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Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma

BACKGROUND: Ferroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few st...

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Autores principales: Liu, Zhaochen, Wang, Jingju, Li, Suxin, Li, Luhao, Li, Lin, Li, Dingyang, Guo, Huahu, Gao, Dute, Liu, Shengyan, Ruan, Chengshuo, Dang, Xiaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797854/
https://www.ncbi.nlm.nih.gov/pubmed/36591279
http://dx.doi.org/10.3389/fimmu.2022.1076045
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author Liu, Zhaochen
Wang, Jingju
Li, Suxin
Li, Luhao
Li, Lin
Li, Dingyang
Guo, Huahu
Gao, Dute
Liu, Shengyan
Ruan, Chengshuo
Dang, Xiaowei
author_facet Liu, Zhaochen
Wang, Jingju
Li, Suxin
Li, Luhao
Li, Lin
Li, Dingyang
Guo, Huahu
Gao, Dute
Liu, Shengyan
Ruan, Chengshuo
Dang, Xiaowei
author_sort Liu, Zhaochen
collection PubMed
description BACKGROUND: Ferroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively. METHODS: We downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis. RESULTS: A total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p<0.0001 in the TCGA cohort and p<0.05 in the ICGC cohort). The FEPM score was proved to be an independent prognostic risk factor (HR>1, p<0.01). Furthermore, the expression profiles analysis suggested that the high-FEPM group appeared to have a more suppressive ferroptosis status and a more active EMT status than the low- FEPM group. Immune infiltration analysis showed that the myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs) were highly enriched in the high-FEPM group. Finally, a nomogram enrolling FEPM score and TNM stage was constructed showing outstanding predictive capacity for the prognosis of patients in the two cohorts. CONCLUSION: In conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients.
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spelling pubmed-97978542022-12-30 Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma Liu, Zhaochen Wang, Jingju Li, Suxin Li, Luhao Li, Lin Li, Dingyang Guo, Huahu Gao, Dute Liu, Shengyan Ruan, Chengshuo Dang, Xiaowei Front Immunol Immunology BACKGROUND: Ferroptosis is one of the main mechanisms of sorafenib against hepatocellular carcinoma (HCC). Epithelial-mesenchymal transition (EMT) plays an important role in the heterogeneity, tumor metastasis, immunosuppressive microenvironment, and drug resistance of HCC. However, there are few studies looking into the relationship between ferroptosis and EMT and how they may affect the prognosis of HCC collectively. METHODS: We downloaded gene expression and clinical data of HCC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases for prognostic model construction and validation respectively. The Least absolute shrinkage and selection operator (LASSO) Cox regression was used for model construction. The predictive ability of the model was assessed by Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve. We performed the expression profiles analysis to evaluate the ferroptosis and EMT state. CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA) methods were used for immune infiltration analysis. RESULTS: A total of thirteen crucial genes were identified for ferroptosis-related and EMT-related prognostic model (FEPM) stratifying patients into two risk groups. The high-FEPM group had shorter overall survivals than the low-FEPM group (p<0.0001 in the TCGA cohort and p<0.05 in the ICGC cohort). The FEPM score was proved to be an independent prognostic risk factor (HR>1, p<0.01). Furthermore, the expression profiles analysis suggested that the high-FEPM group appeared to have a more suppressive ferroptosis status and a more active EMT status than the low- FEPM group. Immune infiltration analysis showed that the myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs) were highly enriched in the high-FEPM group. Finally, a nomogram enrolling FEPM score and TNM stage was constructed showing outstanding predictive capacity for the prognosis of patients in the two cohorts. CONCLUSION: In conclusion, we developed a ferroptosis-related and EMT-related prognostic model, which could help predict overall survival for HCC patients. It might provide a new idea for predicting the response to targeted therapies and immunotherapies in HCC patients. Frontiers Media S.A. 2022-12-15 /pmc/articles/PMC9797854/ /pubmed/36591279 http://dx.doi.org/10.3389/fimmu.2022.1076045 Text en Copyright © 2022 Liu, Wang, Li, Li, Li, Li, Guo, Gao, Liu, Ruan and Dang 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
Liu, Zhaochen
Wang, Jingju
Li, Suxin
Li, Luhao
Li, Lin
Li, Dingyang
Guo, Huahu
Gao, Dute
Liu, Shengyan
Ruan, Chengshuo
Dang, Xiaowei
Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title_full Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title_fullStr Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title_full_unstemmed Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title_short Prognostic prediction and immune infiltration analysis based on ferroptosis and EMT state in hepatocellular carcinoma
title_sort prognostic prediction and immune infiltration analysis based on ferroptosis and emt state in hepatocellular carcinoma
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797854/
https://www.ncbi.nlm.nih.gov/pubmed/36591279
http://dx.doi.org/10.3389/fimmu.2022.1076045
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