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A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma
Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identif...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354044/ https://www.ncbi.nlm.nih.gov/pubmed/35938036 http://dx.doi.org/10.3389/fgene.2022.959456 |
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author | Zhou, Yi Shu, Qi Fu, Zailin Wang, Chen Gu, Jianrong Li, Jianbo Chen, Yifang Xie, Minghua |
author_facet | Zhou, Yi Shu, Qi Fu, Zailin Wang, Chen Gu, Jianrong Li, Jianbo Chen, Yifang Xie, Minghua |
author_sort | Zhou, Yi |
collection | PubMed |
description | Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identified using the Pearson correlation algorithm. Through the univariate and multivariate Cox regression analysis, the prognosis of seven lncRNAs associated with cuproptosis was established and a new risk model was constructed. ESTIMATE, CIBERSORT, and single sample gene set enrichment analyses (ssGSEA) were applied to evaluate the immune microenvironment landscape. The Kaplan–Meier survival analysis revealed that the overall survival (OS) of CM patients in the high-risk group was remarkably lower than that of the low-risk group. The result of the validated cohort and the training cohort indicated that the risk model could produce an accurate prediction of the prognosis of CM. The nomogram result demonstrated that the risk score based on the seven prognostic cuproptosis-related lncRNAs was an independent prognostic indicator feature that distinguished it from other clinical features. The result of the immune microenvironment landscape indicated that the low-risk group showed better immunity than high-risk group. The immunophenoscore (IPS) and immune checkpoints results conveyed a better benefit potential for immunotherapy clinical application in the low-risk groups. The enrichment analysis and the gene set variation analysis (GSVA) were adopted to reveal the role of cuproptosis-related lncRNAs mediated by the immune-related signaling pathways in the development of CM. Altogether, the construction of the risk model based on cuproptosis-related lncRNAs can accurately predict the prognosis of CM and indicate the immune microenvironment of CM, providing a new perspective for the future clinical treatment of CM. |
format | Online Article Text |
id | pubmed-9354044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93540442022-08-06 A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma Zhou, Yi Shu, Qi Fu, Zailin Wang, Chen Gu, Jianrong Li, Jianbo Chen, Yifang Xie, Minghua Front Genet Genetics Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identified using the Pearson correlation algorithm. Through the univariate and multivariate Cox regression analysis, the prognosis of seven lncRNAs associated with cuproptosis was established and a new risk model was constructed. ESTIMATE, CIBERSORT, and single sample gene set enrichment analyses (ssGSEA) were applied to evaluate the immune microenvironment landscape. The Kaplan–Meier survival analysis revealed that the overall survival (OS) of CM patients in the high-risk group was remarkably lower than that of the low-risk group. The result of the validated cohort and the training cohort indicated that the risk model could produce an accurate prediction of the prognosis of CM. The nomogram result demonstrated that the risk score based on the seven prognostic cuproptosis-related lncRNAs was an independent prognostic indicator feature that distinguished it from other clinical features. The result of the immune microenvironment landscape indicated that the low-risk group showed better immunity than high-risk group. The immunophenoscore (IPS) and immune checkpoints results conveyed a better benefit potential for immunotherapy clinical application in the low-risk groups. The enrichment analysis and the gene set variation analysis (GSVA) were adopted to reveal the role of cuproptosis-related lncRNAs mediated by the immune-related signaling pathways in the development of CM. Altogether, the construction of the risk model based on cuproptosis-related lncRNAs can accurately predict the prognosis of CM and indicate the immune microenvironment of CM, providing a new perspective for the future clinical treatment of CM. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9354044/ /pubmed/35938036 http://dx.doi.org/10.3389/fgene.2022.959456 Text en Copyright © 2022 Zhou, Shu, Fu, Wang, Gu, Li, Chen and Xie. 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 | Genetics Zhou, Yi Shu, Qi Fu, Zailin Wang, Chen Gu, Jianrong Li, Jianbo Chen, Yifang Xie, Minghua A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title | A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title_full | A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title_fullStr | A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title_full_unstemmed | A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title_short | A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
title_sort | novel risk model based on cuproptosis-related lncrnas predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354044/ https://www.ncbi.nlm.nih.gov/pubmed/35938036 http://dx.doi.org/10.3389/fgene.2022.959456 |
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