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DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications

The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a...

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Autores principales: Xu, Feng, He, Lulu, Zhan, Xueqin, Chen, Jiexin, Xu, Huan, Huang, Xiaoling, Li, Yangyi, Zheng, Xiaohe, Lin, Ling, Chen, Yongsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803536/
https://www.ncbi.nlm.nih.gov/pubmed/33234739
http://dx.doi.org/10.18632/aging.104129
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author Xu, Feng
He, Lulu
Zhan, Xueqin
Chen, Jiexin
Xu, Huan
Huang, Xiaoling
Li, Yangyi
Zheng, Xiaohe
Lin, Ling
Chen, Yongsong
author_facet Xu, Feng
He, Lulu
Zhan, Xueqin
Chen, Jiexin
Xu, Huan
Huang, Xiaoling
Li, Yangyi
Zheng, Xiaohe
Lin, Ling
Chen, Yongsong
author_sort Xu, Feng
collection PubMed
description The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a predictive model for LUAD prognosis. Thirty-three methylation sites were identified as specific prognostic biomarkers, independent of patients’ clinical characteristics. These methylation profiles were used to identify potential drug candidates and study the immune microenvironment of LUAD and response to immunotherapy. When compared with the high-risk group, the low-risk group had a lower recurrence rate and favorable prognosis. The tumor microenvironment differed between the two groups as reflected by the higher number of resting dendritic cells and a lower number of monocytes and resting mast cells in the low-risk group. Moreover, low-risk patients reported higher immune and stromal scores, lower tumor purity, and higher expression of HLA genes. Low-risk patients responded well to immunotherapy due to higher expression of immune checkpoint molecules and lower stemness index. Thus, our model predicted a favorable prognosis and increased overall survival for patients in the low-risk methylation group. Further, this model could provide potential drug targets to develop effective immunotherapies for LUAD.
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spelling pubmed-78035362021-01-15 DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications Xu, Feng He, Lulu Zhan, Xueqin Chen, Jiexin Xu, Huan Huang, Xiaoling Li, Yangyi Zheng, Xiaohe Lin, Ling Chen, Yongsong Aging (Albany NY) Research Paper The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a predictive model for LUAD prognosis. Thirty-three methylation sites were identified as specific prognostic biomarkers, independent of patients’ clinical characteristics. These methylation profiles were used to identify potential drug candidates and study the immune microenvironment of LUAD and response to immunotherapy. When compared with the high-risk group, the low-risk group had a lower recurrence rate and favorable prognosis. The tumor microenvironment differed between the two groups as reflected by the higher number of resting dendritic cells and a lower number of monocytes and resting mast cells in the low-risk group. Moreover, low-risk patients reported higher immune and stromal scores, lower tumor purity, and higher expression of HLA genes. Low-risk patients responded well to immunotherapy due to higher expression of immune checkpoint molecules and lower stemness index. Thus, our model predicted a favorable prognosis and increased overall survival for patients in the low-risk methylation group. Further, this model could provide potential drug targets to develop effective immunotherapies for LUAD. Impact Journals 2020-11-21 /pmc/articles/PMC7803536/ /pubmed/33234739 http://dx.doi.org/10.18632/aging.104129 Text en Copyright: © 2020 Xu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Xu, Feng
He, Lulu
Zhan, Xueqin
Chen, Jiexin
Xu, Huan
Huang, Xiaoling
Li, Yangyi
Zheng, Xiaohe
Lin, Ling
Chen, Yongsong
DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title_full DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title_fullStr DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title_full_unstemmed DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title_short DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
title_sort dna methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803536/
https://www.ncbi.nlm.nih.gov/pubmed/33234739
http://dx.doi.org/10.18632/aging.104129
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