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Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis
Hepatocellular carcinoma (HCC) is the most aggressive type of gastrointestinal tumor, with a high rate of mortality. However, identifying biomarkers for the treatment of HCC remains to be developed. We aimed to determine whether cell division cycle 25C (CDC25C) could be used as a novel diagnostic an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7607810/ https://www.ncbi.nlm.nih.gov/pubmed/33111630 http://dx.doi.org/10.1177/1533033820967474 |
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author | Xun, Ruifeng Lu, Hougen Wang, Xianwang |
author_facet | Xun, Ruifeng Lu, Hougen Wang, Xianwang |
author_sort | Xun, Ruifeng |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is the most aggressive type of gastrointestinal tumor, with a high rate of mortality. However, identifying biomarkers for the treatment of HCC remains to be developed. We aimed to determine whether cell division cycle 25C (CDC25C) could be used as a novel diagnostic and therapeutic biomarker in HCC. Expression of CDC25C in HCC was analyzed by using GEPIA (Gene Expression Profiling Interactive Analysis) and UALCAN databases. GEPIA and CBioPortal databases were applied to analyze patients’survival and CDC25C mutations, respectively. PPI (Protein-Protein Interaction) network was further built by STRING (Search Tool for the Retrieval of Interacting Genes) and Metascape Web portals. To the best of our knowledge, the novel observations identified in the present study reveal that the expression of CDC25C in HCC was significantly enhanced when compare to that in normal liver tissues (P < 0.001). A higher CDC25C expression resulted in a remarkably shorter disease free survival as well as overall survival. Moreover, the expression of CDC25C in HCC was related to HCC patients’grade and race, but not gender. The expression levels of CDC25C elevated gradually from stage 1 to 3 but decreased in stage 4. The specific gene mutations V41A, L87 H, N222 K and X309-splice of CDC25C occurred in HCC samples and these unique mutations were not detected in any other tumor tissues. Finally, PPI networks and GO enrichment analysis suggested that CDC25C might be associated with cell cycle and p53 signaling pathway. Taken together, bioinformatics analysis revealed that CDC25C might be a potential diagnostic predictor for HCC. |
format | Online Article Text |
id | pubmed-7607810 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-76078102020-11-13 Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis Xun, Ruifeng Lu, Hougen Wang, Xianwang Technol Cancer Res Treat Original Article Hepatocellular carcinoma (HCC) is the most aggressive type of gastrointestinal tumor, with a high rate of mortality. However, identifying biomarkers for the treatment of HCC remains to be developed. We aimed to determine whether cell division cycle 25C (CDC25C) could be used as a novel diagnostic and therapeutic biomarker in HCC. Expression of CDC25C in HCC was analyzed by using GEPIA (Gene Expression Profiling Interactive Analysis) and UALCAN databases. GEPIA and CBioPortal databases were applied to analyze patients’survival and CDC25C mutations, respectively. PPI (Protein-Protein Interaction) network was further built by STRING (Search Tool for the Retrieval of Interacting Genes) and Metascape Web portals. To the best of our knowledge, the novel observations identified in the present study reveal that the expression of CDC25C in HCC was significantly enhanced when compare to that in normal liver tissues (P < 0.001). A higher CDC25C expression resulted in a remarkably shorter disease free survival as well as overall survival. Moreover, the expression of CDC25C in HCC was related to HCC patients’grade and race, but not gender. The expression levels of CDC25C elevated gradually from stage 1 to 3 but decreased in stage 4. The specific gene mutations V41A, L87 H, N222 K and X309-splice of CDC25C occurred in HCC samples and these unique mutations were not detected in any other tumor tissues. Finally, PPI networks and GO enrichment analysis suggested that CDC25C might be associated with cell cycle and p53 signaling pathway. Taken together, bioinformatics analysis revealed that CDC25C might be a potential diagnostic predictor for HCC. SAGE Publications 2020-10-28 /pmc/articles/PMC7607810/ /pubmed/33111630 http://dx.doi.org/10.1177/1533033820967474 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Xun, Ruifeng Lu, Hougen Wang, Xianwang Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title | Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title_full | Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title_fullStr | Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title_full_unstemmed | Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title_short | Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis |
title_sort | identification of cdc25c as a potential biomarker in hepatocellular carcinoma using bioinformatics analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7607810/ https://www.ncbi.nlm.nih.gov/pubmed/33111630 http://dx.doi.org/10.1177/1533033820967474 |
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