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Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma

BACKGROUND: The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains. METHODS: Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan‐Meier analysis was performed...

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Autores principales: Zhou, Andrew, Zhang, Dalin, Kang, Xiaoman, Brooks, James D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501266/
https://www.ncbi.nlm.nih.gov/pubmed/37434467
http://dx.doi.org/10.1002/cam4.6330
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author Zhou, Andrew
Zhang, Dalin
Kang, Xiaoman
Brooks, James D.
author_facet Zhou, Andrew
Zhang, Dalin
Kang, Xiaoman
Brooks, James D.
author_sort Zhou, Andrew
collection PubMed
description BACKGROUND: The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains. METHODS: Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan‐Meier analysis was performed to determine whether age was associated with patient OS. The immune cell composition in the tumor microenvironment (TME) was evaluated using CIBERSORT. The fraction of stromal and immune cells in tumor samples were also using assessed using multiple tools including ESTIMATE, EPIC, and TIMER. Differentially expressed genes (DEGs) from the RNA‐Seq data that were associated with age and immune cell composition were identified using the R package DEGseq. A 22‐gene signature composed of DEGs associated with age and immune cell composition that predicted OS were constructed using Least Absolute Shrinkage and Selection Operator (LASSO). RESULTS: In The Cancer Genome Atlas (TCGA)‐LUAD dataset, we found that younger patients (≤70) had a significant better OS compared to older patients (>70). In addition, older patients had significantly higher expression of immune checkpoint proteins including inhibitory T cell receptors and their ligands. Moreover, analyses using multiple bioinformatics tools showed increased immune infiltration, including CD4+ T cells, in older patients compared to younger patients. We identified a panel of genes differentially expressed between patients >70 years compared to those ≤70 years, as well as between patients with high or low immune scores and selected 84 common genes to construct a prognostic gene signature. A risk score calculated based on 22 genes selected by LASSO predicted 1, 3, and 5‐year OS, with an area under the curve (AUC) of 0.72, 0.72, 0.69, receptively, in TCGA‐LUAD dataset and an independent validation dataset available from the European Genome‐phenome Archive (EGA). CONCLUSION: Our results demonstrate that age contributes to OS of LUAD patients atleast in part through its association with immune infiltration in the TME.
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spelling pubmed-105012662023-09-15 Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma Zhou, Andrew Zhang, Dalin Kang, Xiaoman Brooks, James D. Cancer Med Research Articles BACKGROUND: The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains. METHODS: Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan‐Meier analysis was performed to determine whether age was associated with patient OS. The immune cell composition in the tumor microenvironment (TME) was evaluated using CIBERSORT. The fraction of stromal and immune cells in tumor samples were also using assessed using multiple tools including ESTIMATE, EPIC, and TIMER. Differentially expressed genes (DEGs) from the RNA‐Seq data that were associated with age and immune cell composition were identified using the R package DEGseq. A 22‐gene signature composed of DEGs associated with age and immune cell composition that predicted OS were constructed using Least Absolute Shrinkage and Selection Operator (LASSO). RESULTS: In The Cancer Genome Atlas (TCGA)‐LUAD dataset, we found that younger patients (≤70) had a significant better OS compared to older patients (>70). In addition, older patients had significantly higher expression of immune checkpoint proteins including inhibitory T cell receptors and their ligands. Moreover, analyses using multiple bioinformatics tools showed increased immune infiltration, including CD4+ T cells, in older patients compared to younger patients. We identified a panel of genes differentially expressed between patients >70 years compared to those ≤70 years, as well as between patients with high or low immune scores and selected 84 common genes to construct a prognostic gene signature. A risk score calculated based on 22 genes selected by LASSO predicted 1, 3, and 5‐year OS, with an area under the curve (AUC) of 0.72, 0.72, 0.69, receptively, in TCGA‐LUAD dataset and an independent validation dataset available from the European Genome‐phenome Archive (EGA). CONCLUSION: Our results demonstrate that age contributes to OS of LUAD patients atleast in part through its association with immune infiltration in the TME. John Wiley and Sons Inc. 2023-07-11 /pmc/articles/PMC10501266/ /pubmed/37434467 http://dx.doi.org/10.1002/cam4.6330 Text en © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Zhou, Andrew
Zhang, Dalin
Kang, Xiaoman
Brooks, James D.
Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title_full Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title_fullStr Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title_full_unstemmed Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title_short Identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
title_sort identification of age‐ and immune‐related gene signatures for clinical outcome prediction in lung adenocarcinoma
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501266/
https://www.ncbi.nlm.nih.gov/pubmed/37434467
http://dx.doi.org/10.1002/cam4.6330
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