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Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network
Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108999/ https://www.ncbi.nlm.nih.gov/pubmed/32196072 http://dx.doi.org/10.1042/BSR20200295 |
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author | Xu, Zihao Wu, Zilong Xu, Jiatang Zhang, Jingtao Yu, Bentong |
author_facet | Xu, Zihao Wu, Zilong Xu, Jiatang Zhang, Jingtao Yu, Bentong |
author_sort | Xu, Zihao |
collection | PubMed |
description | Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein–protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells’ infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker. |
format | Online Article Text |
id | pubmed-7108999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71089992020-04-08 Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network Xu, Zihao Wu, Zilong Xu, Jiatang Zhang, Jingtao Yu, Bentong Biosci Rep Cancer Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein–protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells’ infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker. Portland Press Ltd. 2020-03-31 /pmc/articles/PMC7108999/ /pubmed/32196072 http://dx.doi.org/10.1042/BSR20200295 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 | Cancer Xu, Zihao Wu, Zilong Xu, Jiatang Zhang, Jingtao Yu, Bentong Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title | Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title_full | Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title_fullStr | Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title_full_unstemmed | Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title_short | Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network |
title_sort | identification of hub driving genes and regulators of lung adenocarcinoma based on the gene co-expression network |
topic | Cancer |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108999/ https://www.ncbi.nlm.nih.gov/pubmed/32196072 http://dx.doi.org/10.1042/BSR20200295 |
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