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Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma
Immunotherapy is a vital treatment for patients with cutaneous melanoma (CM), but effective predictors to guide clinical immunotherapy are lacking. Cuproptosis is a newly discovered mode of cell death related to tumorigenesis. Exploring the relationship between the mode of cuproptosis and the effect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885583/ https://www.ncbi.nlm.nih.gov/pubmed/36717900 http://dx.doi.org/10.1186/s12967-023-03891-4 |
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author | Liu, Da Yang, Fan Zhang, Tongtong Mao, Rui |
author_facet | Liu, Da Yang, Fan Zhang, Tongtong Mao, Rui |
author_sort | Liu, Da |
collection | PubMed |
description | Immunotherapy is a vital treatment for patients with cutaneous melanoma (CM), but effective predictors to guide clinical immunotherapy are lacking. Cuproptosis is a newly discovered mode of cell death related to tumorigenesis. Exploring the relationship between the mode of cuproptosis and the effect of immunotherapy on CM could better guide clinical management. We clustered all patients with CM in the Cancer Genome Atlas (TCGA) database based on cuproptosis-related genes (CRGs). Prognosis, immunotherapeutic effect, tumor microenvironment score, expression of CD274, CTLA4, and PDCD1, and abundance of CD8 + T infiltration in group A were higher than in group B. Using a combination of LASSO and COX regression analysis, we identified 10 molecules significant to prognosis from differentially expressed genes between the two groups and constructed a cuproptosis-related scoring system (CRSS). Compared with the American Joint Committee on Cancer (AJCC) staging system, CRSS more accurately stratified CM patient risk and guided immunotherapy. CRSS successfully stratified risk and predicted the effect of immunotherapy in 869 patients with eight CM immunotherapy datasets and multiple other tumor immunotherapy cohorts. The nomogram model, which combined AJCC stage and CRSS, greatly improved the ability and accuracy of prognosis prediction. In general, our cuproptosis-related scoring system and nomogram model accurately stratified risk in CM patients and effectively predicted prognosis and the effect of immunotherapy in CM patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03891-4. |
format | Online Article Text |
id | pubmed-9885583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98855832023-01-31 Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma Liu, Da Yang, Fan Zhang, Tongtong Mao, Rui J Transl Med Research Immunotherapy is a vital treatment for patients with cutaneous melanoma (CM), but effective predictors to guide clinical immunotherapy are lacking. Cuproptosis is a newly discovered mode of cell death related to tumorigenesis. Exploring the relationship between the mode of cuproptosis and the effect of immunotherapy on CM could better guide clinical management. We clustered all patients with CM in the Cancer Genome Atlas (TCGA) database based on cuproptosis-related genes (CRGs). Prognosis, immunotherapeutic effect, tumor microenvironment score, expression of CD274, CTLA4, and PDCD1, and abundance of CD8 + T infiltration in group A were higher than in group B. Using a combination of LASSO and COX regression analysis, we identified 10 molecules significant to prognosis from differentially expressed genes between the two groups and constructed a cuproptosis-related scoring system (CRSS). Compared with the American Joint Committee on Cancer (AJCC) staging system, CRSS more accurately stratified CM patient risk and guided immunotherapy. CRSS successfully stratified risk and predicted the effect of immunotherapy in 869 patients with eight CM immunotherapy datasets and multiple other tumor immunotherapy cohorts. The nomogram model, which combined AJCC stage and CRSS, greatly improved the ability and accuracy of prognosis prediction. In general, our cuproptosis-related scoring system and nomogram model accurately stratified risk in CM patients and effectively predicted prognosis and the effect of immunotherapy in CM patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03891-4. BioMed Central 2023-01-30 /pmc/articles/PMC9885583/ /pubmed/36717900 http://dx.doi.org/10.1186/s12967-023-03891-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liu, Da Yang, Fan Zhang, Tongtong Mao, Rui Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title | Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title_full | Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title_fullStr | Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title_full_unstemmed | Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title_short | Leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
title_sort | leveraging a cuproptosis-based signature to predict the prognosis and drug sensitivity of cutaneous melanoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885583/ https://www.ncbi.nlm.nih.gov/pubmed/36717900 http://dx.doi.org/10.1186/s12967-023-03891-4 |
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