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Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer
Purpose: The expression and clinical value of zinc finger protein 2 gene (ZIC2) in hepatocellular carcinoma (HCC) were analyzed by mining gene information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods: Gene chip data sets were retrieved from GEO and TCGA an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823187/ https://www.ncbi.nlm.nih.gov/pubmed/33439969 http://dx.doi.org/10.1042/BSR20203115 |
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author | Sun, Lei Lin, Yaru Wang, Guichun Zhang, Lin Hu, Liangchang Lu, Zhong |
author_facet | Sun, Lei Lin, Yaru Wang, Guichun Zhang, Lin Hu, Liangchang Lu, Zhong |
author_sort | Sun, Lei |
collection | PubMed |
description | Purpose: The expression and clinical value of zinc finger protein 2 gene (ZIC2) in hepatocellular carcinoma (HCC) were analyzed by mining gene information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods: Gene chip data sets were retrieved from GEO and TCGA and screened for differentially expressed genes in HCC. Gene expression profile interaction analysis (GEPIA) and Kaplan–Meier curves were used to analyze the relationship between differentially expressed genes (DEGs) and survival and prognosis in patients with HCC. Moreover, the Genecards database was used to extract ZIC2-related proteins and to analyze the physiological process of protein enrichment. Furthermore, the relationships between ZIC2 gene and tumor cell immune invasion and that between immune cell infiltration and the 5-year survival rate were studied using the tumor immune evaluation resource (TIMER) database. Results: Datasets from GEO and TCGA revealed that ZIC2 was differentially expressed in HCC tissues and normal tissues (P<0.05). High ZIC2 expression was associated with overall survival (OS) and progress-free survival in HCC patients. Overall, 25 ZIC2 related proteins, including Gli3, PRKDC, and rnf180 were identified and protein enrichment analysis indicated these were associated with four types of cell components, six types of cell functions, and eight types of biological processes. ZIC2 was positively correlated with immune infiltration cells in patients with HCC, and higher expression of ZIC2 mRNA CD4+T cells is associated with a better 5-year survival. Conclusion: ZIC2 gene may be used as an immune response marker in liver cancer to predict the prognosis of HCC. |
format | Online Article Text |
id | pubmed-7823187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78231872021-02-04 Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer Sun, Lei Lin, Yaru Wang, Guichun Zhang, Lin Hu, Liangchang Lu, Zhong Biosci Rep Bioinformatics Purpose: The expression and clinical value of zinc finger protein 2 gene (ZIC2) in hepatocellular carcinoma (HCC) were analyzed by mining gene information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods: Gene chip data sets were retrieved from GEO and TCGA and screened for differentially expressed genes in HCC. Gene expression profile interaction analysis (GEPIA) and Kaplan–Meier curves were used to analyze the relationship between differentially expressed genes (DEGs) and survival and prognosis in patients with HCC. Moreover, the Genecards database was used to extract ZIC2-related proteins and to analyze the physiological process of protein enrichment. Furthermore, the relationships between ZIC2 gene and tumor cell immune invasion and that between immune cell infiltration and the 5-year survival rate were studied using the tumor immune evaluation resource (TIMER) database. Results: Datasets from GEO and TCGA revealed that ZIC2 was differentially expressed in HCC tissues and normal tissues (P<0.05). High ZIC2 expression was associated with overall survival (OS) and progress-free survival in HCC patients. Overall, 25 ZIC2 related proteins, including Gli3, PRKDC, and rnf180 were identified and protein enrichment analysis indicated these were associated with four types of cell components, six types of cell functions, and eight types of biological processes. ZIC2 was positively correlated with immune infiltration cells in patients with HCC, and higher expression of ZIC2 mRNA CD4+T cells is associated with a better 5-year survival. Conclusion: ZIC2 gene may be used as an immune response marker in liver cancer to predict the prognosis of HCC. Portland Press Ltd. 2021-01-22 /pmc/articles/PMC7823187/ /pubmed/33439969 http://dx.doi.org/10.1042/BSR20203115 Text en © 2021 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Bioinformatics Sun, Lei Lin, Yaru Wang, Guichun Zhang, Lin Hu, Liangchang Lu, Zhong Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title | Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title_full | Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title_fullStr | Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title_full_unstemmed | Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title_short | Correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
title_sort | correlation of zinc finger protein 2, a prognostic biomarker, with immune infiltrates in liver cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823187/ https://www.ncbi.nlm.nih.gov/pubmed/33439969 http://dx.doi.org/10.1042/BSR20203115 |
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