Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes

Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zhong-zhong Zhu [verfasserIn] Guanglin Zhang [verfasserIn] Jianping Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	biomarker prognosis gastric cancer treatment response necroptosis

Übergeordnetes Werk:	In: Pathology and Oncology Research - Frontiers Media S.A., 2021, 28(2022)
Übergeordnetes Werk:	volume:28 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/pore.2022.1610641

Katalog-ID:	DOAJ095899006

Internformat


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520			\|a Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.
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650		4	\|a prognosis
650		4	\|a gastric cancer
650		4	\|a treatment response
650		4	\|a necroptosis
653		0	\|a Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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700	0		\|a Guanglin Zhang \|e verfasserin \|4 aut
700	0		\|a Jianping Liu \|e verfasserin \|4 aut
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allfields	10.3389/pore.2022.1610641 doi (DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d DE-627 ger DE-627 rakwb eng RC254-282 RB1-214 Zhong-zhong Zhu verfasserin aut Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research. biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology Guanglin Zhang verfasserin aut Jianping Liu verfasserin aut In Pathology and Oncology Research Frontiers Media S.A., 2021 28(2022) (DE-627)32042054X (DE-600)2002501-4 15322807 nnns volume:28 year:2022 https://doi.org/10.3389/pore.2022.1610641 kostenfrei https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d kostenfrei https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full kostenfrei https://doaj.org/toc/1532-2807 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022
spelling	10.3389/pore.2022.1610641 doi (DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d DE-627 ger DE-627 rakwb eng RC254-282 RB1-214 Zhong-zhong Zhu verfasserin aut Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research. biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology Guanglin Zhang verfasserin aut Jianping Liu verfasserin aut In Pathology and Oncology Research Frontiers Media S.A., 2021 28(2022) (DE-627)32042054X (DE-600)2002501-4 15322807 nnns volume:28 year:2022 https://doi.org/10.3389/pore.2022.1610641 kostenfrei https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d kostenfrei https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full kostenfrei https://doaj.org/toc/1532-2807 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022
allfields_unstemmed	10.3389/pore.2022.1610641 doi (DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d DE-627 ger DE-627 rakwb eng RC254-282 RB1-214 Zhong-zhong Zhu verfasserin aut Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research. biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology Guanglin Zhang verfasserin aut Jianping Liu verfasserin aut In Pathology and Oncology Research Frontiers Media S.A., 2021 28(2022) (DE-627)32042054X (DE-600)2002501-4 15322807 nnns volume:28 year:2022 https://doi.org/10.3389/pore.2022.1610641 kostenfrei https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d kostenfrei https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full kostenfrei https://doaj.org/toc/1532-2807 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022
allfieldsGer	10.3389/pore.2022.1610641 doi (DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d DE-627 ger DE-627 rakwb eng RC254-282 RB1-214 Zhong-zhong Zhu verfasserin aut Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research. biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology Guanglin Zhang verfasserin aut Jianping Liu verfasserin aut In Pathology and Oncology Research Frontiers Media S.A., 2021 28(2022) (DE-627)32042054X (DE-600)2002501-4 15322807 nnns volume:28 year:2022 https://doi.org/10.3389/pore.2022.1610641 kostenfrei https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d kostenfrei https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full kostenfrei https://doaj.org/toc/1532-2807 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022
allfieldsSound	10.3389/pore.2022.1610641 doi (DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d DE-627 ger DE-627 rakwb eng RC254-282 RB1-214 Zhong-zhong Zhu verfasserin aut Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research. biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology Guanglin Zhang verfasserin aut Jianping Liu verfasserin aut In Pathology and Oncology Research Frontiers Media S.A., 2021 28(2022) (DE-627)32042054X (DE-600)2002501-4 15322807 nnns volume:28 year:2022 https://doi.org/10.3389/pore.2022.1610641 kostenfrei https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d kostenfrei https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full kostenfrei https://doaj.org/toc/1532-2807 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2004 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 28 2022
language	English
source	In Pathology and Oncology Research 28(2022) volume:28 year:2022
sourceStr	In Pathology and Oncology Research 28(2022) volume:28 year:2022
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topic_facet	biomarker prognosis gastric cancer treatment response necroptosis Neoplasms. Tumors. Oncology. Including cancer and carcinogens Pathology
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container_title	Pathology and Oncology Research
authorswithroles_txt_mv	Zhong-zhong Zhu @@aut@@ Guanglin Zhang @@aut@@ Jianping Liu @@aut@@
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callnumber-first	R - Medicine
author	Zhong-zhong Zhu
spellingShingle	Zhong-zhong Zhu misc RC254-282 misc RB1-214 misc biomarker misc prognosis misc gastric cancer misc treatment response misc necroptosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens misc Pathology Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes
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topic_title	RC254-282 RB1-214 Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes biomarker prognosis gastric cancer treatment response necroptosis
topic	misc RC254-282 misc RB1-214 misc biomarker misc prognosis misc gastric cancer misc treatment response misc necroptosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens misc Pathology
topic_unstemmed	misc RC254-282 misc RB1-214 misc biomarker misc prognosis misc gastric cancer misc treatment response misc necroptosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens misc Pathology
topic_browse	misc RC254-282 misc RB1-214 misc biomarker misc prognosis misc gastric cancer misc treatment response misc necroptosis misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens misc Pathology
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title	Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes
ctrlnum	(DE-627)DOAJ095899006 (DE-599)DOAJ3500dbb6284c4c11a6e0f25af6032e3d
title_full	Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes
author_sort	Zhong-zhong Zhu
journal	Pathology and Oncology Research
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author_browse	Zhong-zhong Zhu Guanglin Zhang Jianping Liu
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title_sort	establishment of a novel prognostic prediction model for gastric cancer based on necroptosis-related genes
callnumber	RC254-282
title_auth	Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes
abstract	Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.
abstractGer	Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.
abstract_unstemmed	Background: Necroptosis plays a crucial role in the progression of multiple types of cancer. However, the role of necroptosis in gastric cancer (GC) remains unclear. The aim of this study is to establish a necroptosis-related prediction model, which could provide information for treatment monitoring.Methods: The TCGA-STAD cohort was employed to establish a prognostic prediction signature and the GEO dataset was employed for external validation. The correlation between the risk score and the immune landscape, tumor mutational burden (TMB), microsatellite instability (MSI), as well as therapeutic responses of different therapies were analyzed.Results: We constructed a prognostic model based on necroptosis-associated genes (NAGs), and its favorable predictive ability was confirmed in an external cohort. The risk score was confirmed as an independent determinant, and a nomogram was further established for prognosis. A high score implies higher tumor immune microenvironment (TIME) scores and more significant TIME cell infiltration. High-risk patients presented with lower TMB, and low-TMB patients had worse overall survival (OS). Meanwhile, Low-risk scores are characterized by MSI-high (MSI-H), lower Tumor Immune Dysfunction and Exclusion (TIDE) score, and higher immunogenicity in immunophenoscore (IPS) analysis.Conclusion: The developed NAG score provides a novel and effective method for predicting the outcome of GC as well as potential targets for further research.
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title_short	Establishment of a Novel Prognostic Prediction Model for Gastric Cancer Based on Necroptosis-Related Genes
url	https://doi.org/10.3389/pore.2022.1610641 https://doaj.org/article/3500dbb6284c4c11a6e0f25af6032e3d https://www.por-journal.com/articles/10.3389/pore.2022.1610641/full https://doaj.org/toc/1532-2807
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up_date	2024-07-03T17:15:51.203Z
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