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Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma
BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC) with a low 5-year survival rate, which may be associated with the presence of metastatic tumors at the time of diagnosis, especially lymph node metastasis (LNM). This study aimed to c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9904923/ https://www.ncbi.nlm.nih.gov/pubmed/36793937 http://dx.doi.org/10.1155/2023/6585109 |
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author | Yu, Jiao Li, Gang Tian, Yingxuan Huo, Shufen |
author_facet | Yu, Jiao Li, Gang Tian, Yingxuan Huo, Shufen |
author_sort | Yu, Jiao |
collection | PubMed |
description | BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC) with a low 5-year survival rate, which may be associated with the presence of metastatic tumors at the time of diagnosis, especially lymph node metastasis (LNM). This study aimed to construct a LNM-related gene signature for predicting the prognosis of patients with LUAD. METHODS: RNA sequencing data and clinical information of LUAD patients were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Samples were divided into metastasis (M) and nonmetastasis (NM) groups based on LNM status. Differentially expressed genes (DEGs) between M and NM groups were screened, and then WGCNA was applied to identify key genes. Furthermore, univariate Cox and LASSO regression analyses were conducted to construct a risk score model, and the predictive performance of model was validated by GSE68465, GSE42127, and GSE50081. The protein and mRNA expression level of LNM-associated genes were detected by human protein atlas (HPA) and GSE68465. RESULTS: A prognostic model based on eight LNM-related genes (ANGPTL4, BARX2, GPR98, KRT6A, PTPRH, RGS20, TCN1, and TNS4) was developed. Patients in the high-risk group had poorer overall survival than those in the low-risk group, and validation analysis showed that this model had potential predictive value for patients with LUAD. HPA analysis supported the upregulation of ANGPTL4, KRT6A, BARX2, RGS20 and the downregulation of GPR98 in LUAD compared with normal tissues. CONCLUSION: Our results indicated that the eight LNM-related genes signature had potential value in the prognosis of patients with LUAD, which may have important practical implications. |
format | Online Article Text |
id | pubmed-9904923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-99049232023-02-14 Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma Yu, Jiao Li, Gang Tian, Yingxuan Huo, Shufen Genet Res (Camb) Research Article BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC) with a low 5-year survival rate, which may be associated with the presence of metastatic tumors at the time of diagnosis, especially lymph node metastasis (LNM). This study aimed to construct a LNM-related gene signature for predicting the prognosis of patients with LUAD. METHODS: RNA sequencing data and clinical information of LUAD patients were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Samples were divided into metastasis (M) and nonmetastasis (NM) groups based on LNM status. Differentially expressed genes (DEGs) between M and NM groups were screened, and then WGCNA was applied to identify key genes. Furthermore, univariate Cox and LASSO regression analyses were conducted to construct a risk score model, and the predictive performance of model was validated by GSE68465, GSE42127, and GSE50081. The protein and mRNA expression level of LNM-associated genes were detected by human protein atlas (HPA) and GSE68465. RESULTS: A prognostic model based on eight LNM-related genes (ANGPTL4, BARX2, GPR98, KRT6A, PTPRH, RGS20, TCN1, and TNS4) was developed. Patients in the high-risk group had poorer overall survival than those in the low-risk group, and validation analysis showed that this model had potential predictive value for patients with LUAD. HPA analysis supported the upregulation of ANGPTL4, KRT6A, BARX2, RGS20 and the downregulation of GPR98 in LUAD compared with normal tissues. CONCLUSION: Our results indicated that the eight LNM-related genes signature had potential value in the prognosis of patients with LUAD, which may have important practical implications. Hindawi 2023-01-31 /pmc/articles/PMC9904923/ /pubmed/36793937 http://dx.doi.org/10.1155/2023/6585109 Text en Copyright © 2023 Jiao Yu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Yu, Jiao Li, Gang Tian, Yingxuan Huo, Shufen Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title | Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title_full | Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title_fullStr | Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title_full_unstemmed | Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title_short | Establishment of a Lymph Node Metastasis-Associated Prognostic Signature for Lung Adenocarcinoma |
title_sort | establishment of a lymph node metastasis-associated prognostic signature for lung adenocarcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9904923/ https://www.ncbi.nlm.nih.gov/pubmed/36793937 http://dx.doi.org/10.1155/2023/6585109 |
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