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Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes

Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its po...

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Autores principales: Wu, Guodong, Feng, Dingwei, Zhang, Ziyu, Zhang, Gao, Zhang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702361/
https://www.ncbi.nlm.nih.gov/pubmed/36452156
http://dx.doi.org/10.3389/fgene.2022.1037011
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author Wu, Guodong
Feng, Dingwei
Zhang, Ziyu
Zhang, Gao
Zhang, Wei
author_facet Wu, Guodong
Feng, Dingwei
Zhang, Ziyu
Zhang, Gao
Zhang, Wei
author_sort Wu, Guodong
collection PubMed
description Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its potential regulatory mechanisms for diagnosing and treating LUAD. According to the expression profile data along with the clinical information related to LUAD from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a consistency matrix through consistency clustering, and used the ConsensusClusterPlus as the measurement distance to cluster and subtype the samples, and performed gene set enrichment analysis and immune infiltration analysis. Least absolute shrinkage and selection operator (Lasso) regression was utilized for obtaining prognostic significant necroptosis phenotype-related genes. Finally, we measured each patient’s riskscore (RS) and build a risk model, and predicted the effect of immunotherapy for different groups of risk factors in the model. Three molecular subtypes of LUAD were obtained by cluster analysis of necroptosis-related genes in LUAD samples. Compared with C1, C3 had a better prognosis and higher immune cell infiltration. The prognosis of the C1 subtype was poor and had a high clinical grade. The proportion of Stage II, Stage III, and Stage IV was much more in comparison with that of the other two subtypes. TP53 gene had a high mutation frequency in the C1 subtype. Gene Set Enrichment Analysis (GSEA) indicated that the aberrant pathways in the C1 and C3 subtypes mainly included some cell cycle-related pathways. In addition, seven genes were identified as related genes of necroptosis phenotype affecting prognosis. High RS had a poor prognosis, while low RS had a good prognosis. The RS was verified to have a strong ability to predict survival. LUAD can be classified by the genes linked with cell necrosis and apoptosis. The difference among various types is helpful to deepen the understanding of LUAD. In addition, a risk model was constructed based. In conclusion, this study provides potential detection targets and treatment methods for LUAD from a new perspective.
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spelling pubmed-97023612022-11-29 Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes Wu, Guodong Feng, Dingwei Zhang, Ziyu Zhang, Gao Zhang, Wei Front Genet Genetics Lung adenocarcinoma (LUAD) is the most widely known histological subtype of lung cancer. Its classification is significant for the characteristic evaluation of patients. The aim of this research is to assess the categorization of LUAD and its risk model based on necroptosis and to investigate its potential regulatory mechanisms for diagnosing and treating LUAD. According to the expression profile data along with the clinical information related to LUAD from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a consistency matrix through consistency clustering, and used the ConsensusClusterPlus as the measurement distance to cluster and subtype the samples, and performed gene set enrichment analysis and immune infiltration analysis. Least absolute shrinkage and selection operator (Lasso) regression was utilized for obtaining prognostic significant necroptosis phenotype-related genes. Finally, we measured each patient’s riskscore (RS) and build a risk model, and predicted the effect of immunotherapy for different groups of risk factors in the model. Three molecular subtypes of LUAD were obtained by cluster analysis of necroptosis-related genes in LUAD samples. Compared with C1, C3 had a better prognosis and higher immune cell infiltration. The prognosis of the C1 subtype was poor and had a high clinical grade. The proportion of Stage II, Stage III, and Stage IV was much more in comparison with that of the other two subtypes. TP53 gene had a high mutation frequency in the C1 subtype. Gene Set Enrichment Analysis (GSEA) indicated that the aberrant pathways in the C1 and C3 subtypes mainly included some cell cycle-related pathways. In addition, seven genes were identified as related genes of necroptosis phenotype affecting prognosis. High RS had a poor prognosis, while low RS had a good prognosis. The RS was verified to have a strong ability to predict survival. LUAD can be classified by the genes linked with cell necrosis and apoptosis. The difference among various types is helpful to deepen the understanding of LUAD. In addition, a risk model was constructed based. In conclusion, this study provides potential detection targets and treatment methods for LUAD from a new perspective. Frontiers Media S.A. 2022-11-14 /pmc/articles/PMC9702361/ /pubmed/36452156 http://dx.doi.org/10.3389/fgene.2022.1037011 Text en Copyright © 2022 Wu, Feng, Zhang, Zhang and Zhang. 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
Wu, Guodong
Feng, Dingwei
Zhang, Ziyu
Zhang, Gao
Zhang, Wei
Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title_full Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title_fullStr Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title_full_unstemmed Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title_short Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
title_sort establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702361/
https://www.ncbi.nlm.nih.gov/pubmed/36452156
http://dx.doi.org/10.3389/fgene.2022.1037011
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