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Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods

The inhibitor of differentiation/DNA-binding (ID) is a member of the helix–loop–helix (HLH) transcription factor family, and plays a role in tumorigenesis, invasiveness and angiogenesis. The aims were to investigate the expression patterns and prognostic values of individual ID family members in lun...

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Autores principales: Xu, Suming, Wang, Yaoqin, Li, Yanhong, Zhang, Lei, Wang, Chunfang, Wu, Xueqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012656/
https://www.ncbi.nlm.nih.gov/pubmed/32003423
http://dx.doi.org/10.1042/BSR20193075
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author Xu, Suming
Wang, Yaoqin
Li, Yanhong
Zhang, Lei
Wang, Chunfang
Wu, Xueqing
author_facet Xu, Suming
Wang, Yaoqin
Li, Yanhong
Zhang, Lei
Wang, Chunfang
Wu, Xueqing
author_sort Xu, Suming
collection PubMed
description The inhibitor of differentiation/DNA-binding (ID) is a member of the helix–loop–helix (HLH) transcription factor family, and plays a role in tumorigenesis, invasiveness and angiogenesis. The aims were to investigate the expression patterns and prognostic values of individual ID family members in lung cancer, and the potential functional roles. The expression levels of ID family were assessed using the Oncomine online database and GEPIA database. Furthermore, the prognostic value of ID family members was evaluated using the Kaplan–Meier plotter database. The genetic mutations of ID family members were investigated using the cBioPortal database. Moreover, enrichment analysis was performed using STRING database and Funrich software. It was found that all the ID family members were significantly down-regulated in lung cancer. Prognostic results indicated that low mRNA expression levels of ID1 or increased mRNA expression levels of ID2/3/4 were associated with improved overall survival, first progression and post progression survival. Additionally, genetic mutations of ID family members were identified in lung cancer, and it was suggested that amplification and deep deletion were the main mutation types. Furthermore, functional enrichment analysis results suggested that ID1/2/4 were significantly enriched in ‘regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism’ for biological process, ‘transcription factor activity’ for molecular function and ‘HLH domain’ for protein domain. However, it was found that ID3 was not enriched in the above functions. The aberrant expression of ID family members may affect the occurrence and prognosis of lung cancer, and may be related to cell metabolism and transcriptional regulation.
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spelling pubmed-70126562020-02-21 Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods Xu, Suming Wang, Yaoqin Li, Yanhong Zhang, Lei Wang, Chunfang Wu, Xueqing Biosci Rep Bioinformatics The inhibitor of differentiation/DNA-binding (ID) is a member of the helix–loop–helix (HLH) transcription factor family, and plays a role in tumorigenesis, invasiveness and angiogenesis. The aims were to investigate the expression patterns and prognostic values of individual ID family members in lung cancer, and the potential functional roles. The expression levels of ID family were assessed using the Oncomine online database and GEPIA database. Furthermore, the prognostic value of ID family members was evaluated using the Kaplan–Meier plotter database. The genetic mutations of ID family members were investigated using the cBioPortal database. Moreover, enrichment analysis was performed using STRING database and Funrich software. It was found that all the ID family members were significantly down-regulated in lung cancer. Prognostic results indicated that low mRNA expression levels of ID1 or increased mRNA expression levels of ID2/3/4 were associated with improved overall survival, first progression and post progression survival. Additionally, genetic mutations of ID family members were identified in lung cancer, and it was suggested that amplification and deep deletion were the main mutation types. Furthermore, functional enrichment analysis results suggested that ID1/2/4 were significantly enriched in ‘regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism’ for biological process, ‘transcription factor activity’ for molecular function and ‘HLH domain’ for protein domain. However, it was found that ID3 was not enriched in the above functions. The aberrant expression of ID family members may affect the occurrence and prognosis of lung cancer, and may be related to cell metabolism and transcriptional regulation. Portland Press Ltd. 2020-02-11 /pmc/articles/PMC7012656/ /pubmed/32003423 http://dx.doi.org/10.1042/BSR20193075 Text en © 2020 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).
spellingShingle Bioinformatics
Xu, Suming
Wang, Yaoqin
Li, Yanhong
Zhang, Lei
Wang, Chunfang
Wu, Xueqing
Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title_full Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title_fullStr Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title_full_unstemmed Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title_short Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods
title_sort comprehensive analysis of inhibitor of differentiation/dna-binding gene family in lung cancer using bioinformatics methods
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012656/
https://www.ncbi.nlm.nih.gov/pubmed/32003423
http://dx.doi.org/10.1042/BSR20193075
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