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Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer

BACKGROUND: This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in...

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Autores principales: Zhang, Heng-Chun, Deng, Shen-Hui, Pi, Ya-Nan, Guo, Jun-Nan, Xi, Hua, Shi, Xin, Yang, Xue-Fei, Zhang, Bo-Miao, Xue, Wei-Nan, Cui, Bin-Bin, Liu, Yan-Long
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014300/
https://www.ncbi.nlm.nih.gov/pubmed/35444656
http://dx.doi.org/10.3389/fimmu.2022.855849
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author Zhang, Heng-Chun
Deng, Shen-Hui
Pi, Ya-Nan
Guo, Jun-Nan
Xi, Hua
Shi, Xin
Yang, Xue-Fei
Zhang, Bo-Miao
Xue, Wei-Nan
Cui, Bin-Bin
Liu, Yan-Long
author_facet Zhang, Heng-Chun
Deng, Shen-Hui
Pi, Ya-Nan
Guo, Jun-Nan
Xi, Hua
Shi, Xin
Yang, Xue-Fei
Zhang, Bo-Miao
Xue, Wei-Nan
Cui, Bin-Bin
Liu, Yan-Long
author_sort Zhang, Heng-Chun
collection PubMed
description BACKGROUND: This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in left-sided and right-sided colon cancers (LCCs and RCCs, respectively). METHODS: We comprehensively evaluated the ferroptosis patterns in 444 LCCs and RCCs based on 59 ferroptosis-related genes (FRGs). The FS was constructed to quantify ferroptosis patterns by using principal component analysis algorithms. Next, the prognostic value and therapeutic sensitivities were evaluated using multiple methods. Finally, we performed weighted gene co-expression network analysis (WGCNA) to identify the key FRGs. The IMvigor210 cohort, TCGA-COAD proteomics cohort, and Immunophenoscores were used to verify the predictive abilities of FS and the key FRGs. RESULTS: Two ferroptosis clusters were determined. Ferroptosis cluster B demonstrated a high degree of congenital ICI and stromal-related signal enrichment with a poor prognosis. The prognosis, response of targeted inhibitors, and immunotherapy were significantly different between high and low FS groups (HSG and LSG, respectively). HSG was characterized by high TMB and microsatellite instability-high subtype with poor prognosis. Meanwhile, LSG was more likely to benefit from immunotherapy. ALOX5 was identified as a key FRG based on FS. Patients with high protein levels of ALOX5 had poorer prognoses. CONCLUSION: This work revealed that the evaluation of ferroptosis subtypes will contribute to gaining insight into the heterogeneity in LCCs and RCCs. The quantification for ferroptosis patterns played a non-negligible role in predicting ICI characterization, prognosis, and individualized immunotherapy strategies.
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spelling pubmed-90143002022-04-19 Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer Zhang, Heng-Chun Deng, Shen-Hui Pi, Ya-Nan Guo, Jun-Nan Xi, Hua Shi, Xin Yang, Xue-Fei Zhang, Bo-Miao Xue, Wei-Nan Cui, Bin-Bin Liu, Yan-Long Front Immunol Immunology BACKGROUND: This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in left-sided and right-sided colon cancers (LCCs and RCCs, respectively). METHODS: We comprehensively evaluated the ferroptosis patterns in 444 LCCs and RCCs based on 59 ferroptosis-related genes (FRGs). The FS was constructed to quantify ferroptosis patterns by using principal component analysis algorithms. Next, the prognostic value and therapeutic sensitivities were evaluated using multiple methods. Finally, we performed weighted gene co-expression network analysis (WGCNA) to identify the key FRGs. The IMvigor210 cohort, TCGA-COAD proteomics cohort, and Immunophenoscores were used to verify the predictive abilities of FS and the key FRGs. RESULTS: Two ferroptosis clusters were determined. Ferroptosis cluster B demonstrated a high degree of congenital ICI and stromal-related signal enrichment with a poor prognosis. The prognosis, response of targeted inhibitors, and immunotherapy were significantly different between high and low FS groups (HSG and LSG, respectively). HSG was characterized by high TMB and microsatellite instability-high subtype with poor prognosis. Meanwhile, LSG was more likely to benefit from immunotherapy. ALOX5 was identified as a key FRG based on FS. Patients with high protein levels of ALOX5 had poorer prognoses. CONCLUSION: This work revealed that the evaluation of ferroptosis subtypes will contribute to gaining insight into the heterogeneity in LCCs and RCCs. The quantification for ferroptosis patterns played a non-negligible role in predicting ICI characterization, prognosis, and individualized immunotherapy strategies. Frontiers Media S.A. 2022-04-04 /pmc/articles/PMC9014300/ /pubmed/35444656 http://dx.doi.org/10.3389/fimmu.2022.855849 Text en Copyright © 2022 Zhang, Deng, Pi, Guo, Xi, Shi, Yang, Zhang, Xue, Cui and Liu 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
Zhang, Heng-Chun
Deng, Shen-Hui
Pi, Ya-Nan
Guo, Jun-Nan
Xi, Hua
Shi, Xin
Yang, Xue-Fei
Zhang, Bo-Miao
Xue, Wei-Nan
Cui, Bin-Bin
Liu, Yan-Long
Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title_full Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title_fullStr Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title_full_unstemmed Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title_short Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer
title_sort identification and validation in a novel quantification system of ferroptosis patterns for the prediction of prognosis and immunotherapy response in left- and right-sided colon cancer
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014300/
https://www.ncbi.nlm.nih.gov/pubmed/35444656
http://dx.doi.org/10.3389/fimmu.2022.855849
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