In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma

Abstract Lung cancer ranks as the primary contributor to cancer-related fatalities on a global scale, hallmarked by a poor prognosis. Programmed cell death (PCD) is critically involved in regulating the onset, progression, and treatment of lung adenocarcinoma (LUAD). Existing prognostic models conce...

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Main Authors: Desheng Zhou, Yachao Cui, Jing Guo, Zhenpeng Wu, Lin Li, Wenguang Yin, Min Deng, Meiyuan Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-06130-6
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author Desheng Zhou
Yachao Cui
Jing Guo
Zhenpeng Wu
Lin Li
Wenguang Yin
Min Deng
Meiyuan Liu
author_facet Desheng Zhou
Yachao Cui
Jing Guo
Zhenpeng Wu
Lin Li
Wenguang Yin
Min Deng
Meiyuan Liu
author_sort Desheng Zhou
collection DOAJ
description Abstract Lung cancer ranks as the primary contributor to cancer-related fatalities on a global scale, hallmarked by a poor prognosis. Programmed cell death (PCD) is critically involved in regulating the onset, progression, and treatment of lung adenocarcinoma (LUAD). Existing prognostic models concerning PCD focus solely on individual mechanisms and fail to account for the intricate interaction among multiple regulatory mechanisms. In this study, the LUAD samples were sorted into low immune cell invasion subtype (C1) and high immune cell invasion subtype (C2) by clustering analysis. A PCD prognostic signature model was developed by LASSO Cox regression analysis. Tumors in the high-risk group were categorized as “cold” and characterized by immunosuppression, which was linked to an unfavorable prognosis and sensitivity to drug therapy. However, the opposite was true for the low-risk group, which was associated with a favorable prognosis and sensitivity to immunotherapy. Single-cell analysis found that the PCD signature model could activate several immune cells, thereby affecting the tumor microenvironment (TME) of LUAD. Furthermore, ENO1, could be used as a target for LUAD prognosis and immunotherapy. This study aims to comprehensively explore the functional mechanisms of various PCD regulatory patterns in LUAD to provide accurate prognosis and personalized treatment plans.
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spelling doaj-art-2fc11fe709854dbca66ef1ab35f525dc2025-08-20T04:01:51ZengNature PortfolioScientific Reports2045-23222025-07-0115112210.1038/s41598-025-06130-6In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinomaDesheng Zhou0Yachao Cui1Jing Guo2Zhenpeng Wu3Lin Li4Wenguang Yin5Min Deng6Meiyuan Liu7Guangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical UniversityGuangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical UniversityCenter of Oncology, Heyou HospitalGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical UniversityGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical UniversityGuangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical UniversityGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical UniversityAbstract Lung cancer ranks as the primary contributor to cancer-related fatalities on a global scale, hallmarked by a poor prognosis. Programmed cell death (PCD) is critically involved in regulating the onset, progression, and treatment of lung adenocarcinoma (LUAD). Existing prognostic models concerning PCD focus solely on individual mechanisms and fail to account for the intricate interaction among multiple regulatory mechanisms. In this study, the LUAD samples were sorted into low immune cell invasion subtype (C1) and high immune cell invasion subtype (C2) by clustering analysis. A PCD prognostic signature model was developed by LASSO Cox regression analysis. Tumors in the high-risk group were categorized as “cold” and characterized by immunosuppression, which was linked to an unfavorable prognosis and sensitivity to drug therapy. However, the opposite was true for the low-risk group, which was associated with a favorable prognosis and sensitivity to immunotherapy. Single-cell analysis found that the PCD signature model could activate several immune cells, thereby affecting the tumor microenvironment (TME) of LUAD. Furthermore, ENO1, could be used as a target for LUAD prognosis and immunotherapy. This study aims to comprehensively explore the functional mechanisms of various PCD regulatory patterns in LUAD to provide accurate prognosis and personalized treatment plans.https://doi.org/10.1038/s41598-025-06130-6Programmed cell deathLung adenocarcinomaCluster analysisSignature modelImmuneENO1
spellingShingle Desheng Zhou
Yachao Cui
Jing Guo
Zhenpeng Wu
Lin Li
Wenguang Yin
Min Deng
Meiyuan Liu
In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
Scientific Reports
Programmed cell death
Lung adenocarcinoma
Cluster analysis
Signature model
Immune
ENO1
title In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
title_full In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
title_fullStr In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
title_full_unstemmed In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
title_short In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma
title_sort in depth exploration of programmed cell death related subtypes and development of a prognostic signature model in lung adenocarcinoma
topic Programmed cell death
Lung adenocarcinoma
Cluster analysis
Signature model
Immune
ENO1
url https://doi.org/10.1038/s41598-025-06130-6
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