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Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer

BACKGROUND: Ferroptosis is a newly defined form of programmed cell death that plays an important role in many cancers. However, ferroptosis-related lncRNAs (FRLs) involved in the regulation of colon cancer are not thoroughly understood. This study aimed to identify a prognostic FRL signature in colo...

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Autores principales: Wu, Zhiwei, Lu, Zhixing, Li, Liang, Ma, Min, Long, Fei, Wu, Runliu, Huang, Lihua, Chou, Jing, Yang, Kaiyan, Zhang, Yi, Li, Xiaorong, Hu, Gui, Lin, Changwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826443/
https://www.ncbi.nlm.nih.gov/pubmed/35154072
http://dx.doi.org/10.3389/fimmu.2021.783362
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author Wu, Zhiwei
Lu, Zhixing
Li, Liang
Ma, Min
Long, Fei
Wu, Runliu
Huang, Lihua
Chou, Jing
Yang, Kaiyan
Zhang, Yi
Li, Xiaorong
Hu, Gui
Zhang, Yi
Lin, Changwei
author_facet Wu, Zhiwei
Lu, Zhixing
Li, Liang
Ma, Min
Long, Fei
Wu, Runliu
Huang, Lihua
Chou, Jing
Yang, Kaiyan
Zhang, Yi
Li, Xiaorong
Hu, Gui
Zhang, Yi
Lin, Changwei
author_sort Wu, Zhiwei
collection PubMed
description BACKGROUND: Ferroptosis is a newly defined form of programmed cell death that plays an important role in many cancers. However, ferroptosis-related lncRNAs (FRLs) involved in the regulation of colon cancer are not thoroughly understood. This study aimed to identify a prognostic FRL signature in colon cancer and explore its potential molecular function. METHODS: RNA-seq data and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database, and a list of ferroptosis-related genes was extracted from the FerrDb website. Analysis of differentially expressed FRLs was performed using the ‘limma’ package in R software. By implementing coexpression analysis and univariate Cox analysis, we then identified prognostic FRLs. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 4 FRLs. We evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis and receiver operating characteristic (ROC) curve analysis. Moreover, the relationships between the signature and immune landscape, somatic mutation and drug sensitivity were explored. Finally, in vitro experiments were conducted to validate the functions of AP003555.1 and AC000584.1. RESULTS: A 4-FRL signature was constructed. Two risk groups were classified based on the risk score calculated by this signature. The signature-based risk score exhibited a more powerful capacity for survival prediction than traditional clinicopathological features in colon patients. Additionally, we observed a significant difference in immune cells, such as CD4+ and CD8+ T cells and macrophages, between the two groups. Moreover, the high-risk group exhibited lower IC50 values for certain chemotherapy drugs, such as cisplatin, docetaxel, bleomycin or axitinib. Finally, the in vitro experiments showed that ferroptosis processes were suppressed after AP003555.1 and AC000584.1 knockdown. CONCLUSION: The proposed 4-FRL signature is a promising biomarker to predict clinical outcomes and therapeutic responses in colon cancer patients.
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spelling pubmed-88264432022-02-10 Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer Wu, Zhiwei Lu, Zhixing Li, Liang Ma, Min Long, Fei Wu, Runliu Huang, Lihua Chou, Jing Yang, Kaiyan Zhang, Yi Li, Xiaorong Hu, Gui Zhang, Yi Lin, Changwei Front Immunol Immunology BACKGROUND: Ferroptosis is a newly defined form of programmed cell death that plays an important role in many cancers. However, ferroptosis-related lncRNAs (FRLs) involved in the regulation of colon cancer are not thoroughly understood. This study aimed to identify a prognostic FRL signature in colon cancer and explore its potential molecular function. METHODS: RNA-seq data and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database, and a list of ferroptosis-related genes was extracted from the FerrDb website. Analysis of differentially expressed FRLs was performed using the ‘limma’ package in R software. By implementing coexpression analysis and univariate Cox analysis, we then identified prognostic FRLs. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 4 FRLs. We evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis and receiver operating characteristic (ROC) curve analysis. Moreover, the relationships between the signature and immune landscape, somatic mutation and drug sensitivity were explored. Finally, in vitro experiments were conducted to validate the functions of AP003555.1 and AC000584.1. RESULTS: A 4-FRL signature was constructed. Two risk groups were classified based on the risk score calculated by this signature. The signature-based risk score exhibited a more powerful capacity for survival prediction than traditional clinicopathological features in colon patients. Additionally, we observed a significant difference in immune cells, such as CD4+ and CD8+ T cells and macrophages, between the two groups. Moreover, the high-risk group exhibited lower IC50 values for certain chemotherapy drugs, such as cisplatin, docetaxel, bleomycin or axitinib. Finally, the in vitro experiments showed that ferroptosis processes were suppressed after AP003555.1 and AC000584.1 knockdown. CONCLUSION: The proposed 4-FRL signature is a promising biomarker to predict clinical outcomes and therapeutic responses in colon cancer patients. Frontiers Media S.A. 2022-01-26 /pmc/articles/PMC8826443/ /pubmed/35154072 http://dx.doi.org/10.3389/fimmu.2021.783362 Text en Copyright © 2022 Wu, Lu, Li, Ma, Long, Wu, Huang, Chou, Yang, Zhang, Li, Hu, Zhang and Lin 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
Wu, Zhiwei
Lu, Zhixing
Li, Liang
Ma, Min
Long, Fei
Wu, Runliu
Huang, Lihua
Chou, Jing
Yang, Kaiyan
Zhang, Yi
Li, Xiaorong
Hu, Gui
Zhang, Yi
Lin, Changwei
Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title_full Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title_fullStr Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title_full_unstemmed Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title_short Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer
title_sort identification and validation of ferroptosis-related lncrna signatures as a novel prognostic model for colon cancer
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826443/
https://www.ncbi.nlm.nih.gov/pubmed/35154072
http://dx.doi.org/10.3389/fimmu.2021.783362
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