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Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity
Lung cancer is one of the main cancer types due to its persistently high incidence and mortality, yet a simple and effective prognostic model is still lacking. This study aimed to identify independent prognostic genes related to the heterogeneity of lung adenocarcinoma (LUAD), generate a prognostic...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035852/ https://www.ncbi.nlm.nih.gov/pubmed/35480896 http://dx.doi.org/10.3389/fmolb.2022.807497 |
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author | Zheng, Pengdou Zhang, Huojun Jiang, Weiling Wang, Lingling Liu, Lu Zhou, Yuhao Zhou, Ling Liu, Huiguo |
author_facet | Zheng, Pengdou Zhang, Huojun Jiang, Weiling Wang, Lingling Liu, Lu Zhou, Yuhao Zhou, Ling Liu, Huiguo |
author_sort | Zheng, Pengdou |
collection | PubMed |
description | Lung cancer is one of the main cancer types due to its persistently high incidence and mortality, yet a simple and effective prognostic model is still lacking. This study aimed to identify independent prognostic genes related to the heterogeneity of lung adenocarcinoma (LUAD), generate a prognostic risk score model, and construct a nomogram in combination with other pathological characteristics to predict patients’ overall survival (OS). A significant amount of data pertaining to single-cell RNA sequencing (scRNA-seq), RNA sequencing (RNA-seq), and somatic mutation were used for data mining. After statistical analyses, a risk scoring model was established based on eight independent prognostic genes, and the OS of high-risk patients was significantly lower than that of low-risk patients. Interestingly, high-risk patients were more sensitive and effective to immune checkpoint blocking therapy. In addition, it was noteworthy that CCL20 not only affected prognosis and differentiation of LUAD but also led to poor histologic grade of tumor cells. Ultimately, combining risk score, clinicopathological information, and CCL20 mutation status, a nomogram with good predictive performance and high accuracy was established. In short, our research established a prognostic model that could be used to guide clinical practice based on the constantly updated big multi-omics data. Finally, this analysis revealed that CCL20 may become a potential therapeutic target for LUAD. |
format | Online Article Text |
id | pubmed-9035852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90358522022-04-26 Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity Zheng, Pengdou Zhang, Huojun Jiang, Weiling Wang, Lingling Liu, Lu Zhou, Yuhao Zhou, Ling Liu, Huiguo Front Mol Biosci Molecular Biosciences Lung cancer is one of the main cancer types due to its persistently high incidence and mortality, yet a simple and effective prognostic model is still lacking. This study aimed to identify independent prognostic genes related to the heterogeneity of lung adenocarcinoma (LUAD), generate a prognostic risk score model, and construct a nomogram in combination with other pathological characteristics to predict patients’ overall survival (OS). A significant amount of data pertaining to single-cell RNA sequencing (scRNA-seq), RNA sequencing (RNA-seq), and somatic mutation were used for data mining. After statistical analyses, a risk scoring model was established based on eight independent prognostic genes, and the OS of high-risk patients was significantly lower than that of low-risk patients. Interestingly, high-risk patients were more sensitive and effective to immune checkpoint blocking therapy. In addition, it was noteworthy that CCL20 not only affected prognosis and differentiation of LUAD but also led to poor histologic grade of tumor cells. Ultimately, combining risk score, clinicopathological information, and CCL20 mutation status, a nomogram with good predictive performance and high accuracy was established. In short, our research established a prognostic model that could be used to guide clinical practice based on the constantly updated big multi-omics data. Finally, this analysis revealed that CCL20 may become a potential therapeutic target for LUAD. Frontiers Media S.A. 2022-04-11 /pmc/articles/PMC9035852/ /pubmed/35480896 http://dx.doi.org/10.3389/fmolb.2022.807497 Text en Copyright © 2022 Zheng, Zhang, Jiang, Wang, Liu, Zhou, Zhou 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 | Molecular Biosciences Zheng, Pengdou Zhang, Huojun Jiang, Weiling Wang, Lingling Liu, Lu Zhou, Yuhao Zhou, Ling Liu, Huiguo Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title | Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title_full | Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title_fullStr | Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title_full_unstemmed | Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title_short | Establishment of a Prognostic Model of Lung Adenocarcinoma Based on Tumor Heterogeneity |
title_sort | establishment of a prognostic model of lung adenocarcinoma based on tumor heterogeneity |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035852/ https://www.ncbi.nlm.nih.gov/pubmed/35480896 http://dx.doi.org/10.3389/fmolb.2022.807497 |
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