (FaDu,HOK) 验证的枢纽基因表达.

主要成果:

从GSE6631数据集中确定了1372个差异表达基因 (DEG).
开发并验证了基于四个上调的枢纽基因的诊断和预后模型:UBE2C,BUB1B,MCM4和KIF23.
观察到枢纽基因表达和免疫细胞透之间的相关性,表明HNSC免疫疗法的潜力.

结论:

通过使用UBE2C,BUB1B,MCM4和KIF23.3成功开发了HNSC的新型诊断和预后模型.
鉴定到的枢纽基因和开发的模型显示了改善HNSC患者管理的前景.
建议进行进一步的实验研究,以验证该模型的临床效率.

关键词:

在HNSC中,HNSC是最重要的.生物标志物生物标志物基因中心基因枢纽免疫疗法免疫疗法

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