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整合多项生物信息学研究以鉴定视网膜母细胞瘤中的 microRNA-靶基因-转录因子调控网络。

Integrated analysis of multiple bioinformatics studies to identify microRNA-target gene-transcription factor regulatory networks in retinoblastoma.

作者信息

Wen Yanjun, Zhu Maolin, Zhang Xuerui, Xiao Haodong, Wei Yan, Zhao Peiquan

机构信息

Department of Ophthalmology, Shanghai Xinhua Hospital, Affiliated to Medicine School of Shanghai Jiao Tong University, Shanghai, China.

Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, Shanghai, China.

出版信息

Transl Cancer Res. 2022 Jul;11(7):2225-2237. doi: 10.21037/tcr-21-1748.

Abstract

BACKGROUND

In children, retinoblastoma (RB) is one of the most common primary malignant ocular tumors and has a poor prognosis and high mortality. To understand the molecular mechanisms of RB, we identified microRNAs (miRNAs), key genes and transcription factors (TFs) using bioinformatics analysis to build potential miRNA-gene-TF networks.

METHODS

We collected three gene expression profiles and one miRNA expression profile from the Gene Expression Omnibus (GEO) database. We used the limma R package to identify overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs in RB tissues compared to noncancer tissues. The robust rank aggregation (RRA) method was implemented to identify key genes among the DEGs. Then, miRNA-key gene-TF networks were built using the online tools TransmiR and miRTarBase. Next, we used RT-qPCR to confirm the results.

RESULTS

We identified 180 DEGs in RB tissues compared to nontumor tissues using integrative analysis, among which 109 genes were upregulated and 71 were downregulated. Gene ontology (GO) analysis revealed that these DEGs were primarily involved with chromosome segregation, condensed chromosome and DNA replication origin binding. The most highly enriched pathways obtained in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were cell cycle, DNA replication, homologous recombination, P53 signaling pathway and pyrimidine metabolism. Furthermore, two key differentially expressed miRNAs (DEMs) were also established: let-7a and let-7b. Finally, the potential regulatory networks of miRNA-target gene-TFs were examined.

CONCLUSIONS

This study identified key genes and built miRNA-target gene-TF regulatory networks in RB, which will deepen our understanding of the molecular mechanisms involved in the development of RB. These key genes and miRNAs may be potential targets and biomarkers for RB diagnosis and therapy.

摘要

背景

在儿童中,视网膜母细胞瘤(RB)是最常见的原发性恶性眼肿瘤之一,预后较差且死亡率高。为了解RB的分子机制,我们使用生物信息学分析鉴定了 microRNA(miRNA)、关键基因和转录因子(TF),以构建潜在的 miRNA-基因-TF 网络。

方法

我们从基因表达综合数据库(GEO)收集了三个基因表达谱和一个 miRNA 表达谱。我们使用 limma R 包来鉴定与非癌组织相比,RB 组织中重叠的差异表达基因(DEG)和差异表达 miRNA。采用稳健秩聚合(RRA)方法在 DEG 中鉴定关键基因。然后,使用在线工具 TransmiR 和 miRTarBase 构建 miRNA-关键基因-TF 网络。接下来,我们使用 RT-qPCR 来确认结果。

结果

通过综合分析,我们鉴定出与非肿瘤组织相比,RB 组织中有 180 个 DEG,其中 109 个基因上调,71 个基因下调。基因本体(GO)分析表明,这些 DEG 主要参与染色体分离、浓缩染色体和 DNA 复制起点结合。京都基因与基因组百科全书(KEGG)通路分析中获得的最高度富集的通路是细胞周期、DNA 复制、同源重组、P53 信号通路和嘧啶代谢。此外,还确定了两个关键的差异表达 miRNA(DEM):let-7a 和 let-7b。最后,研究了 miRNA-靶基因-TF 的潜在调控网络。

结论

本研究鉴定了 RB 中的关键基因并构建了 miRNA-靶基因-TF 调控网络,这将加深我们对 RB 发生发展所涉及分子机制的理解。这些关键基因和 miRNA 可能是 RB 诊断和治疗的潜在靶点和生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ee/9372260/24a4fd3607d6/tcr-11-07-2225-f1.jpg

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