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A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs

BACKGROUND: Necroptosis is a form of regulatory cell death (RCD) that attracts and activates immune cells, resulting in pro-tumor or anti-tumor effects. The purpose of this study was to investigate genes associated with necroptosis, to construct a risk score for predicting overall survival in patien...

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Autores principales: Li, Zedong, Fang, Jianyu, Chen, Sheng, Liu, Hao, Zhou, Jun, Huang, Jiangsheng, Liu, Sushun, Peng, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001936/
https://www.ncbi.nlm.nih.gov/pubmed/35422802
http://dx.doi.org/10.3389/fimmu.2022.870264
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author Li, Zedong
Fang, Jianyu
Chen, Sheng
Liu, Hao
Zhou, Jun
Huang, Jiangsheng
Liu, Sushun
Peng, Yu
author_facet Li, Zedong
Fang, Jianyu
Chen, Sheng
Liu, Hao
Zhou, Jun
Huang, Jiangsheng
Liu, Sushun
Peng, Yu
author_sort Li, Zedong
collection PubMed
description BACKGROUND: Necroptosis is a form of regulatory cell death (RCD) that attracts and activates immune cells, resulting in pro-tumor or anti-tumor effects. The purpose of this study was to investigate genes associated with necroptosis, to construct a risk score for predicting overall survival in patients with hepatocellular carcinoma, and to find potentially effective drugs. METHODS: The three algorithms ssGSEA, EPIC, and ESTIMATE were used to quantify the immune cell infiltration of the samples, differentially expressed genes (DEGs) analysis, and weighted gene co-expression network analysis were used to screen necroptosis related genes. Variables were screened according to random survival forest analysis, and combinations with significant p-values and a low number of genes were defined as prognostic signatures by using log-rank test after gene combination. Based on the sensitivity data of PRISM and CTRP2.0 datasets, we predicted the potential therapeutic agents for high-NRS patients. RESULTS: Seven genes such as TOP2A were used to define necroptosis-related risk score (NRS). The prognostic value of risk score was further validated, where high NRS was identified as a poor prognostic factor and tended to have higher grades of histologic grade, pathologic stage, T stage, BCLC, CLIP, and higher AFP. Higher NRS was also negatively correlated with the abundance of DCs, Neutrophils, Th17 cells, Macrophages, Endothelial, and positively correlated with Th2 cells. Necroptosis is often accompanied by the release of multiple cytokines, and we found that some cytokines were significantly correlated with both NRS and immune cells, suggesting that necroptosis may affect the infiltration of immune cells through cytokines. In addition, we found that TP53 mutations were more common in samples with high NRS, and these mutations may be associated with changes in NRS. Patients with high NRS may be more sensitive to gemcitabine, and gemcitabine may be an effective drug to improve the prognosis of patients with high NRS, which may play a role by inhibiting the expression of TOP2A. CONCLUSIONS: We constructed a necroptosis-related scoring model to predict OS in HCC patients, and NRS was associated with immune response, TP53 mutation, and poor clinical classification in HCC patients. In addition, gemcitabine may be an effective drug for high-NRS patients.
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spelling pubmed-90019362022-04-13 A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs Li, Zedong Fang, Jianyu Chen, Sheng Liu, Hao Zhou, Jun Huang, Jiangsheng Liu, Sushun Peng, Yu Front Immunol Immunology BACKGROUND: Necroptosis is a form of regulatory cell death (RCD) that attracts and activates immune cells, resulting in pro-tumor or anti-tumor effects. The purpose of this study was to investigate genes associated with necroptosis, to construct a risk score for predicting overall survival in patients with hepatocellular carcinoma, and to find potentially effective drugs. METHODS: The three algorithms ssGSEA, EPIC, and ESTIMATE were used to quantify the immune cell infiltration of the samples, differentially expressed genes (DEGs) analysis, and weighted gene co-expression network analysis were used to screen necroptosis related genes. Variables were screened according to random survival forest analysis, and combinations with significant p-values and a low number of genes were defined as prognostic signatures by using log-rank test after gene combination. Based on the sensitivity data of PRISM and CTRP2.0 datasets, we predicted the potential therapeutic agents for high-NRS patients. RESULTS: Seven genes such as TOP2A were used to define necroptosis-related risk score (NRS). The prognostic value of risk score was further validated, where high NRS was identified as a poor prognostic factor and tended to have higher grades of histologic grade, pathologic stage, T stage, BCLC, CLIP, and higher AFP. Higher NRS was also negatively correlated with the abundance of DCs, Neutrophils, Th17 cells, Macrophages, Endothelial, and positively correlated with Th2 cells. Necroptosis is often accompanied by the release of multiple cytokines, and we found that some cytokines were significantly correlated with both NRS and immune cells, suggesting that necroptosis may affect the infiltration of immune cells through cytokines. In addition, we found that TP53 mutations were more common in samples with high NRS, and these mutations may be associated with changes in NRS. Patients with high NRS may be more sensitive to gemcitabine, and gemcitabine may be an effective drug to improve the prognosis of patients with high NRS, which may play a role by inhibiting the expression of TOP2A. CONCLUSIONS: We constructed a necroptosis-related scoring model to predict OS in HCC patients, and NRS was associated with immune response, TP53 mutation, and poor clinical classification in HCC patients. In addition, gemcitabine may be an effective drug for high-NRS patients. Frontiers Media S.A. 2022-03-29 /pmc/articles/PMC9001936/ /pubmed/35422802 http://dx.doi.org/10.3389/fimmu.2022.870264 Text en Copyright © 2022 Li, Fang, Chen, Liu, Zhou, Huang, Liu and Peng 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
Li, Zedong
Fang, Jianyu
Chen, Sheng
Liu, Hao
Zhou, Jun
Huang, Jiangsheng
Liu, Sushun
Peng, Yu
A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title_full A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title_fullStr A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title_full_unstemmed A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title_short A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs
title_sort risk model developed based on necroptosis predicts overall survival for hepatocellular carcinoma and identification of possible therapeutic drugs
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001936/
https://www.ncbi.nlm.nih.gov/pubmed/35422802
http://dx.doi.org/10.3389/fimmu.2022.870264
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