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Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) datab...

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Autores principales: Zhou, Jun, Hui, Xiaoliang, Mao, Ying, Fan, Liya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680377/
https://www.ncbi.nlm.nih.gov/pubmed/31311829
http://dx.doi.org/10.1042/BSR20190625
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author Zhou, Jun
Hui, Xiaoliang
Mao, Ying
Fan, Liya
author_facet Zhou, Jun
Hui, Xiaoliang
Mao, Ying
Fan, Liya
author_sort Zhou, Jun
collection PubMed
description Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) in PDAC were obtained by using GEO2R, and overlapped DEGs were acquired with Venn Diagrams. Functional enrichment analysis of overlapped DEGs and DEmiRNAs was conducted with Metascape and FunRich, respectively. The protein–protein interaction (PPI) network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) of DEmiRNAs and hub genes were investigated by Kaplan–Meier (KM) plotter (KM plotter). Transcriptional data and correlation analyses among hub genes were verified through GEPIA and Human Protein Atlas (HPA). Additionally, miRNA targets were searched using miRTarBase, then miRNA–DEG regulatory network was visualized with Cytoscape. A total of 32 DEmiRNAs and 150 overlapped DEGs were identified, and Metascape showed that DEGs were significantly enriched in cellular chemical homeostasis and pathways in cancer, while DEmiRNAs were mainly enriched in signal transduction and Glypican pathway. Moreover, seven hub genes with a high degree, namely, V-myc avian myelocytomatosis viral oncogene homolog (MYC), solute carrier family 2 member 1 (SLC2A1), PKM, plasminogen activator, urokinase (PLAU), peroxisome proliferator activated receptor γ (PPARG), MET proto-oncogene, receptor tyrosine kinase (MET), and integrin subunit α 3 (ITGA3), were identified and found to be up-regulated between PDAC and normal tissues. miR-135b, miR-221, miR-21, miR-27a, miR-199b-5p, miR-143, miR-196a, miR-655, miR-455-3p, miR-744 and hub genes predicted poor OS of PDAC. An integrative bioinformatics analysis identified several hub genes that may serve as potential biomarkers or targets for early diagnosis and precision target treatment of PDAC.
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spelling pubmed-66803772019-08-23 Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis Zhou, Jun Hui, Xiaoliang Mao, Ying Fan, Liya Biosci Rep Research Articles Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) in PDAC were obtained by using GEO2R, and overlapped DEGs were acquired with Venn Diagrams. Functional enrichment analysis of overlapped DEGs and DEmiRNAs was conducted with Metascape and FunRich, respectively. The protein–protein interaction (PPI) network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) of DEmiRNAs and hub genes were investigated by Kaplan–Meier (KM) plotter (KM plotter). Transcriptional data and correlation analyses among hub genes were verified through GEPIA and Human Protein Atlas (HPA). Additionally, miRNA targets were searched using miRTarBase, then miRNA–DEG regulatory network was visualized with Cytoscape. A total of 32 DEmiRNAs and 150 overlapped DEGs were identified, and Metascape showed that DEGs were significantly enriched in cellular chemical homeostasis and pathways in cancer, while DEmiRNAs were mainly enriched in signal transduction and Glypican pathway. Moreover, seven hub genes with a high degree, namely, V-myc avian myelocytomatosis viral oncogene homolog (MYC), solute carrier family 2 member 1 (SLC2A1), PKM, plasminogen activator, urokinase (PLAU), peroxisome proliferator activated receptor γ (PPARG), MET proto-oncogene, receptor tyrosine kinase (MET), and integrin subunit α 3 (ITGA3), were identified and found to be up-regulated between PDAC and normal tissues. miR-135b, miR-221, miR-21, miR-27a, miR-199b-5p, miR-143, miR-196a, miR-655, miR-455-3p, miR-744 and hub genes predicted poor OS of PDAC. An integrative bioinformatics analysis identified several hub genes that may serve as potential biomarkers or targets for early diagnosis and precision target treatment of PDAC. Portland Press Ltd. 2019-08-02 /pmc/articles/PMC6680377/ /pubmed/31311829 http://dx.doi.org/10.1042/BSR20190625 Text en © 2019 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Articles
Zhou, Jun
Hui, Xiaoliang
Mao, Ying
Fan, Liya
Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title_full Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title_fullStr Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title_full_unstemmed Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title_short Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
title_sort identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680377/
https://www.ncbi.nlm.nih.gov/pubmed/31311829
http://dx.doi.org/10.1042/BSR20190625
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