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Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma

BACKGROUND: Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignan...

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Autores principales: Yan, Zijun, Liu, Qiming, Cao, Ziyang, Wang, Jinxia, Zhang, Hongyang, Liu, Jiangbin, Zou, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687102/
https://www.ncbi.nlm.nih.gov/pubmed/36439943
http://dx.doi.org/10.3389/fninf.2022.1034793
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author Yan, Zijun
Liu, Qiming
Cao, Ziyang
Wang, Jinxia
Zhang, Hongyang
Liu, Jiangbin
Zou, Lin
author_facet Yan, Zijun
Liu, Qiming
Cao, Ziyang
Wang, Jinxia
Zhang, Hongyang
Liu, Jiangbin
Zou, Lin
author_sort Yan, Zijun
collection PubMed
description BACKGROUND: Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients. METHODS: Multi-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated. RESULTS: We constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment. CONCLUSION: This study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients.
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spelling pubmed-96871022022-11-25 Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma Yan, Zijun Liu, Qiming Cao, Ziyang Wang, Jinxia Zhang, Hongyang Liu, Jiangbin Zou, Lin Front Neuroinform Neuroscience BACKGROUND: Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients. METHODS: Multi-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated. RESULTS: We constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment. CONCLUSION: This study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients. Frontiers Media S.A. 2022-11-10 /pmc/articles/PMC9687102/ /pubmed/36439943 http://dx.doi.org/10.3389/fninf.2022.1034793 Text en Copyright © 2022 Yan, Liu, Cao, Wang, Zhang, Liu and Zou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Yan, Zijun
Liu, Qiming
Cao, Ziyang
Wang, Jinxia
Zhang, Hongyang
Liu, Jiangbin
Zou, Lin
Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title_full Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title_fullStr Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title_full_unstemmed Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title_short Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
title_sort multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687102/
https://www.ncbi.nlm.nih.gov/pubmed/36439943
http://dx.doi.org/10.3389/fninf.2022.1034793
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