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Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis

BACKGROUND: Genomic abnormality is a crucial factor for lung cancer development. This study used bioinformatics analysis to explore the hub genes involved in lung adenocarcinoma. METHODS: The GeneCards, Comparative Toxicogenomics Database (CTD), and DISEASES databases were used to screen the genes a...

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Autores principales: Zeng, Changyi, Zhou, You, Ye, Wanqing, Fang, Zihan, Wang, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641136/
https://www.ncbi.nlm.nih.gov/pubmed/36388051
http://dx.doi.org/10.21037/tcr-22-2225
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author Zeng, Changyi
Zhou, You
Ye, Wanqing
Fang, Zihan
Wang, Ke
author_facet Zeng, Changyi
Zhou, You
Ye, Wanqing
Fang, Zihan
Wang, Ke
author_sort Zeng, Changyi
collection PubMed
description BACKGROUND: Genomic abnormality is a crucial factor for lung cancer development. This study used bioinformatics analysis to explore the hub genes involved in lung adenocarcinoma. METHODS: The GeneCards, Comparative Toxicogenomics Database (CTD), and DISEASES databases were used to screen the genes associated with lung adenocarcinoma. The hub genes were then identified using WebGestalt. The Cancer Genome Atlas (TCGA), UALCAN, and the Human Protein Atlas (HPA) were used to validate the expression of hub genes. The predictive effects of hub genes on the risk of lung adenocarcinoma were evaluated using receiver operating characteristic (ROC) curve analysis. The Tumor-Immune System Interaction Database (TISIDB) was used to estimate the correlation between hub genes and immune infiltration. RESULTS: A total of 21 genes were defined as common genes associated with lung adenocarcinoma, and from these, AKT1, CD44, and CDKN2A were identified as hub genes. Significant differences in the hub gene mRNA and protein expression were observed between lung adenocarcinoma samples and normal samples derived from the TCGA and UALCAN databases. The area under the ROC curve (AUC) for AKT1, CD44, and CDKN2A in predicting lung adenocarcinoma risk was 0.847, 0.880, and 0.805, respectively, with sensitivity of 89.8%, 93.2%, and 94.9%, respectively. TISIDB analysis indicated that AKT1, CD44, and CDKN2A expression had a strong relationship with immune infiltration in lung adenocarcinoma. CONCLUSIONS: These hub genes, AKT1, CD44, and CDKN2A, may represent tumor biomarkers that may contribute to the understanding, diagnosis, and treatment of lung adenocarcinoma.
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spelling pubmed-96411362022-11-15 Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis Zeng, Changyi Zhou, You Ye, Wanqing Fang, Zihan Wang, Ke Transl Cancer Res Original Article BACKGROUND: Genomic abnormality is a crucial factor for lung cancer development. This study used bioinformatics analysis to explore the hub genes involved in lung adenocarcinoma. METHODS: The GeneCards, Comparative Toxicogenomics Database (CTD), and DISEASES databases were used to screen the genes associated with lung adenocarcinoma. The hub genes were then identified using WebGestalt. The Cancer Genome Atlas (TCGA), UALCAN, and the Human Protein Atlas (HPA) were used to validate the expression of hub genes. The predictive effects of hub genes on the risk of lung adenocarcinoma were evaluated using receiver operating characteristic (ROC) curve analysis. The Tumor-Immune System Interaction Database (TISIDB) was used to estimate the correlation between hub genes and immune infiltration. RESULTS: A total of 21 genes were defined as common genes associated with lung adenocarcinoma, and from these, AKT1, CD44, and CDKN2A were identified as hub genes. Significant differences in the hub gene mRNA and protein expression were observed between lung adenocarcinoma samples and normal samples derived from the TCGA and UALCAN databases. The area under the ROC curve (AUC) for AKT1, CD44, and CDKN2A in predicting lung adenocarcinoma risk was 0.847, 0.880, and 0.805, respectively, with sensitivity of 89.8%, 93.2%, and 94.9%, respectively. TISIDB analysis indicated that AKT1, CD44, and CDKN2A expression had a strong relationship with immune infiltration in lung adenocarcinoma. CONCLUSIONS: These hub genes, AKT1, CD44, and CDKN2A, may represent tumor biomarkers that may contribute to the understanding, diagnosis, and treatment of lung adenocarcinoma. AME Publishing Company 2022-10 /pmc/articles/PMC9641136/ /pubmed/36388051 http://dx.doi.org/10.21037/tcr-22-2225 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zeng, Changyi
Zhou, You
Ye, Wanqing
Fang, Zihan
Wang, Ke
Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title_full Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title_fullStr Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title_full_unstemmed Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title_short Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
title_sort exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641136/
https://www.ncbi.nlm.nih.gov/pubmed/36388051
http://dx.doi.org/10.21037/tcr-22-2225
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