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Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD), the major lung cancer histotype, represents 40% lung cancers. Currently, outcomes are remarkably different in LUAD patients with similar AJCC/UICC-TNM features. T cell proliferation-related regulator genes (TPRGs) relate to the proliferation, activity and func...

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Autores principales: Yang, Qin, Zhu, Weiyuan, Gong, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106713/
https://www.ncbi.nlm.nih.gov/pubmed/37077919
http://dx.doi.org/10.3389/fimmu.2023.1148483
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author Yang, Qin
Zhu, Weiyuan
Gong, Han
author_facet Yang, Qin
Zhu, Weiyuan
Gong, Han
author_sort Yang, Qin
collection PubMed
description BACKGROUND: Lung adenocarcinoma (LUAD), the major lung cancer histotype, represents 40% lung cancers. Currently, outcomes are remarkably different in LUAD patients with similar AJCC/UICC-TNM features. T cell proliferation-related regulator genes (TPRGs) relate to the proliferation, activity and function of T cells and tumor progression. The values of TPRGs in classifying LUAD patients and predicting outcomes remain unknown. METHODS: Gene expression profile and corresponding clinical data were downloaded from TCGA and the GEO databases. We systematically analyzed the expression profile characteristics of 35 TPRGs in LUAD patients and investigated the differences in overall survival (OS), biology pathway, immunity and somatic mutation between different TPRGs-related subtypes. Subsequently, we constructed a TPRGs-related risk model in TCGA cohort to quantify risk scores using LASSO cox regression analysis and then validated this risk model in two GEO cohorts. LUAD patients were divided into high- and low-risk subtypes according to the median risk score. We systematically compared the biology pathway, immunity, somatic mutation and drug susceptibility between the two risk subtypes. Finally, we validate biological functions of two TPRGs-encoded proteins (DCLRE1B and HOMER1) in LUAD cells A549. RESULTS: We identified different TPRGs-related subtypes (including cluster 1/cluster A and its counterpart cluster 2/cluster B). Compared to the cluster 1/cluster A subtype, cluster 2/cluster B subtype tended to have a prominent survival advantage with an immunosuppressive microenvironment and a higher somatic mutation frequency. Then, we constructed a TPRGs-related 6-gene risk model. The high-risk subtype characterized by higher somatic mutation frequency and lower immunotherapy response had a worse prognosis. This risk model was an independent prognostic factor and showed to be reliable and accurate for LUAD classification. Furthermore, subtypes with different risk scores were significantly associated with drug sensitivity. DCLRE1B and HOMER1 suppressed cell proliferation, migration and invasion in LUAD cells A549, which was in line with their prognostic values. CONCLUSION: We construed a novel stratification model of LUAD based on TPRGs, which can accurately and reliably predict the prognosis and might be used as a predictive tool for LUAD patients.
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spelling pubmed-101067132023-04-18 Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma Yang, Qin Zhu, Weiyuan Gong, Han Front Immunol Immunology BACKGROUND: Lung adenocarcinoma (LUAD), the major lung cancer histotype, represents 40% lung cancers. Currently, outcomes are remarkably different in LUAD patients with similar AJCC/UICC-TNM features. T cell proliferation-related regulator genes (TPRGs) relate to the proliferation, activity and function of T cells and tumor progression. The values of TPRGs in classifying LUAD patients and predicting outcomes remain unknown. METHODS: Gene expression profile and corresponding clinical data were downloaded from TCGA and the GEO databases. We systematically analyzed the expression profile characteristics of 35 TPRGs in LUAD patients and investigated the differences in overall survival (OS), biology pathway, immunity and somatic mutation between different TPRGs-related subtypes. Subsequently, we constructed a TPRGs-related risk model in TCGA cohort to quantify risk scores using LASSO cox regression analysis and then validated this risk model in two GEO cohorts. LUAD patients were divided into high- and low-risk subtypes according to the median risk score. We systematically compared the biology pathway, immunity, somatic mutation and drug susceptibility between the two risk subtypes. Finally, we validate biological functions of two TPRGs-encoded proteins (DCLRE1B and HOMER1) in LUAD cells A549. RESULTS: We identified different TPRGs-related subtypes (including cluster 1/cluster A and its counterpart cluster 2/cluster B). Compared to the cluster 1/cluster A subtype, cluster 2/cluster B subtype tended to have a prominent survival advantage with an immunosuppressive microenvironment and a higher somatic mutation frequency. Then, we constructed a TPRGs-related 6-gene risk model. The high-risk subtype characterized by higher somatic mutation frequency and lower immunotherapy response had a worse prognosis. This risk model was an independent prognostic factor and showed to be reliable and accurate for LUAD classification. Furthermore, subtypes with different risk scores were significantly associated with drug sensitivity. DCLRE1B and HOMER1 suppressed cell proliferation, migration and invasion in LUAD cells A549, which was in line with their prognostic values. CONCLUSION: We construed a novel stratification model of LUAD based on TPRGs, which can accurately and reliably predict the prognosis and might be used as a predictive tool for LUAD patients. Frontiers Media S.A. 2023-04-03 /pmc/articles/PMC10106713/ /pubmed/37077919 http://dx.doi.org/10.3389/fimmu.2023.1148483 Text en Copyright © 2023 Yang, Zhu and Gong 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 Immunology
Yang, Qin
Zhu, Weiyuan
Gong, Han
Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title_full Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title_fullStr Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title_full_unstemmed Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title_short Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
title_sort subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106713/
https://www.ncbi.nlm.nih.gov/pubmed/37077919
http://dx.doi.org/10.3389/fimmu.2023.1148483
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AT zhuweiyuan subtypeclassificationbasedontcellproliferationrelatedregulatorgenesandriskmodelforpredictingoutcomesoflungadenocarcinoma
AT gonghan subtypeclassificationbasedontcellproliferationrelatedregulatorgenesandriskmodelforpredictingoutcomesoflungadenocarcinoma