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CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis
The mortality rate associated with hepatocellular carcinoma (HCC) is the third highest among all digestive system tumors. However, the causes of HCC development and the underlying mechanisms have remained to be fully elucidated. In the present bioinformatics study, genetic markers were identified an...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086186/ https://www.ncbi.nlm.nih.gov/pubmed/32256749 http://dx.doi.org/10.3892/etm.2020.8522 |
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author | Liu, Linglong Chen, Anning Chen, Siyu Song, Wei Yao, Qingmei Wang, Pengfei Zhou, Sufang |
author_facet | Liu, Linglong Chen, Anning Chen, Siyu Song, Wei Yao, Qingmei Wang, Pengfei Zhou, Sufang |
author_sort | Liu, Linglong |
collection | PubMed |
description | The mortality rate associated with hepatocellular carcinoma (HCC) is the third highest among all digestive system tumors. However, the causes of HCC development and the underlying mechanisms have remained to be fully elucidated. In the present bioinformatics study, genetic markers were identified and their association with HCC was determined. The mRNA expression datasets GSE87630, GSE74656 and GSE76427 were downloaded from the Gene Expression Omnibus (GEO) database. A total of 96 differentially expressed genes (DEGs) were screened from the 3 GEO datasets, including 25 upregulated and 71 downregulated genes. DEGs were uploaded to the database for Annotation, Visualization and Integrated Discovery to screen for enriched Gene Ontology terms in various categories and the Search Tool for the Retrieval of Interacting Genes/Proteins was used to identify the interactions and functions of the DEGs. A total of 3 genetic markers were identified in a stepwise pathway and functional analysis in a previous study. The association of the genetic markers with prognosis was analysed using the UALCAN online analysis tool. Regression analysis was also performed to identify the relationship between HCC grade and disease recurrence and the expression of genetic markers using The Cancer Genome Atlas HCC dataset. In addition, the expression of the 3 genetic markers in HCC tissues was determined using reverse transcription-quantitative PCR, the Oncomine database and the Human Protein Atlas database. The expression levels of the 3 genetic markers cyclin B2 (CCNB2), nucleolar and spindle-associated protein 1 (NUSAP1) and thymidine kinase 1 (TK1) were significantly correlated with each other and high mRNA expression of CCNB2 was significantly associated with poor overall survival of patients with HCC. Receiver operating characteristic curve analysis indicated that NUSAP1 and TK1 were capable of distinguishing between recurrent and non-recurrent HCC. Furthermore, CCNB2, NUSAP1 and TK1 were highly correlated with the HCC grade. It was also indicated that the mRNA expression of CCNB2, NUSAPA and TK1 was increased in primary HCC tissues when compared with that in adjacent tissues. The present study identified that the CCNB2, NUSAP1 and TK1 genes may serve as prognostic markers for HCC, and may be of value from the perspectives of basic research and clinical treatment of HCC. |
format | Online Article Text |
id | pubmed-7086186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-70861862020-04-02 CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis Liu, Linglong Chen, Anning Chen, Siyu Song, Wei Yao, Qingmei Wang, Pengfei Zhou, Sufang Exp Ther Med Articles The mortality rate associated with hepatocellular carcinoma (HCC) is the third highest among all digestive system tumors. However, the causes of HCC development and the underlying mechanisms have remained to be fully elucidated. In the present bioinformatics study, genetic markers were identified and their association with HCC was determined. The mRNA expression datasets GSE87630, GSE74656 and GSE76427 were downloaded from the Gene Expression Omnibus (GEO) database. A total of 96 differentially expressed genes (DEGs) were screened from the 3 GEO datasets, including 25 upregulated and 71 downregulated genes. DEGs were uploaded to the database for Annotation, Visualization and Integrated Discovery to screen for enriched Gene Ontology terms in various categories and the Search Tool for the Retrieval of Interacting Genes/Proteins was used to identify the interactions and functions of the DEGs. A total of 3 genetic markers were identified in a stepwise pathway and functional analysis in a previous study. The association of the genetic markers with prognosis was analysed using the UALCAN online analysis tool. Regression analysis was also performed to identify the relationship between HCC grade and disease recurrence and the expression of genetic markers using The Cancer Genome Atlas HCC dataset. In addition, the expression of the 3 genetic markers in HCC tissues was determined using reverse transcription-quantitative PCR, the Oncomine database and the Human Protein Atlas database. The expression levels of the 3 genetic markers cyclin B2 (CCNB2), nucleolar and spindle-associated protein 1 (NUSAP1) and thymidine kinase 1 (TK1) were significantly correlated with each other and high mRNA expression of CCNB2 was significantly associated with poor overall survival of patients with HCC. Receiver operating characteristic curve analysis indicated that NUSAP1 and TK1 were capable of distinguishing between recurrent and non-recurrent HCC. Furthermore, CCNB2, NUSAP1 and TK1 were highly correlated with the HCC grade. It was also indicated that the mRNA expression of CCNB2, NUSAPA and TK1 was increased in primary HCC tissues when compared with that in adjacent tissues. The present study identified that the CCNB2, NUSAP1 and TK1 genes may serve as prognostic markers for HCC, and may be of value from the perspectives of basic research and clinical treatment of HCC. D.A. Spandidos 2020-04 2020-02-11 /pmc/articles/PMC7086186/ /pubmed/32256749 http://dx.doi.org/10.3892/etm.2020.8522 Text en Copyright: © Liu 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 Liu, Linglong Chen, Anning Chen, Siyu Song, Wei Yao, Qingmei Wang, Pengfei Zhou, Sufang CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title | CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title_full | CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title_fullStr | CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title_full_unstemmed | CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title_short | CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
title_sort | ccnb2, nusap1 and tk1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086186/ https://www.ncbi.nlm.nih.gov/pubmed/32256749 http://dx.doi.org/10.3892/etm.2020.8522 |
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