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Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer

Cuproptosis, a novel form of copper-mediated regulated cell death, participates in tumor progression. However, the role of cuproptosis-related genes (CRGs) in colorectal cancer (CRC) remains unclear. We aimed to investigate the cuproptosis subtypes and build a predictive model to improve the prognos...

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Autores principales: Huang, Yan, Yin, Dongzhi, Wu, Lina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576756/
https://www.ncbi.nlm.nih.gov/pubmed/36253436
http://dx.doi.org/10.1038/s41598-022-22300-2
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author Huang, Yan
Yin, Dongzhi
Wu, Lina
author_facet Huang, Yan
Yin, Dongzhi
Wu, Lina
author_sort Huang, Yan
collection PubMed
description Cuproptosis, a novel form of copper-mediated regulated cell death, participates in tumor progression. However, the role of cuproptosis-related genes (CRGs) in colorectal cancer (CRC) remains unclear. We aimed to investigate the cuproptosis subtypes and build a predictive model to improve the prognosis of patients with CRC. Gene expression data were downloaded from the TCGA database to identify distinct molecular subtypes using a non-negative matrix factorization algorithm. A robust and efficient prognostic signature was constructed by performing multivariate Cox regression analysis and further validated using the Gene Expression Omnibus cohort. Based on the gene expression matrix of CRC, the abundance of infiltrating immune cells and tumour microenvironment scores were calculated using the CIBERSORT and ESTIMATE algorithms, respectively. The pRRophetic algorithm was used to predict the sensitivity of the patients to different chemotherapy drugs. Two distinct molecular subtypes were identified based on 41 CRGs, with subtype C1 being characterized by an advanced clinical stage and worse overall survival. A prognostic signature was constructed based on the DEGs between the two cuproptosis subtypes, and its predictive ability was validated in an external database. Patients with CRC who belonged to the low-risk group had significantly higher survival rates than those who belonged to the high-risk group. Additionally, it remained a valid prognostic indicator in strata of age, sex, tumor location, and TNM stage, and its significance persisted after the multivariate Cox regression analysis. By further analyzing the prognostic signature, a higher immune score was observed in the low-risk group, which presented a better prognosis. AKT.inhibitor.VIII, doxorubicin, lenalidomide, and tipiparnib were more sensitive in the high-risk score group. A highly accurate nomogram was constructed to improve clinical application of the risk score. Compared with an ideal nomogram, our model, consisting of clinicopathological features, performed well in predicting patient survival. In conclusion, our study provides new ways and perspectives for the prediction of the prognosis of patients with CRC and guide more effective treatment regimens.
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spelling pubmed-95767562022-10-19 Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer Huang, Yan Yin, Dongzhi Wu, Lina Sci Rep Article Cuproptosis, a novel form of copper-mediated regulated cell death, participates in tumor progression. However, the role of cuproptosis-related genes (CRGs) in colorectal cancer (CRC) remains unclear. We aimed to investigate the cuproptosis subtypes and build a predictive model to improve the prognosis of patients with CRC. Gene expression data were downloaded from the TCGA database to identify distinct molecular subtypes using a non-negative matrix factorization algorithm. A robust and efficient prognostic signature was constructed by performing multivariate Cox regression analysis and further validated using the Gene Expression Omnibus cohort. Based on the gene expression matrix of CRC, the abundance of infiltrating immune cells and tumour microenvironment scores were calculated using the CIBERSORT and ESTIMATE algorithms, respectively. The pRRophetic algorithm was used to predict the sensitivity of the patients to different chemotherapy drugs. Two distinct molecular subtypes were identified based on 41 CRGs, with subtype C1 being characterized by an advanced clinical stage and worse overall survival. A prognostic signature was constructed based on the DEGs between the two cuproptosis subtypes, and its predictive ability was validated in an external database. Patients with CRC who belonged to the low-risk group had significantly higher survival rates than those who belonged to the high-risk group. Additionally, it remained a valid prognostic indicator in strata of age, sex, tumor location, and TNM stage, and its significance persisted after the multivariate Cox regression analysis. By further analyzing the prognostic signature, a higher immune score was observed in the low-risk group, which presented a better prognosis. AKT.inhibitor.VIII, doxorubicin, lenalidomide, and tipiparnib were more sensitive in the high-risk score group. A highly accurate nomogram was constructed to improve clinical application of the risk score. Compared with an ideal nomogram, our model, consisting of clinicopathological features, performed well in predicting patient survival. In conclusion, our study provides new ways and perspectives for the prediction of the prognosis of patients with CRC and guide more effective treatment regimens. Nature Publishing Group UK 2022-10-17 /pmc/articles/PMC9576756/ /pubmed/36253436 http://dx.doi.org/10.1038/s41598-022-22300-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Article
Huang, Yan
Yin, Dongzhi
Wu, Lina
Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title_full Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title_fullStr Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title_full_unstemmed Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title_short Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
title_sort identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576756/
https://www.ncbi.nlm.nih.gov/pubmed/36253436
http://dx.doi.org/10.1038/s41598-022-22300-2
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