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肝脏再生的综合研究:一项荟萃分析和系统生物学方法

A comprehensive investigation on liver regeneration: a meta-analysis and systems biology approach.

作者信息

Asnaashari Solmaz, Amjad Elham, Sokouti Babak

机构信息

Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

出版信息

Clin Exp Hepatol. 2021 Jun;7(2):183-190. doi: 10.5114/ceh.2021.107564. Epub 2021 Jun 30.

Abstract

AIM OF THE STUDY

Liver regeneration is one of the essential fields of regenerative medicine as a branch of tissue engineering and molecular biology that draws global researchers' attention. This study aims to conduct a systematic review and meta-analysis on the high-throughput gene expression microarray dataset of liver regeneration on the NCBI-GEO database to identify the significant genes and signaling pathways and confirm the genes from literature studies on associated diseases.

MATERIAL AND METHODS

We thoroughly searched the NCBI-GEO database to retrieve and screen the GEO microarray datasets' contents. Due to the inclusion of different species in eligible GEO datasets in the meta-analysis, the list of significant genes for the random-effects model were identified. Moreover, we carried out detailed gene analyses for three main gene ontology components and the KEGG signaling pathway. Furthermore, we investigated the possibility of genes' association with liver cancer through the Kaplan-Meier plot.

RESULTS

The random-effects model from six eligible GEO datasets identified 71 genes with eight down-regulated and 63 up-regulated genes. The target genes are involved in various cellular functions such as cell proliferation, cell death, and cell cycle control. Finally, we noted that 58 out of 71 genes are associated with different types of diseases related explicitly to other liver and inflammation diseases.

CONCLUSIONS

The current study assessed various GEO datasets at the early stages of liver regeneration with promising results. The present systematic review and meta-analysis results are beneficial for future novel drug design and discovery specifically for patients in the liver transplantation process.

摘要

研究目的

肝脏再生作为组织工程和分子生物学分支的再生医学的重要领域之一,吸引了全球研究人员的关注。本研究旨在对NCBI - GEO数据库上肝脏再生的高通量基因表达微阵列数据集进行系统评价和荟萃分析,以识别重要基因和信号通路,并从相关疾病的文献研究中确认这些基因。

材料与方法

我们全面检索了NCBI - GEO数据库,以检索和筛选GEO微阵列数据集的内容。由于荟萃分析中纳入的合格GEO数据集中包含不同物种,因此确定了随机效应模型的重要基因列表。此外,我们对三个主要的基因本体组成部分和KEGG信号通路进行了详细的基因分析。此外,我们通过Kaplan - Meier图研究了基因与肝癌关联的可能性。

结果

来自六个合格GEO数据集的随机效应模型识别出71个基因,其中8个基因下调,63个基因上调。这些靶基因参与各种细胞功能,如细胞增殖、细胞死亡和细胞周期控制。最后,我们注意到71个基因中的58个与明确与其他肝脏和炎症疾病相关的不同类型疾病有关。

结论

本研究在肝脏再生的早期阶段评估了各种GEO数据集,取得了有前景的结果。目前的系统评价和荟萃分析结果有利于未来新型药物的设计和发现,特别是对于肝移植过程中的患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcb0/8284170/19c7e48e89a9/CEH-7-44626-g001.jpg

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