Identification of a prognostic model using cuproptosis-related genes in uveal melanoma

The most common intraocular malignancy in adults remains uveal melanoma (UVM), and those with metastatic disease have a poor outlook. Proliferation, angiogenesis, and metastasis of tumor cells can be triggered by cuproptosis, affecting the survival of cancer patients. Nonetheless, cuproptosis-relate...

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Main Authors: Yao Chen, Xiaozhen Chen, Xianggui Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Cell and Developmental Biology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fcell.2022.973073/full
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author Yao Chen
Yao Chen
Yao Chen
Xiaozhen Chen
Xiaozhen Chen
Xianggui Wang
Xianggui Wang
Xianggui Wang
author_facet Yao Chen
Yao Chen
Yao Chen
Xiaozhen Chen
Xiaozhen Chen
Xianggui Wang
Xianggui Wang
Xianggui Wang
author_sort Yao Chen
collection DOAJ
description The most common intraocular malignancy in adults remains uveal melanoma (UVM), and those with metastatic disease have a poor outlook. Proliferation, angiogenesis, and metastasis of tumor cells can be triggered by cuproptosis, affecting the survival of cancer patients. Nonetheless, cuproptosis-related genes (CRGs) have not been identified in UVM. In this study, we analyzed 10 CRGs in 80 patients with UVM in the Cancer Genome Atlas (TCGA) database regarding the alterations of the genes including copy number variation and methylation. We further constructed a prognostic gene model using these CRGs and built the risk score formula. Univariate and multivariate Cox regression was applied to validate the risk score as an independent prognostic factor. The prognostic model was validated using 63 UVM samples from the GSE22138 cohort, an independent validation data set. Based on the risk scores for 80 patients with UVM from TCGA, we categorized the patients into high- and low-risk groups. Differentially expressed genes (DEGs) between groups were enriched in allograft rejection, hypoxia, glycolysis, TNFα signaling via NF-κB, and interferon-γ responses via Gene set enrichment analysis (GSEA). CD8 T cells and exhausted T cells were notably enriched in the high-risk group. In conclusion, the alteration of CRGs is related to patients with UVM, and the constructed CRG-related model may be helpful to predict the prognosis of such patients.
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spelling doaj.art-29c20e35d38e4a258da1a97cbc21a8c82022-12-22T01:38:23ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2022-08-011010.3389/fcell.2022.973073973073Identification of a prognostic model using cuproptosis-related genes in uveal melanomaYao Chen0Yao Chen1Yao Chen2Xiaozhen Chen3Xiaozhen Chen4Xianggui Wang5Xianggui Wang6Xianggui Wang7Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, ChinaHunan Key Laboratory of Ophthalmology, Xiangya Hospital, Central South University, Changsha, ChinaNational Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, ChinaNational Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, ChinaHunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Ophthalmology, Xiangya Hospital, Central South University, Changsha, ChinaHunan Key Laboratory of Ophthalmology, Xiangya Hospital, Central South University, Changsha, ChinaNational Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, ChinaThe most common intraocular malignancy in adults remains uveal melanoma (UVM), and those with metastatic disease have a poor outlook. Proliferation, angiogenesis, and metastasis of tumor cells can be triggered by cuproptosis, affecting the survival of cancer patients. Nonetheless, cuproptosis-related genes (CRGs) have not been identified in UVM. In this study, we analyzed 10 CRGs in 80 patients with UVM in the Cancer Genome Atlas (TCGA) database regarding the alterations of the genes including copy number variation and methylation. We further constructed a prognostic gene model using these CRGs and built the risk score formula. Univariate and multivariate Cox regression was applied to validate the risk score as an independent prognostic factor. The prognostic model was validated using 63 UVM samples from the GSE22138 cohort, an independent validation data set. Based on the risk scores for 80 patients with UVM from TCGA, we categorized the patients into high- and low-risk groups. Differentially expressed genes (DEGs) between groups were enriched in allograft rejection, hypoxia, glycolysis, TNFα signaling via NF-κB, and interferon-γ responses via Gene set enrichment analysis (GSEA). CD8 T cells and exhausted T cells were notably enriched in the high-risk group. In conclusion, the alteration of CRGs is related to patients with UVM, and the constructed CRG-related model may be helpful to predict the prognosis of such patients.https://www.frontiersin.org/articles/10.3389/fcell.2022.973073/fulluveal melanomacuproptosissignatureprognosisbioinfomatics
spellingShingle Yao Chen
Yao Chen
Yao Chen
Xiaozhen Chen
Xiaozhen Chen
Xianggui Wang
Xianggui Wang
Xianggui Wang
Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
Frontiers in Cell and Developmental Biology
uveal melanoma
cuproptosis
signature
prognosis
bioinfomatics
title Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
title_full Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
title_fullStr Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
title_full_unstemmed Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
title_short Identification of a prognostic model using cuproptosis-related genes in uveal melanoma
title_sort identification of a prognostic model using cuproptosis related genes in uveal melanoma
topic uveal melanoma
cuproptosis
signature
prognosis
bioinfomatics
url https://www.frontiersin.org/articles/10.3389/fcell.2022.973073/full
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