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Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma
Objective: Lung adenocarcinoma (LUAD) is a common malignant tumor with a poor prognosis. The present study aimed to screen the key genes involved in LUAD development and prognosis. Methods: The transcriptome data for 515 LUAD and 347 normal samples were downloaded from The Cancer Genome Atlas and Ge...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9158403/ https://www.ncbi.nlm.nih.gov/pubmed/35635202 http://dx.doi.org/10.1177/00469580221096259 |
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author | Luo, Xuan Xu, Jian Guo Wang, ZhiYuan Wang, XiaoFang Zhu, QianYing Zhao, Juan Bian, Li |
author_facet | Luo, Xuan Xu, Jian Guo Wang, ZhiYuan Wang, XiaoFang Zhu, QianYing Zhao, Juan Bian, Li |
author_sort | Luo, Xuan |
collection | PubMed |
description | Objective: Lung adenocarcinoma (LUAD) is a common malignant tumor with a poor prognosis. The present study aimed to screen the key genes involved in LUAD development and prognosis. Methods: The transcriptome data for 515 LUAD and 347 normal samples were downloaded from The Cancer Genome Atlas and Genotype Tissue Expression databases. The weighted gene co-expression network and differentially expressed genes were used to identify the central regulatory genes for the development of LUAD. Univariate Cox, LASSO, and multivariate Cox regression analyses were utilized to identify prognosis-related genes. Results: The top 10 central regulatory genes of LUAD included IL6, PECAM1, CDH5, VWF, THBS1, CAV1, TEK, HGF, SPP1, and ENG. Genes that have an impact on survival included PECAM1, HGF, SPP1, and ENG. The favorable prognosis genes included KDF1, ZNF691, DNASE2B, and ELAPOR1, while unfavorable prognosis genes included RPL22, ENO1, PCSK9, SNX7, and LCE5A. The areas under the receiver operating characteristic curves of the risk score model in the training and testing datasets were .78 and .758, respectively. Conclusion: Bioinformatics methods were used to identify genes involved in the development and prognosis of LUAD, which will provide a basis for further research on the treatment and prognosis of LUAD. |
format | Online Article Text |
id | pubmed-9158403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-91584032022-06-02 Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma Luo, Xuan Xu, Jian Guo Wang, ZhiYuan Wang, XiaoFang Zhu, QianYing Zhao, Juan Bian, Li Inquiry Original Research Article Objective: Lung adenocarcinoma (LUAD) is a common malignant tumor with a poor prognosis. The present study aimed to screen the key genes involved in LUAD development and prognosis. Methods: The transcriptome data for 515 LUAD and 347 normal samples were downloaded from The Cancer Genome Atlas and Genotype Tissue Expression databases. The weighted gene co-expression network and differentially expressed genes were used to identify the central regulatory genes for the development of LUAD. Univariate Cox, LASSO, and multivariate Cox regression analyses were utilized to identify prognosis-related genes. Results: The top 10 central regulatory genes of LUAD included IL6, PECAM1, CDH5, VWF, THBS1, CAV1, TEK, HGF, SPP1, and ENG. Genes that have an impact on survival included PECAM1, HGF, SPP1, and ENG. The favorable prognosis genes included KDF1, ZNF691, DNASE2B, and ELAPOR1, while unfavorable prognosis genes included RPL22, ENO1, PCSK9, SNX7, and LCE5A. The areas under the receiver operating characteristic curves of the risk score model in the training and testing datasets were .78 and .758, respectively. Conclusion: Bioinformatics methods were used to identify genes involved in the development and prognosis of LUAD, which will provide a basis for further research on the treatment and prognosis of LUAD. SAGE Publications 2022-05-30 /pmc/articles/PMC9158403/ /pubmed/35635202 http://dx.doi.org/10.1177/00469580221096259 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Article Luo, Xuan Xu, Jian Guo Wang, ZhiYuan Wang, XiaoFang Zhu, QianYing Zhao, Juan Bian, Li Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title | Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title_full | Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title_fullStr | Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title_full_unstemmed | Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title_short | Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma |
title_sort | bioinformatics identification of key genes for the development and prognosis of lung adenocarcinoma |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9158403/ https://www.ncbi.nlm.nih.gov/pubmed/35635202 http://dx.doi.org/10.1177/00469580221096259 |
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