Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

Background Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer. Methods One mRNA dataset (GSE28739) and one miRNA dataset (GSE25...

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Autores principales:	Wenwen Wang, Wenwen Zhang, Yuanjing Hu
Formato:	article
Lenguaje:	EN
Publicado:	PeerJ Inc. 2021
Materias:	Ovarian cancer Platinum resistance Hub genes Expression profiling data Medicine R
Acceso en línea:	https://doaj.org/article/773418419bdc4798bf760d3905cc26d8
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spelling	oai:doaj.org-article:773418419bdc4798bf760d3905cc26d82021-11-10T15:05:07ZIdentification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer10.7717/peerj.123532167-8359https://doaj.org/article/773418419bdc4798bf760d3905cc26d82021-11-01T00:00:00Zhttps://peerj.com/articles/12353.pdfhttps://peerj.com/articles/12353/https://doaj.org/toc/2167-8359Background Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer. Methods One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein–protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software. Results A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494. Conclusions The TF-miRNA–mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.Wenwen WangWenwen ZhangYuanjing HuPeerJ Inc.articleOvarian cancerPlatinum resistanceHub genesExpression profiling dataMedicineRENPeerJ, Vol 9, p e12353 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ovarian cancer Platinum resistance Hub genes Expression profiling data Medicine R
spellingShingle	Ovarian cancer Platinum resistance Hub genes Expression profiling data Medicine R Wenwen Wang Wenwen Zhang Yuanjing Hu Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
description	Background Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer. Methods One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein–protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software. Results A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494. Conclusions The TF-miRNA–mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.
format	article
author	Wenwen Wang Wenwen Zhang Yuanjing Hu
author_facet	Wenwen Wang Wenwen Zhang Yuanjing Hu
author_sort	Wenwen Wang
title	Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
title_short	Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
title_full	Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
title_fullStr	Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
title_full_unstemmed	Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer
title_sort	identification of keygenes, mirnas and mirna-mrna regulatory pathways for chemotherapy resistance in ovarian cancer
publisher	PeerJ Inc.
publishDate	2021
url	https://doaj.org/article/773418419bdc4798bf760d3905cc26d8
work_keys_str_mv	AT wenwenwang identificationofkeygenesmirnasandmirnamrnaregulatorypathwaysforchemotherapyresistanceinovariancancer AT wenwenzhang identificationofkeygenesmirnasandmirnamrnaregulatorypathwaysforchemotherapyresistanceinovariancancer AT yuanjinghu identificationofkeygenesmirnasandmirnamrnaregulatorypathwaysforchemotherapyresistanceinovariancancer
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Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

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