Cargando…

Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis

BACKGROUND: Patients with non‐small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5‐year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. METHODS: Differentially expressed genes (DEGs) were...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yongwen, Shi, Ruifeng, Zhu, Guangsheng, Chen, Chen, Huang, Hua, Gao, Min, Xu, Songlin, Cao, Peijun, Zhang, Zihe, Wu, Di, Li, Xuanguang, Liu, Hongyu, Chen, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720627/
https://www.ncbi.nlm.nih.gov/pubmed/34806315
http://dx.doi.org/10.1111/1759-7714.14226
_version_ 1784625163491344384
author Li, Yongwen
Shi, Ruifeng
Zhu, Guangsheng
Chen, Chen
Huang, Hua
Gao, Min
Xu, Songlin
Cao, Peijun
Zhang, Zihe
Wu, Di
Li, Xuanguang
Liu, Hongyu
Chen, Jun
author_facet Li, Yongwen
Shi, Ruifeng
Zhu, Guangsheng
Chen, Chen
Huang, Hua
Gao, Min
Xu, Songlin
Cao, Peijun
Zhang, Zihe
Wu, Di
Li, Xuanguang
Liu, Hongyu
Chen, Jun
author_sort Li, Yongwen
collection PubMed
description BACKGROUND: Patients with non‐small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5‐year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. METHODS: Differentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real‐time polymerase chain reaction (RT‐qPCR). The circular RNA–microRNA–messenger RNA (circRNA–miRNA–mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan–Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively. RESULTS: hsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT‐qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell‐cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival. CONCLUSION: Our study constructed a circRNA–miRNA–mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer.
format Online
Article
Text
id pubmed-8720627
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley & Sons Australia, Ltd
record_format MEDLINE/PubMed
spelling pubmed-87206272022-01-07 Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis Li, Yongwen Shi, Ruifeng Zhu, Guangsheng Chen, Chen Huang, Hua Gao, Min Xu, Songlin Cao, Peijun Zhang, Zihe Wu, Di Li, Xuanguang Liu, Hongyu Chen, Jun Thorac Cancer Original Articles BACKGROUND: Patients with non‐small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5‐year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. METHODS: Differentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real‐time polymerase chain reaction (RT‐qPCR). The circular RNA–microRNA–messenger RNA (circRNA–miRNA–mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan–Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively. RESULTS: hsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT‐qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell‐cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival. CONCLUSION: Our study constructed a circRNA–miRNA–mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer. John Wiley & Sons Australia, Ltd 2021-11-21 2022-01 /pmc/articles/PMC8720627/ /pubmed/34806315 http://dx.doi.org/10.1111/1759-7714.14226 Text en © 2021 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Li, Yongwen
Shi, Ruifeng
Zhu, Guangsheng
Chen, Chen
Huang, Hua
Gao, Min
Xu, Songlin
Cao, Peijun
Zhang, Zihe
Wu, Di
Li, Xuanguang
Liu, Hongyu
Chen, Jun
Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title_full Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title_fullStr Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title_full_unstemmed Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title_short Construction of a circular RNA–microRNA–messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
title_sort construction of a circular rna–microrna–messenger rna regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720627/
https://www.ncbi.nlm.nih.gov/pubmed/34806315
http://dx.doi.org/10.1111/1759-7714.14226
work_keys_str_mv AT liyongwen constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT shiruifeng constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT zhuguangsheng constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT chenchen constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT huanghua constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT gaomin constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT xusonglin constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT caopeijun constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT zhangzihe constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT wudi constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT lixuanguang constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT liuhongyu constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis
AT chenjun constructionofacircularrnamicrornamessengerrnaregulatorynetworkofhsacirc0043256inlungcancerbyintegratedanalysis