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A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma

BACKGROUND: Lymph node metastasis is one of the important factors affecting the prognosis of lung adenocarcinoma (LUAD) patients. The key molecules in lymph node metastasis have not yet been fully revealed. Therefore, we aimed to construct a prognostic model based on lymph node metastasis-related ge...

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Autores principales: Li, Qiao, Liu, Xiao-Li, Jiang, Ni, Li, Qian-Yun, Song, Yong-Xiang, Ke, Xi-Xian, Han, Hao, Luo, Qian, Guo, Qiang, Luo, Xiang-Yu, Chen, Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183535/
https://www.ncbi.nlm.nih.gov/pubmed/37197482
http://dx.doi.org/10.21037/jtd-23-265
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author Li, Qiao
Liu, Xiao-Li
Jiang, Ni
Li, Qian-Yun
Song, Yong-Xiang
Ke, Xi-Xian
Han, Hao
Luo, Qian
Guo, Qiang
Luo, Xiang-Yu
Chen, Cheng
author_facet Li, Qiao
Liu, Xiao-Li
Jiang, Ni
Li, Qian-Yun
Song, Yong-Xiang
Ke, Xi-Xian
Han, Hao
Luo, Qian
Guo, Qiang
Luo, Xiang-Yu
Chen, Cheng
author_sort Li, Qiao
collection PubMed
description BACKGROUND: Lymph node metastasis is one of the important factors affecting the prognosis of lung adenocarcinoma (LUAD) patients. The key molecules in lymph node metastasis have not yet been fully revealed. Therefore, we aimed to construct a prognostic model based on lymph node metastasis-related genes to evaluate the prognosis of LUAD patients. METHODS: The differentially expressed genes (DEGs) in the process of LUAD metastasis were identified in The Cancer Genome Atlas (TCGA) database, and the biological roles of the DEGs were depicted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and a protein-protein interaction (PPI) network. Survival analysis and Cox regression analysis were used to identify the genes related to the prognosis of patients with LUAD, and a nomogram and a prognostic model were constructed. The potential prognostic value, immune escape, and regulatory mechanisms of the prognostic model in LUAD progression were explored through survival analysis and gene set enrichment analysis (GSEA). RESULTS: A total of 75 genes were upregulated, and 138 genes were downregulated in tissues of lymph node metastasis. The expression levels of STC1, CYP17A1, RHOV, GUCA2B, TM4SF20, DEFB1, CRHR2, ABCC2, CYP4B1, KRT16, and NTS were revealed as risk factors for a poor prognosis in LUAD patients. High-risk LUAD patients had a poor prognosis in the prognostic model based on RHOV, ABCC2, and CYP4B1. The clinical stage and the risk score were found to be independent risk factors for a poor prognosis in LUAD patients, and the risk score was associated with the tumor purity, T cell, natural killer (NK) cell, and other immune cells. The prognostic model might affect the progression of LUAD using DNA replication, the cell cycle, P53, and other signaling pathways. CONCLUSIONS: Lymph node metastasis-related genes RHOV, ABCC2, and CYP4B1 are associated with a poor prognosis in LUAD. A prognostic model based on RHOV, ABCC2, and CYP4B1 might predict the prognosis of LUAD patients and be associated with immune infiltration.
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spelling pubmed-101835352023-05-16 A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma Li, Qiao Liu, Xiao-Li Jiang, Ni Li, Qian-Yun Song, Yong-Xiang Ke, Xi-Xian Han, Hao Luo, Qian Guo, Qiang Luo, Xiang-Yu Chen, Cheng J Thorac Dis Original Article BACKGROUND: Lymph node metastasis is one of the important factors affecting the prognosis of lung adenocarcinoma (LUAD) patients. The key molecules in lymph node metastasis have not yet been fully revealed. Therefore, we aimed to construct a prognostic model based on lymph node metastasis-related genes to evaluate the prognosis of LUAD patients. METHODS: The differentially expressed genes (DEGs) in the process of LUAD metastasis were identified in The Cancer Genome Atlas (TCGA) database, and the biological roles of the DEGs were depicted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and a protein-protein interaction (PPI) network. Survival analysis and Cox regression analysis were used to identify the genes related to the prognosis of patients with LUAD, and a nomogram and a prognostic model were constructed. The potential prognostic value, immune escape, and regulatory mechanisms of the prognostic model in LUAD progression were explored through survival analysis and gene set enrichment analysis (GSEA). RESULTS: A total of 75 genes were upregulated, and 138 genes were downregulated in tissues of lymph node metastasis. The expression levels of STC1, CYP17A1, RHOV, GUCA2B, TM4SF20, DEFB1, CRHR2, ABCC2, CYP4B1, KRT16, and NTS were revealed as risk factors for a poor prognosis in LUAD patients. High-risk LUAD patients had a poor prognosis in the prognostic model based on RHOV, ABCC2, and CYP4B1. The clinical stage and the risk score were found to be independent risk factors for a poor prognosis in LUAD patients, and the risk score was associated with the tumor purity, T cell, natural killer (NK) cell, and other immune cells. The prognostic model might affect the progression of LUAD using DNA replication, the cell cycle, P53, and other signaling pathways. CONCLUSIONS: Lymph node metastasis-related genes RHOV, ABCC2, and CYP4B1 are associated with a poor prognosis in LUAD. A prognostic model based on RHOV, ABCC2, and CYP4B1 might predict the prognosis of LUAD patients and be associated with immune infiltration. AME Publishing Company 2023-04-10 2023-04-28 /pmc/articles/PMC10183535/ /pubmed/37197482 http://dx.doi.org/10.21037/jtd-23-265 Text en 2023 Journal of Thoracic Disease. 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
Li, Qiao
Liu, Xiao-Li
Jiang, Ni
Li, Qian-Yun
Song, Yong-Xiang
Ke, Xi-Xian
Han, Hao
Luo, Qian
Guo, Qiang
Luo, Xiang-Yu
Chen, Cheng
A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title_full A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title_fullStr A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title_full_unstemmed A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title_short A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
title_sort new prognostic model for rhov, abcc2, and cyp4b1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183535/
https://www.ncbi.nlm.nih.gov/pubmed/37197482
http://dx.doi.org/10.21037/jtd-23-265
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