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Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR wer...

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Autores principales: Liu, Shui, Yao, Xiaoxiao, Zhang, Dan, Sheng, Jiyao, Wen, Xin, Wang, Qingyu, Chen, Gaoyang, Li, Zhaoyan, Du, Zhenwu, Zhang, Xuewen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136478/
https://www.ncbi.nlm.nih.gov/pubmed/30228980
http://dx.doi.org/10.1155/2018/1431396
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author Liu, Shui
Yao, Xiaoxiao
Zhang, Dan
Sheng, Jiyao
Wen, Xin
Wang, Qingyu
Chen, Gaoyang
Li, Zhaoyan
Du, Zhenwu
Zhang, Xuewen
author_facet Liu, Shui
Yao, Xiaoxiao
Zhang, Dan
Sheng, Jiyao
Wen, Xin
Wang, Qingyu
Chen, Gaoyang
Li, Zhaoyan
Du, Zhenwu
Zhang, Xuewen
author_sort Liu, Shui
collection PubMed
description Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.
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spelling pubmed-61364782018-09-18 Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma Liu, Shui Yao, Xiaoxiao Zhang, Dan Sheng, Jiyao Wen, Xin Wang, Qingyu Chen, Gaoyang Li, Zhaoyan Du, Zhenwu Zhang, Xuewen Biomed Res Int Research Article Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC. Hindawi 2018-08-29 /pmc/articles/PMC6136478/ /pubmed/30228980 http://dx.doi.org/10.1155/2018/1431396 Text en Copyright © 2018 Shui Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Shui
Yao, Xiaoxiao
Zhang, Dan
Sheng, Jiyao
Wen, Xin
Wang, Qingyu
Chen, Gaoyang
Li, Zhaoyan
Du, Zhenwu
Zhang, Xuewen
Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title_full Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title_fullStr Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title_full_unstemmed Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title_short Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma
title_sort analysis of transcription factor-related regulatory networks based on bioinformatics analysis and validation in hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136478/
https://www.ncbi.nlm.nih.gov/pubmed/30228980
http://dx.doi.org/10.1155/2018/1431396
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