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APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) with poor survival in advanced stage. Nowadays the rate of nonsmoking patients has dramatically increased and may be associated with the presence of driver mutations. Better understanding of the muta...

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Autores principales: Ma, Jianli, Yang, Xudong, Zhang, Jing, Antonoff, Mara B., Wu, Qianjiang, Ji, Hongfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088004/
https://www.ncbi.nlm.nih.gov/pubmed/37057114
http://dx.doi.org/10.21037/tlcr-23-150
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author Ma, Jianli
Yang, Xudong
Zhang, Jing
Antonoff, Mara B.
Wu, Qianjiang
Ji, Hongfei
author_facet Ma, Jianli
Yang, Xudong
Zhang, Jing
Antonoff, Mara B.
Wu, Qianjiang
Ji, Hongfei
author_sort Ma, Jianli
collection PubMed
description BACKGROUND: Lung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) with poor survival in advanced stage. Nowadays the rate of nonsmoking patients has dramatically increased and may be associated with the presence of driver mutations. Better understanding of the mutation profile data of nonsmoking LUAD patients are critical to predict survival and provide greater benefits to more patients. The apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC) has been shown to play an important role in molecular tumorigenesis of NSCLC. However, the clinical relevance of APOBEC in nonsmoking LUAD remains to be understood. METHODS: LUAD patients with somatic mutation and RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) were assessed and screened in the Gene Expression Omnibus. Transcriptome data and mutational signatures were analyzed using R package. Then, we used the least absolute shrinkage and selection operator (LASSO) regression model to construct the APOBEC3 score (APOBEC3 score) model. The prognostic value was evaluated using Kaplan–Meier analysis. Finally, the functional enrichment analysis of differential expressed genes (DEGs) and the immune-related features were also estimated using R package. RESULTS: By analyzing the mutational profile data of NSCLC in the TCGA database, we found that different mutation patterns existed between smoking and nonsmoking patients, and the APOBEC3 family played an important role in the mutation pattern of nonsmoking patients with LUAD. We established an APOBEC3 score and found that TCW (W = A or T) mutation counts were significantly greater in the high APOBEC3 score group than in the low APOBEC3 score group. Furthermore, there were different immune feathers and prognostic values between the high and low APOBEC3 score patients, suggesting an independent prognostic factor of APOBEC3 in nonsmoking LUAD patients. CONCLUSIONS: We established a comprehensive view of APOBEC3 mutations in nonsmoking LUAD patients. Our review provides new insights into using the APOBEC3 mutation to predict prognosis and improve the immunotherapy response for future applications.
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spelling pubmed-100880042023-04-12 APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma Ma, Jianli Yang, Xudong Zhang, Jing Antonoff, Mara B. Wu, Qianjiang Ji, Hongfei Transl Lung Cancer Res Original Article BACKGROUND: Lung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) with poor survival in advanced stage. Nowadays the rate of nonsmoking patients has dramatically increased and may be associated with the presence of driver mutations. Better understanding of the mutation profile data of nonsmoking LUAD patients are critical to predict survival and provide greater benefits to more patients. The apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC) has been shown to play an important role in molecular tumorigenesis of NSCLC. However, the clinical relevance of APOBEC in nonsmoking LUAD remains to be understood. METHODS: LUAD patients with somatic mutation and RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) were assessed and screened in the Gene Expression Omnibus. Transcriptome data and mutational signatures were analyzed using R package. Then, we used the least absolute shrinkage and selection operator (LASSO) regression model to construct the APOBEC3 score (APOBEC3 score) model. The prognostic value was evaluated using Kaplan–Meier analysis. Finally, the functional enrichment analysis of differential expressed genes (DEGs) and the immune-related features were also estimated using R package. RESULTS: By analyzing the mutational profile data of NSCLC in the TCGA database, we found that different mutation patterns existed between smoking and nonsmoking patients, and the APOBEC3 family played an important role in the mutation pattern of nonsmoking patients with LUAD. We established an APOBEC3 score and found that TCW (W = A or T) mutation counts were significantly greater in the high APOBEC3 score group than in the low APOBEC3 score group. Furthermore, there were different immune feathers and prognostic values between the high and low APOBEC3 score patients, suggesting an independent prognostic factor of APOBEC3 in nonsmoking LUAD patients. CONCLUSIONS: We established a comprehensive view of APOBEC3 mutations in nonsmoking LUAD patients. Our review provides new insights into using the APOBEC3 mutation to predict prognosis and improve the immunotherapy response for future applications. AME Publishing Company 2023-03-31 2023-03-31 /pmc/articles/PMC10088004/ /pubmed/37057114 http://dx.doi.org/10.21037/tlcr-23-150 Text en 2023 Translational Lung Cancer Research. 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
Ma, Jianli
Yang, Xudong
Zhang, Jing
Antonoff, Mara B.
Wu, Qianjiang
Ji, Hongfei
APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title_full APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title_fullStr APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title_full_unstemmed APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title_short APOBEC mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
title_sort apobec mutational signature predicts prognosis and immunotherapy response in nonsmoking patients with lung adenocarcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088004/
https://www.ncbi.nlm.nih.gov/pubmed/37057114
http://dx.doi.org/10.21037/tlcr-23-150
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