Cargando…
Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis
Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733258/ https://www.ncbi.nlm.nih.gov/pubmed/31534853 http://dx.doi.org/10.7717/peerj.7619 |
_version_ | 1783449950854578176 |
---|---|
author | Li, Chuanfei Qin, Feng Hong, Hao Tang, Hui Jiang, Xiaoling Yang, Shuangyan Mei, Zhechuan Zhou, Di |
author_facet | Li, Chuanfei Qin, Feng Hong, Hao Tang, Hui Jiang, Xiaoling Yang, Shuangyan Mei, Zhechuan Zhou, Di |
author_sort | Li, Chuanfei |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment. |
format | Online Article Text |
id | pubmed-6733258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67332582019-09-18 Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis Li, Chuanfei Qin, Feng Hong, Hao Tang, Hui Jiang, Xiaoling Yang, Shuangyan Mei, Zhechuan Zhou, Di PeerJ Bioinformatics Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment. PeerJ Inc. 2019-09-06 /pmc/articles/PMC6733258/ /pubmed/31534853 http://dx.doi.org/10.7717/peerj.7619 Text en ©2019 Li et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Li, Chuanfei Qin, Feng Hong, Hao Tang, Hui Jiang, Xiaoling Yang, Shuangyan Mei, Zhechuan Zhou, Di Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title | Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title_full | Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title_fullStr | Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title_full_unstemmed | Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title_short | Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
title_sort | identification of flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733258/ https://www.ncbi.nlm.nih.gov/pubmed/31534853 http://dx.doi.org/10.7717/peerj.7619 |
work_keys_str_mv | AT lichuanfei identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT qinfeng identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT honghao identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT tanghui identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT jiangxiaoling identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT yangshuangyan identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT meizhechuan identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis AT zhoudi identificationofflapendonuclease1asapotentialcoregeneinhepatocellularcarcinomabyintegratedbioinformaticsanalysis |