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Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin
The purpose of the present study was to identify the potential targets and markers for diagnosis, therapy and prognosis in patients with prolactinoma at the molecular level and to determine the therapeutic effects of genipin in prolactinoma. The gene expression profiles of GSE2175, GSE26966 and GSE3...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691206/ https://www.ncbi.nlm.nih.gov/pubmed/31322266 http://dx.doi.org/10.3892/mmr.2019.10505 |
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author | Zhong, Sheng Wu, Bo Wang, Xinhui Sun, Dandan Liu, Daqun Jiang, Shanshan Ge, Junliang Zhang, Yuan Liu, Xinrui Zhou, Xiaoli Jin, Rihua Chen, Yong |
author_facet | Zhong, Sheng Wu, Bo Wang, Xinhui Sun, Dandan Liu, Daqun Jiang, Shanshan Ge, Junliang Zhang, Yuan Liu, Xinrui Zhou, Xiaoli Jin, Rihua Chen, Yong |
author_sort | Zhong, Sheng |
collection | PubMed |
description | The purpose of the present study was to identify the potential targets and markers for diagnosis, therapy and prognosis in patients with prolactinoma at the molecular level and to determine the therapeutic effects of genipin in prolactinoma. The gene expression profiles of GSE2175, GSE26966 and GSE36314 were obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified after comparing between gene expression profiles of the prolactinoma tissues and normal tissues. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network analysis were conducted. In addition, in vitro, scratch assay, colony-forming assay, Cell Counting Kit 8 (CCK8) assay and flow cytometry were performed to verify the functional effects of genipin. An aggregate of 12,695, 3,847 and 5,310 DEGs were identified from GSE2175, GSE26966 and GSE36314, respectively. The results of GO and KEGG analysis showed that the DEGs significant and important for prolactinoma were mostly involved with ‘spindle pole’ and ‘oocyte meiosis’. A total of 20 genes were selected as hub genes with high degrees after PPI network analysis, including mitogen-activated protein kinase 1 (MAPK1), MYC, early growth response 1 (EGR1), Bcl2 and calmodulin 1 (CALM1). CCK8 assay, colony-forming assay and scratch assay were performed to verify the anti-prolactinoma effect of genipin. The results of flow cytometry showed that apoptosis was increased by genipin. MAPK1, MYC, EGR1, Bcl2 and CALM1 were screened as main hub genes. Genipin upregulated the expression level of EGR1 and p21 (downstream mediator of EGR1) and EGR1, inhibited the proliferation and migration of prolactinoma cells. Genipin is a promising drug for treatment of patients with prolactinoma. |
format | Online Article Text |
id | pubmed-6691206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-66912062019-08-19 Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin Zhong, Sheng Wu, Bo Wang, Xinhui Sun, Dandan Liu, Daqun Jiang, Shanshan Ge, Junliang Zhang, Yuan Liu, Xinrui Zhou, Xiaoli Jin, Rihua Chen, Yong Mol Med Rep Articles The purpose of the present study was to identify the potential targets and markers for diagnosis, therapy and prognosis in patients with prolactinoma at the molecular level and to determine the therapeutic effects of genipin in prolactinoma. The gene expression profiles of GSE2175, GSE26966 and GSE36314 were obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified after comparing between gene expression profiles of the prolactinoma tissues and normal tissues. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network analysis were conducted. In addition, in vitro, scratch assay, colony-forming assay, Cell Counting Kit 8 (CCK8) assay and flow cytometry were performed to verify the functional effects of genipin. An aggregate of 12,695, 3,847 and 5,310 DEGs were identified from GSE2175, GSE26966 and GSE36314, respectively. The results of GO and KEGG analysis showed that the DEGs significant and important for prolactinoma were mostly involved with ‘spindle pole’ and ‘oocyte meiosis’. A total of 20 genes were selected as hub genes with high degrees after PPI network analysis, including mitogen-activated protein kinase 1 (MAPK1), MYC, early growth response 1 (EGR1), Bcl2 and calmodulin 1 (CALM1). CCK8 assay, colony-forming assay and scratch assay were performed to verify the anti-prolactinoma effect of genipin. The results of flow cytometry showed that apoptosis was increased by genipin. MAPK1, MYC, EGR1, Bcl2 and CALM1 were screened as main hub genes. Genipin upregulated the expression level of EGR1 and p21 (downstream mediator of EGR1) and EGR1, inhibited the proliferation and migration of prolactinoma cells. Genipin is a promising drug for treatment of patients with prolactinoma. D.A. Spandidos 2019-09 2019-07-18 /pmc/articles/PMC6691206/ /pubmed/31322266 http://dx.doi.org/10.3892/mmr.2019.10505 Text en Copyright: © Zhong et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Zhong, Sheng Wu, Bo Wang, Xinhui Sun, Dandan Liu, Daqun Jiang, Shanshan Ge, Junliang Zhang, Yuan Liu, Xinrui Zhou, Xiaoli Jin, Rihua Chen, Yong Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title | Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title_full | Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title_fullStr | Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title_full_unstemmed | Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title_short | Identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
title_sort | identification of driver genes and key pathways of prolactinoma predicts the therapeutic effect of genipin |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691206/ https://www.ncbi.nlm.nih.gov/pubmed/31322266 http://dx.doi.org/10.3892/mmr.2019.10505 |
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