Cargando…
Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes
BACKGROUND: Given that abnormal autophagy is involved in the pathogenesis of cancers, we sought to explore the potential value of autophagy-associated genes in lung adenocarcinoma (LUAD). METHODS: RNA sequencing and clinical data on tumour and normal samples were acquired from The Cancer Genome Atla...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115085/ https://www.ncbi.nlm.nih.gov/pubmed/32238163 http://dx.doi.org/10.1186/s12967-020-02321-z |
_version_ | 1783514025354592256 |
---|---|
author | Wang, Xiaofei Yao, Shuang Xiao, Zengtuan Gong, Jialin Liu, Zuo Han, Baoai Zhang, Zhenfa |
author_facet | Wang, Xiaofei Yao, Shuang Xiao, Zengtuan Gong, Jialin Liu, Zuo Han, Baoai Zhang, Zhenfa |
author_sort | Wang, Xiaofei |
collection | PubMed |
description | BACKGROUND: Given that abnormal autophagy is involved in the pathogenesis of cancers, we sought to explore the potential value of autophagy-associated genes in lung adenocarcinoma (LUAD). METHODS: RNA sequencing and clinical data on tumour and normal samples were acquired from The Cancer Genome Atlas (TCGA) database and randomly assigned to training and testing groups. Differentially expressed autophagy-associated genes (AAGs) were screened. Within the training group, Cox regression and Lasso regression analyses were conducted to screen five prognostic AAGs, which were used to develop a model. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were plotted to determine the performance of the model in both groups. Immunohistochemistry was used to demonstrate the differential expression of AAGs in tumour and normal tissues at the protein level. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to further elucidate the roles of AAGs in LUAD. RESULTS: The data from the TCGA database included 497 tumour and 54 normal samples, within which 30 differentially expressed AAGs were screened. Using Cox regression and Lasso regression analyses for the training group, 5 prognostic AAGs were identified and the prognostic model was constructed. Patients with low risk had better overall survival (OS) in the training group (3-year OS, 73.0% vs 48.0%; 5-year OS, 45.0% vs 33.8%; P = 1.305E−04) and in the testing group (3-year OS, 66.8% vs 41.2%; 5-year OS, 31.7% vs 25.8%; P = 1.027E−03). The areas under the ROC curves (AUC) were significant for both the training and testing groups (3-year AUC, 0.810 vs 0.894; 5-year AUC, 0.792 vs 0.749). CONCLUSIONS: We developed a survival model for LUAD and validated the performance of the model, which may provide superior outcomes for the patients. |
format | Online Article Text |
id | pubmed-7115085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71150852020-04-07 Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes Wang, Xiaofei Yao, Shuang Xiao, Zengtuan Gong, Jialin Liu, Zuo Han, Baoai Zhang, Zhenfa J Transl Med Research BACKGROUND: Given that abnormal autophagy is involved in the pathogenesis of cancers, we sought to explore the potential value of autophagy-associated genes in lung adenocarcinoma (LUAD). METHODS: RNA sequencing and clinical data on tumour and normal samples were acquired from The Cancer Genome Atlas (TCGA) database and randomly assigned to training and testing groups. Differentially expressed autophagy-associated genes (AAGs) were screened. Within the training group, Cox regression and Lasso regression analyses were conducted to screen five prognostic AAGs, which were used to develop a model. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were plotted to determine the performance of the model in both groups. Immunohistochemistry was used to demonstrate the differential expression of AAGs in tumour and normal tissues at the protein level. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to further elucidate the roles of AAGs in LUAD. RESULTS: The data from the TCGA database included 497 tumour and 54 normal samples, within which 30 differentially expressed AAGs were screened. Using Cox regression and Lasso regression analyses for the training group, 5 prognostic AAGs were identified and the prognostic model was constructed. Patients with low risk had better overall survival (OS) in the training group (3-year OS, 73.0% vs 48.0%; 5-year OS, 45.0% vs 33.8%; P = 1.305E−04) and in the testing group (3-year OS, 66.8% vs 41.2%; 5-year OS, 31.7% vs 25.8%; P = 1.027E−03). The areas under the ROC curves (AUC) were significant for both the training and testing groups (3-year AUC, 0.810 vs 0.894; 5-year AUC, 0.792 vs 0.749). CONCLUSIONS: We developed a survival model for LUAD and validated the performance of the model, which may provide superior outcomes for the patients. BioMed Central 2020-04-01 /pmc/articles/PMC7115085/ /pubmed/32238163 http://dx.doi.org/10.1186/s12967-020-02321-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Xiaofei Yao, Shuang Xiao, Zengtuan Gong, Jialin Liu, Zuo Han, Baoai Zhang, Zhenfa Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title | Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title_full | Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title_fullStr | Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title_full_unstemmed | Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title_short | Development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
title_sort | development and validation of a survival model for lung adenocarcinoma based on autophagy-associated genes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115085/ https://www.ncbi.nlm.nih.gov/pubmed/32238163 http://dx.doi.org/10.1186/s12967-020-02321-z |
work_keys_str_mv | AT wangxiaofei developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT yaoshuang developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT xiaozengtuan developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT gongjialin developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT liuzuo developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT hanbaoai developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes AT zhangzhenfa developmentandvalidationofasurvivalmodelforlungadenocarcinomabasedonautophagyassociatedgenes |