Nomogram based on autophagy related genes for predicting the survival in melanoma

Abstract Background Autophagy, a highly conserved lysosomal degradation pathway, is associated with the prognosis of melanoma. However, prognostic prediction models based on autophagy related genes (ARGs) have never been recognized in melanoma. In the present study, we aimed to establish a novel nom...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Guangtong Deng, Wenhua Wang, Yayun Li, Huiyan Sun, Xiang Chen, Furong Zeng
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Autophagy Melanoma Survival Nomogram Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/883b5e7a2f1c4898aa6fac8f3cc1cdbb
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:883b5e7a2f1c4898aa6fac8f3cc1cdbb
record_format	dspace
spelling	oai:doaj.org-article:883b5e7a2f1c4898aa6fac8f3cc1cdbb2021-11-28T12:27:39ZNomogram based on autophagy related genes for predicting the survival in melanoma10.1186/s12885-021-08928-91471-2407https://doaj.org/article/883b5e7a2f1c4898aa6fac8f3cc1cdbb2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12885-021-08928-9https://doaj.org/toc/1471-2407Abstract Background Autophagy, a highly conserved lysosomal degradation pathway, is associated with the prognosis of melanoma. However, prognostic prediction models based on autophagy related genes (ARGs) have never been recognized in melanoma. In the present study, we aimed to establish a novel nomogram to predict the prognosis of melanoma based on ARGs signature and clinical parameters. Methods Data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases were extracted to identify the differentially expressed ARGs. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate analysis were used to select the prognostic ARGs. ARGs signature, age and stage were then enrolled to establish a nomogram to predict the survival probabilities of melanoma. The nomogram was evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram and TNM stage model. The nomogram was validated in GEO cohorts. Results Five prognostic ARGs were selected to construct ARGs signature model and validated in the GEO cohort. Kaplan-Meier survival analysis suggested that patients in high-risk group had significantly worse overall survival than those in low-risk group in TCGA cohort (P = 5.859 × 10–9) and GEO cohort (P = 3.075 × 10–9). We then established and validated a novel promising prognostic nomogram through combining ARGs signature and clinical parameters. The C-index of the nomogram was 0.717 in TCGA training cohort and 0.738 in GEO validation cohort. TCGA/GEO-based ROC curve and decision curve analysis (DCA) demonstrated that the nomogram was better than traditional TNM staging system for melanoma prognosis. Conclusion We firstly developed and validated an ARGs signature based-nomogram for individualized prognosis prediction in melanoma patients, which could assist with decision making for clinicians.Guangtong DengWenhua WangYayun LiHuiyan SunXiang ChenFurong ZengBMCarticleAutophagyMelanomaSurvivalNomogramNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENBMC Cancer, Vol 21, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Autophagy Melanoma Survival Nomogram Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Autophagy Melanoma Survival Nomogram Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Guangtong Deng Wenhua Wang Yayun Li Huiyan Sun Xiang Chen Furong Zeng Nomogram based on autophagy related genes for predicting the survival in melanoma
description	Abstract Background Autophagy, a highly conserved lysosomal degradation pathway, is associated with the prognosis of melanoma. However, prognostic prediction models based on autophagy related genes (ARGs) have never been recognized in melanoma. In the present study, we aimed to establish a novel nomogram to predict the prognosis of melanoma based on ARGs signature and clinical parameters. Methods Data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases were extracted to identify the differentially expressed ARGs. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate analysis were used to select the prognostic ARGs. ARGs signature, age and stage were then enrolled to establish a nomogram to predict the survival probabilities of melanoma. The nomogram was evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram and TNM stage model. The nomogram was validated in GEO cohorts. Results Five prognostic ARGs were selected to construct ARGs signature model and validated in the GEO cohort. Kaplan-Meier survival analysis suggested that patients in high-risk group had significantly worse overall survival than those in low-risk group in TCGA cohort (P = 5.859 × 10–9) and GEO cohort (P = 3.075 × 10–9). We then established and validated a novel promising prognostic nomogram through combining ARGs signature and clinical parameters. The C-index of the nomogram was 0.717 in TCGA training cohort and 0.738 in GEO validation cohort. TCGA/GEO-based ROC curve and decision curve analysis (DCA) demonstrated that the nomogram was better than traditional TNM staging system for melanoma prognosis. Conclusion We firstly developed and validated an ARGs signature based-nomogram for individualized prognosis prediction in melanoma patients, which could assist with decision making for clinicians.
format	article
author	Guangtong Deng Wenhua Wang Yayun Li Huiyan Sun Xiang Chen Furong Zeng
author_facet	Guangtong Deng Wenhua Wang Yayun Li Huiyan Sun Xiang Chen Furong Zeng
author_sort	Guangtong Deng
title	Nomogram based on autophagy related genes for predicting the survival in melanoma
title_short	Nomogram based on autophagy related genes for predicting the survival in melanoma
title_full	Nomogram based on autophagy related genes for predicting the survival in melanoma
title_fullStr	Nomogram based on autophagy related genes for predicting the survival in melanoma
title_full_unstemmed	Nomogram based on autophagy related genes for predicting the survival in melanoma
title_sort	nomogram based on autophagy related genes for predicting the survival in melanoma
publisher	BMC
publishDate	2021
url	https://doaj.org/article/883b5e7a2f1c4898aa6fac8f3cc1cdbb
work_keys_str_mv	AT guangtongdeng nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma AT wenhuawang nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma AT yayunli nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma AT huiyansun nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma AT xiangchen nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma AT furongzeng nomogrambasedonautophagyrelatedgenesforpredictingthesurvivalinmelanoma
_version_	1718407967902007296

Nomogram based on autophagy related genes for predicting the survival in melanoma

Ejemplares similares