Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes

Background: Uveal melanoma (UM) is the most aggressive intraocular tumor worldwide. Accurate prognostic models are urgently needed. The present research aimed to construct and validate a prognostic signature is associated with overall survival (OS) for UM patients based on metabolism-related genes...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Han Zhao, Yun Chen, Peijun Shen, Lan Gong
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	uveal melanoma metabolism tcga geo prognostic model immune cell infiltration Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/ff4021cbc2094952bfbe48cac45e7380
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ff4021cbc2094952bfbe48cac45e7380
record_format	dspace
spelling	oai:doaj.org-article:ff4021cbc2094952bfbe48cac45e73802021-11-23T03:05:02ZConstruction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes10.3934/mbe.20213991551-0018https://doaj.org/article/ff4021cbc2094952bfbe48cac45e73802021-09-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021399?viewType=HTMLhttps://doaj.org/toc/1551-0018Background: Uveal melanoma (UM) is the most aggressive intraocular tumor worldwide. Accurate prognostic models are urgently needed. The present research aimed to construct and validate a prognostic signature is associated with overall survival (OS) for UM patients based on metabolism-related genes (MRGs). Methods: MRGs were obtained from molecular signature database (MSigDB). The gene expression profiles and patient clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. In the training datasets, MRGs were analyzed through univariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) Cox analyses to build a prognostic model. The GSE84976 was treated as the validation cohort. In addition, time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival curve analyses the reliability of the developed model. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. Nomogram that combined the five-gene signature was used to evaluate the predictive OS value of UM patients. Results: Five MRGs were identified and used to establish the prognostic model for UM patients. The model was successfully validated using the testing cohort. Moreover, ROC analysis demonstrated a strong predictive ability that our prognostic signature had for UM prognosis. Multivariable Cox regression analysis revealed that the risk model was an independent predictor of prognosis. UM patients with a high-risk score showed a higher level of immune checkpoint molecules. Conclusion: We established a novel metabolism-related signature that could predict survival and might be therapeutic targets for the treatment of UM patients.Han Zhao Yun ChenPeijun ShenLan GongAIMS Pressarticleuveal melanomametabolismtcgageoprognostic modelimmune cell infiltrationBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 8045-8063 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	uveal melanoma metabolism tcga geo prognostic model immune cell infiltration Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	uveal melanoma metabolism tcga geo prognostic model immune cell infiltration Biotechnology TP248.13-248.65 Mathematics QA1-939 Han Zhao Yun Chen Peijun Shen Lan Gong Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
description	Background: Uveal melanoma (UM) is the most aggressive intraocular tumor worldwide. Accurate prognostic models are urgently needed. The present research aimed to construct and validate a prognostic signature is associated with overall survival (OS) for UM patients based on metabolism-related genes (MRGs). Methods: MRGs were obtained from molecular signature database (MSigDB). The gene expression profiles and patient clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. In the training datasets, MRGs were analyzed through univariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) Cox analyses to build a prognostic model. The GSE84976 was treated as the validation cohort. In addition, time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival curve analyses the reliability of the developed model. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. Nomogram that combined the five-gene signature was used to evaluate the predictive OS value of UM patients. Results: Five MRGs were identified and used to establish the prognostic model for UM patients. The model was successfully validated using the testing cohort. Moreover, ROC analysis demonstrated a strong predictive ability that our prognostic signature had for UM prognosis. Multivariable Cox regression analysis revealed that the risk model was an independent predictor of prognosis. UM patients with a high-risk score showed a higher level of immune checkpoint molecules. Conclusion: We established a novel metabolism-related signature that could predict survival and might be therapeutic targets for the treatment of UM patients.
format	article
author	Han Zhao Yun Chen Peijun Shen Lan Gong
author_facet	Han Zhao Yun Chen Peijun Shen Lan Gong
author_sort	Han Zhao
title	Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
title_short	Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
title_full	Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
title_fullStr	Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
title_full_unstemmed	Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
title_sort	construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/ff4021cbc2094952bfbe48cac45e7380
work_keys_str_mv	AT hanzhao constructionandvalidationofanovelprognosticsignatureforuvealmelanomabasedonfivemetabolismrelatedgenes AT yunchen constructionandvalidationofanovelprognosticsignatureforuvealmelanomabasedonfivemetabolismrelatedgenes AT peijunshen constructionandvalidationofanovelprognosticsignatureforuvealmelanomabasedonfivemetabolismrelatedgenes AT langong constructionandvalidationofanovelprognosticsignatureforuvealmelanomabasedonfivemetabolismrelatedgenes
_version_	1718417357324419072

Construction and validation of a novel prognostic signature for uveal melanoma based on five metabolism-related genes

Ejemplares similares