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Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis

BACKGROUND: Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cig...

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Autores principales: Wang, Jin, Chen, Tao, Yu, Xiaofan, OUYang, Nan, Tan, Lirong, Jia, Beibei, Tong, Jian, Li, Jianxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427766/
https://www.ncbi.nlm.nih.gov/pubmed/32795291
http://dx.doi.org/10.1186/s12967-020-02474-x
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author Wang, Jin
Chen, Tao
Yu, Xiaofan
OUYang, Nan
Tan, Lirong
Jia, Beibei
Tong, Jian
Li, Jianxiang
author_facet Wang, Jin
Chen, Tao
Yu, Xiaofan
OUYang, Nan
Tan, Lirong
Jia, Beibei
Tong, Jian
Li, Jianxiang
author_sort Wang, Jin
collection PubMed
description BACKGROUND: Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis. RESULTS: Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C (GYPC), NME/NM23 nucleoside diphosphate kinase 1 (NME1) and slit guidance ligand 2 (SLIT2), were found to be significantly correlated with LUAD patients’ smoking history. The expression levels of GYPC, NME1 and SLIT2 in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of NME1 was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of GYPC and SLIT2, as well as decreased expression of NME1 were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation. CONCLUSION: In conclusion, our observations indicated that the differential expression of GYPC, NME1 and SLIT2 may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients.
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spelling pubmed-74277662020-08-17 Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis Wang, Jin Chen, Tao Yu, Xiaofan OUYang, Nan Tan, Lirong Jia, Beibei Tong, Jian Li, Jianxiang J Transl Med Research BACKGROUND: Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis. RESULTS: Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C (GYPC), NME/NM23 nucleoside diphosphate kinase 1 (NME1) and slit guidance ligand 2 (SLIT2), were found to be significantly correlated with LUAD patients’ smoking history. The expression levels of GYPC, NME1 and SLIT2 in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of NME1 was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of GYPC and SLIT2, as well as decreased expression of NME1 were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation. CONCLUSION: In conclusion, our observations indicated that the differential expression of GYPC, NME1 and SLIT2 may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients. BioMed Central 2020-08-14 /pmc/articles/PMC7427766/ /pubmed/32795291 http://dx.doi.org/10.1186/s12967-020-02474-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wang, Jin
Chen, Tao
Yu, Xiaofan
OUYang, Nan
Tan, Lirong
Jia, Beibei
Tong, Jian
Li, Jianxiang
Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title_full Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title_fullStr Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title_full_unstemmed Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title_short Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
title_sort identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427766/
https://www.ncbi.nlm.nih.gov/pubmed/32795291
http://dx.doi.org/10.1186/s12967-020-02474-x
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