基于GEO数据库的细胞癌中lncRNA介导的ceRNA网络的全面分析
Tianci Yang1,2, Yixuan Li1,2, Zhouhang Zheng1,2
1The Second Clinical Medical School, Lanzhou University, Lanzhou, China.
Medicine
|August 30, 2024
概括
这项研究通过构建一个 lncRNA-microRNA-messenger RNA (mRNA) 竞争的内源RNA (ceRNA) 网络来确定参与细胞癌 (RCC) 病原发生的关键长非编码RNA (lncRNA). 这些发现为RCC发展和潜在的治疗目标提供了洞察力.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 细胞癌 (RCC) 是癌症死亡的重要原因,病因不明.
- 长非编码RNAs (lncRNAs) 作为竞争的内源RNAs (ceRNAs) 起作用,调节基因表达并影响癌症的进展.
- 在RCC中lncRNA-miRNA-mRNA ceRNA网络的特定作用仍然在很大程度上是未知的.
研究的目的:
- 构建一个细胞癌特异的lncRNA-miRNA-mRNA ceRNA网络.
- 确定关键的差异表达lncRNAs (DElncRNAs),对于RCC启动和进展至关重要.
- 阐明已识别的ceRNA网络在RCC病变发生过程中的功能意义.
主要方法:
- 利用基因表达综合数据库中的转录组数据进行RCC分析.
- 采用Limma包用于识别差异表达基因 (DEG) 和重量基因共表达网络分析 (WGCNA) 关键的DElncRNAs.
- 预测的lncRNA-miRNA和miRNA-mRNA相互作用,使用分别的RNA交互分子和miRDB数据库的百科全书.
- 在癌症基因图谱 (TCGA) 数据库中验证了关键的DElncRNA相关基因表达和预后.
- 使用Cytoscape构建了ceRNA网络,并使用KEGG和GO进行了功能丰富分析.
主要成果:
- 在RCC组织中鉴定了286个DElncRNA,56个差异表达的miRNA和2065个DEmRNA.
- 通过WGCNA和相互作用数据库分析,确定了包括GAS6-AS1和MIAT在内的七个关键的DElncRNA.
- 构建了一个具有217个节点和463个边缘的全面的RCC特定ceRNA网络.
- 功能分析显示,在与癌症相关的途径中,DEmRNAs的丰富程度显著.
结论:
- 成功构建了一个新的RCC特定的lncRNA-miRNA-mRNA ceRNA网络.
- 确定了七个关键的DElncRNAs,可能在RCC发展中发挥关键作用.
- 这些发现为了解RCC病原体和开发向治疗提供了基础.
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