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Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Fatty acid metabolism takes part in malignancy progression. However, the roles fatty acid metabolism plays in LUAD are still unclear. Methods: The transcriptomic and clinical data of LUAD patients from T...

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Autores principales: Wang, Suyu, Chen, Aona, Zhu, Wanli, Feng, Di, Wei, Juan, Li, Quanfu, Shi, Xuan, Lv, Xin, Liu, Meiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9329533/
https://www.ncbi.nlm.nih.gov/pubmed/35910199
http://dx.doi.org/10.3389/fgene.2022.905508
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author Wang, Suyu
Chen, Aona
Zhu, Wanli
Feng, Di
Wei, Juan
Li, Quanfu
Shi, Xuan
Lv, Xin
Liu, Meiyun
author_facet Wang, Suyu
Chen, Aona
Zhu, Wanli
Feng, Di
Wei, Juan
Li, Quanfu
Shi, Xuan
Lv, Xin
Liu, Meiyun
author_sort Wang, Suyu
collection PubMed
description Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Fatty acid metabolism takes part in malignancy progression. However, the roles fatty acid metabolism plays in LUAD are still unclear. Methods: The transcriptomic and clinical data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were extracted. ssGSEA, WGCNA, univariable Cox regression, and LASSO Cox regression analyses were performed to identify the fatty acid metabolism-related genes which influenced the overall survival (OS) and build a fatty acid-related risk score (FARS) model. A nomogram was established based on the FARS and other clinicopathological features, and ROC and calibration plots were used to validate the prediction accuracy. The tumor microenvironment (TME) of patients with high and low FARS was compared. Results: A total of 38 genes were identified to be independently related to the survival outcome and put into a FARS model. High FARS patients exhibited significantly worse OS. The nomogram included the FARS and pathological stage, and the AUC of the nomogram predicting 1-, 2-, 3-, 4-, and 5-year OS was 0.789, 0.807, 0.798, 0.809, and 0.753, respectively. Calibration plots also indicated good accuracy. Moreover, the samples of the high FARS had higher expression of PDL1. Conclusion: We constructed a FARS model which could accurately predict the survival outcome of the LUAD patients. The genes of the FARS are related to the tumor microenvironment and patients with high FARS can potentially benefit more from anti-PD1/PDL1 immunotherapy. In addition, the mechanisms of the genes in the FARS affecting prognosis are worthy of further research to develop new gene-targeted drugs.
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spelling pubmed-93295332022-07-29 Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma Wang, Suyu Chen, Aona Zhu, Wanli Feng, Di Wei, Juan Li, Quanfu Shi, Xuan Lv, Xin Liu, Meiyun Front Genet Genetics Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Fatty acid metabolism takes part in malignancy progression. However, the roles fatty acid metabolism plays in LUAD are still unclear. Methods: The transcriptomic and clinical data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were extracted. ssGSEA, WGCNA, univariable Cox regression, and LASSO Cox regression analyses were performed to identify the fatty acid metabolism-related genes which influenced the overall survival (OS) and build a fatty acid-related risk score (FARS) model. A nomogram was established based on the FARS and other clinicopathological features, and ROC and calibration plots were used to validate the prediction accuracy. The tumor microenvironment (TME) of patients with high and low FARS was compared. Results: A total of 38 genes were identified to be independently related to the survival outcome and put into a FARS model. High FARS patients exhibited significantly worse OS. The nomogram included the FARS and pathological stage, and the AUC of the nomogram predicting 1-, 2-, 3-, 4-, and 5-year OS was 0.789, 0.807, 0.798, 0.809, and 0.753, respectively. Calibration plots also indicated good accuracy. Moreover, the samples of the high FARS had higher expression of PDL1. Conclusion: We constructed a FARS model which could accurately predict the survival outcome of the LUAD patients. The genes of the FARS are related to the tumor microenvironment and patients with high FARS can potentially benefit more from anti-PD1/PDL1 immunotherapy. In addition, the mechanisms of the genes in the FARS affecting prognosis are worthy of further research to develop new gene-targeted drugs. Frontiers Media S.A. 2022-07-14 /pmc/articles/PMC9329533/ /pubmed/35910199 http://dx.doi.org/10.3389/fgene.2022.905508 Text en Copyright © 2022 Wang, Chen, Zhu, Feng, Wei, Li, Shi, Lv and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Suyu
Chen, Aona
Zhu, Wanli
Feng, Di
Wei, Juan
Li, Quanfu
Shi, Xuan
Lv, Xin
Liu, Meiyun
Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title_full Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title_fullStr Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title_full_unstemmed Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title_short Characterization of Fatty Acid Metabolism in Lung Adenocarcinoma
title_sort characterization of fatty acid metabolism in lung adenocarcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9329533/
https://www.ncbi.nlm.nih.gov/pubmed/35910199
http://dx.doi.org/10.3389/fgene.2022.905508
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