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基于转录因子预后系统的人骨髓间充质干细胞成骨分化相关关键转录因子-基因调控网络的鉴定

Identification of key transcription factors - gene regulatory network related with osteogenic differentiation of human mesenchymal stem cells based on transcription factor prognosis system.

作者信息

Kang Xuefeng, Sun Yong, Zhang Zhao

机构信息

Department of Orthopedics, Heilongjiang Provincial Hospital, Harbin, Heilongjiang 150030, P.R. China.

出版信息

Exp Ther Med. 2019 Mar;17(3):2113-2122. doi: 10.3892/etm.2019.7170. Epub 2019 Jan 14.

DOI:10.3892/etm.2019.7170
PMID:30783479
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6364222/
Abstract

Human mesenchymal stem cells (hMSCs) have the capacity to differentiate into fabricate cartilage, muscle, marrow stroma, tendon/ligament, fat, and other connective tissues, providing a potential source for tissue regeneration. The aim of this study was to find the key transcription factors (TFs), which regulated osteogenic differentiation of hMSCs. In this study, three methods were performed to find the key TFs, which included enrichment analysis, direct impact value and indirect impact value. We used the patient and public involvements (PPI) network to integrate the results of the above methods for analysis. Then, we compared the osteoblast data to the control group on days 1, 3 and 7. Finally, we found the combination of the optimal and vital 30 TFs related to osteogenic differentiation. TFs FOS, SOX9 and EP300 were commonly expressed in 3 different days in the osteogenic lineages and presented in the PPI network at relatively high degrees. Moreover, TFs CREBBP, ESR1 and EGR1 also presented high effects on the 1st, 3rd and 7th day. The constructed network gives us a more comprehensive understanding of the mechanism of osteogenesis of hMSCs.

摘要

人间充质干细胞(hMSCs)具有分化形成软骨、肌肉、骨髓基质、肌腱/韧带、脂肪及其他结缔组织的能力,为组织再生提供了潜在来源。本研究的目的是寻找调控hMSCs成骨分化的关键转录因子(TFs)。在本研究中,采用了三种方法来寻找关键TFs,包括富集分析、直接影响值和间接影响值。我们利用患者和公众参与(PPI)网络整合上述方法的结果进行分析。然后,我们在第1、3和7天将成骨细胞数据与对照组进行比较。最后,我们发现了与成骨分化相关的30个最佳且关键的TFs组合。TFs FOS、SOX9和EP300在成骨谱系的3个不同时间点均有表达,且在PPI网络中呈现相对较高的度数。此外,TFs CREBBP、ESR1和EGR1在第1、3和7天也呈现出较高的影响。构建的网络使我们对hMSCs成骨机制有了更全面的了解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/6031360f2caa/etm-17-03-2113-g07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/c512e36219d9/etm-17-03-2113-g02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/8ecb7c889e24/etm-17-03-2113-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/dcb5fc5efa14/etm-17-03-2113-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/60cc0bd6a1af/etm-17-03-2113-g05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/ee5d478ca9e2/etm-17-03-2113-g06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/6031360f2caa/etm-17-03-2113-g07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/c512e36219d9/etm-17-03-2113-g02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/8ecb7c889e24/etm-17-03-2113-g03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/dcb5fc5efa14/etm-17-03-2113-g04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/60cc0bd6a1af/etm-17-03-2113-g05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/ee5d478ca9e2/etm-17-03-2113-g06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ddb/6364222/6031360f2caa/etm-17-03-2113-g07.jpg

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