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Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data
Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003274/ https://www.ncbi.nlm.nih.gov/pubmed/32047816 http://dx.doi.org/10.1155/2020/8283401 |
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author | Xu, Yingkun Wu, Guangzhen Li, Jianyi Li, Jiatong Ruan, Ningke Ma, Liye Han, Xiaoyang Wei, Yanjun Li, Liang Zhang, Hongge Chen, Yougen Xia, Qinghua |
author_facet | Xu, Yingkun Wu, Guangzhen Li, Jianyi Li, Jiatong Ruan, Ningke Ma, Liye Han, Xiaoyang Wei, Yanjun Li, Liang Zhang, Hongge Chen, Yougen Xia, Qinghua |
author_sort | Xu, Yingkun |
collection | PubMed |
description | Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance. |
format | Online Article Text |
id | pubmed-7003274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-70032742020-02-11 Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data Xu, Yingkun Wu, Guangzhen Li, Jianyi Li, Jiatong Ruan, Ningke Ma, Liye Han, Xiaoyang Wei, Yanjun Li, Liang Zhang, Hongge Chen, Yougen Xia, Qinghua Biomed Res Int Research Article Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance. Hindawi 2020-01-23 /pmc/articles/PMC7003274/ /pubmed/32047816 http://dx.doi.org/10.1155/2020/8283401 Text en Copyright © 2020 Yingkun Xu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xu, Yingkun Wu, Guangzhen Li, Jianyi Li, Jiatong Ruan, Ningke Ma, Liye Han, Xiaoyang Wei, Yanjun Li, Liang Zhang, Hongge Chen, Yougen Xia, Qinghua Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title | Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title_full | Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title_fullStr | Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title_full_unstemmed | Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title_short | Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data |
title_sort | screening and identification of key biomarkers for bladder cancer: a study based on tcga and geo data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003274/ https://www.ncbi.nlm.nih.gov/pubmed/32047816 http://dx.doi.org/10.1155/2020/8283401 |
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