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A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects human health. Previous studies have indicated that abnormal levels of glycosylation promote progression and poor prognosis of lung cancer. Thus, the present study aimed to explore the prognostic signatur...

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Autores principales: Liang, Jin-xiao, Chen, Qian, Gao, Wei, Chen, Da, Qian, Xin-yu, Bi, Jin-qiao, Lin, Xing-chen, Han, Bing-bing, Liu, Jin-shi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793550/
https://www.ncbi.nlm.nih.gov/pubmed/36575396
http://dx.doi.org/10.1186/s12859-022-05109-8
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author Liang, Jin-xiao
Chen, Qian
Gao, Wei
Chen, Da
Qian, Xin-yu
Bi, Jin-qiao
Lin, Xing-chen
Han, Bing-bing
Liu, Jin-shi
author_facet Liang, Jin-xiao
Chen, Qian
Gao, Wei
Chen, Da
Qian, Xin-yu
Bi, Jin-qiao
Lin, Xing-chen
Han, Bing-bing
Liu, Jin-shi
author_sort Liang, Jin-xiao
collection PubMed
description BACKGROUND: Lung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects human health. Previous studies have indicated that abnormal levels of glycosylation promote progression and poor prognosis of lung cancer. Thus, the present study aimed to explore the prognostic signature related to glycosyltransferases (GTs) for LUAD. METHODS: The gene expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and GTs were obtained from the GlycomeDB database. Differentially expressed GTs-related genes (DGTs) were identified using edge package and Venn diagram. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ingenuity pathway analysis (IPA) methods were used to investigate the biological processes of DGTs. Subsequently, Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a prognostic model for LUAD. Kaplan–Meier (K–M) analysis was adopted to explore the overall survival (OS) of LUAD patients. The accuracy and specificity of the prognostic model were evaluated by receiver operating characteristic analysis (ROC). In addition, single-sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze the infiltrating immune cells in the tumor environment. RESULTS: A total of 48 DGTs were mainly enriched in the processes of glycosylation, glycoprotein biosynthetic process, glycosphingolipid biosynthesis-lacto and neolacto series, and cell-mediated immune response. Furthermore, B3GNT3, MFNG, GYLTL1B, ALG3, and GALNT13 were screened as prognostic genes to construct a risk model for LUAD, and the LUAD patients were divided into high- and low-risk groups. K–M curve suggested that patients with a high-risk score had shorter OS than those with a low-risk score. The ROC analysis demonstrated that the risk model efficiently diagnoses LUAD. Additionally, the proportion of infiltrating aDCs (p < 0.05) and Tgds (p < 0.01) was higher in the high-risk group than in the low-risk group. Spearman’s correlation analysis manifested that the prognostic genes (MFNG and ALG3) were significantly correlated with infiltrating immune cells. CONCLUSION: In summary, this study established a novel GTs-related risk model for the prognosis of LUAD patients, providing new therapeutic targets for LUAD. However, the biological role of glycosylation-related genes in LUAD needs to be explored further. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-05109-8.
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spelling pubmed-97935502022-12-28 A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma Liang, Jin-xiao Chen, Qian Gao, Wei Chen, Da Qian, Xin-yu Bi, Jin-qiao Lin, Xing-chen Han, Bing-bing Liu, Jin-shi BMC Bioinformatics Research BACKGROUND: Lung adenocarcinoma (LUAD) is the most common malignant tumor that seriously affects human health. Previous studies have indicated that abnormal levels of glycosylation promote progression and poor prognosis of lung cancer. Thus, the present study aimed to explore the prognostic signature related to glycosyltransferases (GTs) for LUAD. METHODS: The gene expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and GTs were obtained from the GlycomeDB database. Differentially expressed GTs-related genes (DGTs) were identified using edge package and Venn diagram. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ingenuity pathway analysis (IPA) methods were used to investigate the biological processes of DGTs. Subsequently, Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a prognostic model for LUAD. Kaplan–Meier (K–M) analysis was adopted to explore the overall survival (OS) of LUAD patients. The accuracy and specificity of the prognostic model were evaluated by receiver operating characteristic analysis (ROC). In addition, single-sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze the infiltrating immune cells in the tumor environment. RESULTS: A total of 48 DGTs were mainly enriched in the processes of glycosylation, glycoprotein biosynthetic process, glycosphingolipid biosynthesis-lacto and neolacto series, and cell-mediated immune response. Furthermore, B3GNT3, MFNG, GYLTL1B, ALG3, and GALNT13 were screened as prognostic genes to construct a risk model for LUAD, and the LUAD patients were divided into high- and low-risk groups. K–M curve suggested that patients with a high-risk score had shorter OS than those with a low-risk score. The ROC analysis demonstrated that the risk model efficiently diagnoses LUAD. Additionally, the proportion of infiltrating aDCs (p < 0.05) and Tgds (p < 0.01) was higher in the high-risk group than in the low-risk group. Spearman’s correlation analysis manifested that the prognostic genes (MFNG and ALG3) were significantly correlated with infiltrating immune cells. CONCLUSION: In summary, this study established a novel GTs-related risk model for the prognosis of LUAD patients, providing new therapeutic targets for LUAD. However, the biological role of glycosylation-related genes in LUAD needs to be explored further. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-05109-8. BioMed Central 2022-12-27 /pmc/articles/PMC9793550/ /pubmed/36575396 http://dx.doi.org/10.1186/s12859-022-05109-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Liang, Jin-xiao
Chen, Qian
Gao, Wei
Chen, Da
Qian, Xin-yu
Bi, Jin-qiao
Lin, Xing-chen
Han, Bing-bing
Liu, Jin-shi
A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title_full A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title_fullStr A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title_full_unstemmed A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title_short A novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
title_sort novel glycosylation-related gene signature predicts survival in patients with lung adenocarcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793550/
https://www.ncbi.nlm.nih.gov/pubmed/36575396
http://dx.doi.org/10.1186/s12859-022-05109-8
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