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Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a rapidly progressive malignancy, and its mortality rate is very high. In this study, we aimed at finding novel prognosis-related genes and constructing a credible prognostic model to improve the prediction for LUAD patients. Differential gene expression, mutant subtype...

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Autores principales: Chen, Xueping, Yu, Liqun, Zhang, Honglei, Jin, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252847/
https://www.ncbi.nlm.nih.gov/pubmed/37296766
http://dx.doi.org/10.3390/diagnostics13111914
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author Chen, Xueping
Yu, Liqun
Zhang, Honglei
Jin, Hua
author_facet Chen, Xueping
Yu, Liqun
Zhang, Honglei
Jin, Hua
author_sort Chen, Xueping
collection PubMed
description Lung adenocarcinoma (LUAD) is a rapidly progressive malignancy, and its mortality rate is very high. In this study, we aimed at finding novel prognosis-related genes and constructing a credible prognostic model to improve the prediction for LUAD patients. Differential gene expression, mutant subtype, and univariate Cox regression analyses were conducted with the dataset from the Cancer Genome Atlas (TCGA) database to screen for prognostic features. These features were employed in the following multivariate Cox regression analysis and the produced prognostic model included the stage and expression of SMCO2, SATB2, HAVCR1, GRIA1, and GALNT4, as well as mutation subtypes of TP53. The exactness of the model was confirmed by an overall survival (OS) analysis and disease-free survival (DFS) analysis, which indicated that patients in the high-risk group had a poorer prognosis compared to those in the low-risk group. The area under the receiver operating characteristic curve (AUC) was 0.793 in the training group and 0.779 in the testing group. The AUC of tumor recurrence was 0.778 in the training group and 0.815 in the testing group. In addition, the number of deceased patients increased as the risk scores raised. Furthermore, the knockdown of prognostic gene HAVCR1 suppressed the proliferation of A549 cells, which supports our prognostic model that the high expression of HAVCR1 predicts poor prognosis. Our work created a reliable prognostic risk score model for LUAD and provided potential prognostic biomarkers.
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spelling pubmed-102528472023-06-10 Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma Chen, Xueping Yu, Liqun Zhang, Honglei Jin, Hua Diagnostics (Basel) Article Lung adenocarcinoma (LUAD) is a rapidly progressive malignancy, and its mortality rate is very high. In this study, we aimed at finding novel prognosis-related genes and constructing a credible prognostic model to improve the prediction for LUAD patients. Differential gene expression, mutant subtype, and univariate Cox regression analyses were conducted with the dataset from the Cancer Genome Atlas (TCGA) database to screen for prognostic features. These features were employed in the following multivariate Cox regression analysis and the produced prognostic model included the stage and expression of SMCO2, SATB2, HAVCR1, GRIA1, and GALNT4, as well as mutation subtypes of TP53. The exactness of the model was confirmed by an overall survival (OS) analysis and disease-free survival (DFS) analysis, which indicated that patients in the high-risk group had a poorer prognosis compared to those in the low-risk group. The area under the receiver operating characteristic curve (AUC) was 0.793 in the training group and 0.779 in the testing group. The AUC of tumor recurrence was 0.778 in the training group and 0.815 in the testing group. In addition, the number of deceased patients increased as the risk scores raised. Furthermore, the knockdown of prognostic gene HAVCR1 suppressed the proliferation of A549 cells, which supports our prognostic model that the high expression of HAVCR1 predicts poor prognosis. Our work created a reliable prognostic risk score model for LUAD and provided potential prognostic biomarkers. MDPI 2023-05-30 /pmc/articles/PMC10252847/ /pubmed/37296766 http://dx.doi.org/10.3390/diagnostics13111914 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Xueping
Yu, Liqun
Zhang, Honglei
Jin, Hua
Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title_full Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title_fullStr Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title_full_unstemmed Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title_short Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma
title_sort identification of new prognostic genes and construction of a prognostic model for lung adenocarcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252847/
https://www.ncbi.nlm.nih.gov/pubmed/37296766
http://dx.doi.org/10.3390/diagnostics13111914
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