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Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis
To explore the gene modules and key genes of head and neck squamous cell carcinoma (HNSCC), a bioinformatics algorithm based on the gene co-expression network analysis was proposed in this study. Firstly, differentially expressed genes (DEGs) were identified and a gene co-expression network (i-GCN)...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717835/ https://www.ncbi.nlm.nih.gov/pubmed/33285674 http://dx.doi.org/10.1097/MD.0000000000022655 |
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author | Zhao, Qian Zhang, Yan Zhang, Xue Sun, Yeqing Lin, Zhengkui |
author_facet | Zhao, Qian Zhang, Yan Zhang, Xue Sun, Yeqing Lin, Zhengkui |
author_sort | Zhao, Qian |
collection | PubMed |
description | To explore the gene modules and key genes of head and neck squamous cell carcinoma (HNSCC), a bioinformatics algorithm based on the gene co-expression network analysis was proposed in this study. Firstly, differentially expressed genes (DEGs) were identified and a gene co-expression network (i-GCN) was constructed with Pearson correlation analysis. Then, the gene modules were identified with 5 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Gene Ontology (GO) analysis was used to annotate the biological pathways of the gene modules. Then, the key genes were identified with 2 methods, gene significance (GS) and PageRank algorithm. Moreover, we used the Disgenet database to search the related diseases of the key genes. Lastly, the online software onclnc was used to perform the survival analysis on the key genes and draw survival curves. There were 2600 up-regulated and 1547 down-regulated genes identified in HNSCC. An i-GCN was constructed with Pearson correlation analysis. Then, the i-GCN was divided into 9 gene modules. The result of association analysis showed that, sex was mainly related to mitosis and meiosis processes, event was mainly related to responding to interferons, viruses and T cell differentiation processes, T stage was mainly related to muscle development and contraction, regulation of protein transport activity processes, N stage was mainly related to mitosis and meiosis processes, while M stage was mainly related to responding to interferons and immune response processes. Lastly, 34 key genes were identified, such as CDKN2A, HOXA1, CDC7, PPL, EVPL, PXN, PDGFRB, CALD1, and NUSAP1. Among them, HOXA1, PXN, and NUSAP1 were negatively correlated with the survival prognosis. HOXA1, PXN, and NUSAP1 might play important roles in the progression of HNSCC and severed as potential biomarkers for future diagnosis. |
format | Online Article Text |
id | pubmed-7717835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-77178352020-12-07 Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis Zhao, Qian Zhang, Yan Zhang, Xue Sun, Yeqing Lin, Zhengkui Medicine (Baltimore) 5700 To explore the gene modules and key genes of head and neck squamous cell carcinoma (HNSCC), a bioinformatics algorithm based on the gene co-expression network analysis was proposed in this study. Firstly, differentially expressed genes (DEGs) were identified and a gene co-expression network (i-GCN) was constructed with Pearson correlation analysis. Then, the gene modules were identified with 5 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Gene Ontology (GO) analysis was used to annotate the biological pathways of the gene modules. Then, the key genes were identified with 2 methods, gene significance (GS) and PageRank algorithm. Moreover, we used the Disgenet database to search the related diseases of the key genes. Lastly, the online software onclnc was used to perform the survival analysis on the key genes and draw survival curves. There were 2600 up-regulated and 1547 down-regulated genes identified in HNSCC. An i-GCN was constructed with Pearson correlation analysis. Then, the i-GCN was divided into 9 gene modules. The result of association analysis showed that, sex was mainly related to mitosis and meiosis processes, event was mainly related to responding to interferons, viruses and T cell differentiation processes, T stage was mainly related to muscle development and contraction, regulation of protein transport activity processes, N stage was mainly related to mitosis and meiosis processes, while M stage was mainly related to responding to interferons and immune response processes. Lastly, 34 key genes were identified, such as CDKN2A, HOXA1, CDC7, PPL, EVPL, PXN, PDGFRB, CALD1, and NUSAP1. Among them, HOXA1, PXN, and NUSAP1 were negatively correlated with the survival prognosis. HOXA1, PXN, and NUSAP1 might play important roles in the progression of HNSCC and severed as potential biomarkers for future diagnosis. Lippincott Williams & Wilkins 2020-12-04 /pmc/articles/PMC7717835/ /pubmed/33285674 http://dx.doi.org/10.1097/MD.0000000000022655 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | 5700 Zhao, Qian Zhang, Yan Zhang, Xue Sun, Yeqing Lin, Zhengkui Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title | Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title_full | Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title_fullStr | Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title_full_unstemmed | Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title_short | Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
title_sort | mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis |
topic | 5700 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717835/ https://www.ncbi.nlm.nih.gov/pubmed/33285674 http://dx.doi.org/10.1097/MD.0000000000022655 |
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