Cargando…
Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis
Chromophobe renal cell carcinoma (chRCC), the third most common histological subtype of RCC, comprises 5–7% of all RCC cases. The aim of the present study was to identify potential biomarkers for chRCC and to examine the underlying mechanisms. A total of 4 profile datasets were downloaded from the G...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607225/ https://www.ncbi.nlm.nih.gov/pubmed/31423244 http://dx.doi.org/10.3892/ol.2019.10476 |
_version_ | 1783432052549353472 |
---|---|
author | Wang, Sheng Yu, Zhi-Hong Chai, Ke-Qun |
author_facet | Wang, Sheng Yu, Zhi-Hong Chai, Ke-Qun |
author_sort | Wang, Sheng |
collection | PubMed |
description | Chromophobe renal cell carcinoma (chRCC), the third most common histological subtype of RCC, comprises 5–7% of all RCC cases. The aim of the present study was to identify potential biomarkers for chRCC and to examine the underlying mechanisms. A total of 4 profile datasets were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs were performed with the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed to predict hub genes. Hub gene expression within chRCC across multiple datasets, as well as overall survival, were investigated by utilizing the Oncomine platform and UALCAN dataset, separately. A total of 266 DEGs (88 upregulated genes and 168 downregulated genes) were identified from 4 profile datasets. Integrating the results from the PPI network, Oncomine platform and survival analysis, CFTR was screened as a key factor in the prognosis of chRCC. GO and KEGG analysis revealed that 266 DEGs were mainly enriched in 17 terms and 9 pathways. The present study identified key genes and potential molecular mechanisms underlying the development of chRCC, and CFTR may be a potential prognostic biomarker and novel therapeutic target for chRCC. |
format | Online Article Text |
id | pubmed-6607225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-66072252019-08-18 Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis Wang, Sheng Yu, Zhi-Hong Chai, Ke-Qun Oncol Lett Articles Chromophobe renal cell carcinoma (chRCC), the third most common histological subtype of RCC, comprises 5–7% of all RCC cases. The aim of the present study was to identify potential biomarkers for chRCC and to examine the underlying mechanisms. A total of 4 profile datasets were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs were performed with the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed to predict hub genes. Hub gene expression within chRCC across multiple datasets, as well as overall survival, were investigated by utilizing the Oncomine platform and UALCAN dataset, separately. A total of 266 DEGs (88 upregulated genes and 168 downregulated genes) were identified from 4 profile datasets. Integrating the results from the PPI network, Oncomine platform and survival analysis, CFTR was screened as a key factor in the prognosis of chRCC. GO and KEGG analysis revealed that 266 DEGs were mainly enriched in 17 terms and 9 pathways. The present study identified key genes and potential molecular mechanisms underlying the development of chRCC, and CFTR may be a potential prognostic biomarker and novel therapeutic target for chRCC. D.A. Spandidos 2019-08 2019-06-14 /pmc/articles/PMC6607225/ /pubmed/31423244 http://dx.doi.org/10.3892/ol.2019.10476 Text en Copyright: © Wang 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 Wang, Sheng Yu, Zhi-Hong Chai, Ke-Qun Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title | Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title_full | Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title_fullStr | Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title_full_unstemmed | Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title_short | Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
title_sort | identification of cftr as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607225/ https://www.ncbi.nlm.nih.gov/pubmed/31423244 http://dx.doi.org/10.3892/ol.2019.10476 |
work_keys_str_mv | AT wangsheng identificationofcftrasanovelkeygeneinchromophoberenalcellcarcinomathroughbioinformaticsanalysis AT yuzhihong identificationofcftrasanovelkeygeneinchromophoberenalcellcarcinomathroughbioinformaticsanalysis AT chaikequn identificationofcftrasanovelkeygeneinchromophoberenalcellcarcinomathroughbioinformaticsanalysis |