Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients

Abstract Currently, effective prediction models for patients with advanced and postoperative gastric cancer (GC) are lacking. Programmed cell death (PCD) plays a crucial role in the development and metastasis of malignant tumors. This study aimed to investigate the underlying PCD-related molecular m...

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Main Authors: Huiheng Qu, Peng Zhou, Zhihui Yang, Hao Wang, Kaiyuan Deng, Nan Wang, Yuyang Li, Yupeng Zhao, Yigang Chen, Qian Yang, Jiazeng Xia
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-06424-9
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author Huiheng Qu
Peng Zhou
Zhihui Yang
Hao Wang
Kaiyuan Deng
Nan Wang
Yuyang Li
Yupeng Zhao
Yigang Chen
Qian Yang
Jiazeng Xia
author_facet Huiheng Qu
Peng Zhou
Zhihui Yang
Hao Wang
Kaiyuan Deng
Nan Wang
Yuyang Li
Yupeng Zhao
Yigang Chen
Qian Yang
Jiazeng Xia
author_sort Huiheng Qu
collection DOAJ
description Abstract Currently, effective prediction models for patients with advanced and postoperative gastric cancer (GC) are lacking. Programmed cell death (PCD) plays a crucial role in the development and metastasis of malignant tumors. This study aimed to investigate the underlying PCD-related molecular mechanisms and develop predictive models for GC. GC profiles were collected from TCGA-STAD, GSE84433, GSE62254, and GSE183904 databases. Differential expression analysis was conducted to identify PCD-related genes (differentially expressed genes (DEGs)), which were then subjected to functional analyses. Cox proportional hazards analyses were used to select PCD-related prognostic DEGs, and a cell death index (CDI) model was proposed. The performance of this model, tumor molecular subtypes, and the tumor microenvironment were assessed. Additionally, drug sensitivity and immune checkpoint expression were examined based on the CDI model. A total of 345 PCD-related DEGs were identified, enriched in processes such as autophagy, apoptosis, necroptosis, ferroptosis, and signaling pathways including p53, NOD-like receptor, IL-17, NF-kappa B, and PI3K-Akt. Subsequently, a CDI model comprising 17 PCD-related prognostic DEGs was constructed, demonstrating superior predictive capability. GC samples were classified into three distinct clustering subtypes, with cluster 1 exhibiting the best overall survival, followed by cluster 3 and cluster 2. Eight immune cell types were significantly associated with the CDI risk score. Furthermore, the CDI risk score exhibited positive correlations with most drugs (except for BMS.754807). Additionally, the expression of immune checkpoint genes PDCD1, CD274, and IDO1 was notably upregulated in the low-risk CDI group. Our developed CDI model, based on 17 PCD-associated prognostic genes, can be employed for risk assessment and prognosis prediction in patients with GC.
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spelling doaj-art-b96d2e84d8b74a43a8a8a03f5ed0dcf42025-08-20T03:03:24ZengNature PortfolioScientific Reports2045-23222025-07-0115111810.1038/s41598-025-06424-9Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patientsHuiheng Qu0Peng Zhou1Zhihui Yang2Hao Wang3Kaiyuan Deng4Nan Wang5Yuyang Li6Yupeng Zhao7Yigang Chen8Qian Yang9Jiazeng Xia10Department of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityWake Forest Baptist Comprehensive Cancer Center, Wake Forest Baptist Medical CenterDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityThe Afliated Wuxi No. 2 People’s Hospital of Nanjing Medical UniversityDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityWake Forest Baptist Comprehensive Cancer Center, Wake Forest Baptist Medical CenterDepartment of General Surgery, Wuxi No. 2 People’s Hospital, Institute of General Surgery, Jiangnan University Medical Center, Jiangnan UniversityAbstract Currently, effective prediction models for patients with advanced and postoperative gastric cancer (GC) are lacking. Programmed cell death (PCD) plays a crucial role in the development and metastasis of malignant tumors. This study aimed to investigate the underlying PCD-related molecular mechanisms and develop predictive models for GC. GC profiles were collected from TCGA-STAD, GSE84433, GSE62254, and GSE183904 databases. Differential expression analysis was conducted to identify PCD-related genes (differentially expressed genes (DEGs)), which were then subjected to functional analyses. Cox proportional hazards analyses were used to select PCD-related prognostic DEGs, and a cell death index (CDI) model was proposed. The performance of this model, tumor molecular subtypes, and the tumor microenvironment were assessed. Additionally, drug sensitivity and immune checkpoint expression were examined based on the CDI model. A total of 345 PCD-related DEGs were identified, enriched in processes such as autophagy, apoptosis, necroptosis, ferroptosis, and signaling pathways including p53, NOD-like receptor, IL-17, NF-kappa B, and PI3K-Akt. Subsequently, a CDI model comprising 17 PCD-related prognostic DEGs was constructed, demonstrating superior predictive capability. GC samples were classified into three distinct clustering subtypes, with cluster 1 exhibiting the best overall survival, followed by cluster 3 and cluster 2. Eight immune cell types were significantly associated with the CDI risk score. Furthermore, the CDI risk score exhibited positive correlations with most drugs (except for BMS.754807). Additionally, the expression of immune checkpoint genes PDCD1, CD274, and IDO1 was notably upregulated in the low-risk CDI group. Our developed CDI model, based on 17 PCD-associated prognostic genes, can be employed for risk assessment and prognosis prediction in patients with GC.https://doi.org/10.1038/s41598-025-06424-9Programmed cell deathCell death index modelPrognosisImmunotherapyGastric cancer
spellingShingle Huiheng Qu
Peng Zhou
Zhihui Yang
Hao Wang
Kaiyuan Deng
Nan Wang
Yuyang Li
Yupeng Zhao
Yigang Chen
Qian Yang
Jiazeng Xia
Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
Scientific Reports
Programmed cell death
Cell death index model
Prognosis
Immunotherapy
Gastric cancer
title Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
title_full Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
title_fullStr Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
title_full_unstemmed Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
title_short Comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern-related genes in gastric cancer patients
title_sort comprehensive analysis of prognosis and drug sensitivity of programmed cell death pattern related genes in gastric cancer patients
topic Programmed cell death
Cell death index model
Prognosis
Immunotherapy
Gastric cancer
url https://doi.org/10.1038/s41598-025-06424-9
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