Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases
Objective To construct a prognostic model for neuroblastoma (NB) based on cuproptosis-related genes (CRGs) and improve individualized management of neuroblastoma patients. Methods CRGs expression data with complete clinical information were collected from publicly available databases. A total of 3...
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Editorial Office of Journal of Army Medical University
2023-02-01
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| Series: | 陆军军医大学学报 |
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| Online Access: | http://aammt.tmmu.edu.cn/Upload/rhtml/202207150.htm |
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| author | XIANG Bin CHEN Meiling CAO Lijian HE Xueyu TIAN Xiaomao |
| author_facet | XIANG Bin CHEN Meiling CAO Lijian HE Xueyu TIAN Xiaomao |
| author_sort | XIANG Bin |
| collection | DOAJ |
| description | Objective To construct a prognostic model for neuroblastoma (NB) based on cuproptosis-related genes (CRGs) and improve individualized management of neuroblastoma patients. Methods CRGs expression data with complete clinical information were collected from publicly available databases. A total of 3 independent datasets were obtained, including the GSE49711 cohort from Gene Expression Omnibus (GEO) database, the TARGET-NB cohort from Therapeutically Applicable Research to Generate Effective Treatments(TARGET) database, and the E-MTAB-8248 cohort from ArrayExpress database. 968 patients were finally included for follow-up data analysis after excluding patients with incomplete follow-up information. The GSE49711 cohort was selected as the training set to construct the prognositic model, and the other two data sets were used as the validation set to verify the accuracy. Log-rank tests were used to screen prognostically significant variables, and the best multi-gene prognostic model was contructed using LASSO-Cox regression. ROC curves, column plots, calibration curves, and DCA curves were used to assess the accuracy of the prognostic models. RT-qPCR was used to validate the expression levels of risk genes in NB cell lines, and the key risk gene PDHA1 was selected for functional analysis. Results A prognostic model was first constructed in the training cohort with a risk score formula of (1.573)×PDHA1+(-0.561)×GLS+(0.320)×LIAS+(0.088)×MTF1+(0.301)×PDHB. According to the risk scores calculated based on the formula, patients were classified into the high- and low-risk subgroups based on the median values. Survival analysis showed that NB patients in the high-risk subgroup had a significantly lower survival rate than that in the low-risk subgroup (P < 0.001). The time-dependent ROC curve predicted the area under curve (AUC) of 3-year, 5-year and 7-year survival rate was 0.80, 0.80, and 0.81, respectively. Survival analysis showed that in the TARGET-NB and E-MTAB-8248 cohorts, the high-risk subgroup was associated with a worse prognosis compared with the low-risk subgroup(P=0.011, P=0.008 7). The calibration curve and DCA curve (C-index: 0.736) of nomagram showed the good clinical value of nomagram. The expression levels of genes in the risk model and the function of the key gene PDHA1 were verified by RT-qPCR and loss-of-function experiments. Conclusion A prognostic model to predict the survival rate of patients with neuroblastoma is constructed based on cuproptosis-related genes and validated in two external datasets.
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| first_indexed | 2024-04-10T07:04:02Z |
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| series | 陆军军医大学学报 |
| spelling | doaj.art-96ea601b25464679a9dcf68f1790e74b2023-02-27T10:49:14ZzhoEditorial Office of Journal of Army Medical University陆军军医大学学报2097-09272023-02-0145430730710.16016/j.2097-0927.202207150Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databasesXIANG Bin0CHEN Meiling1CAO Lijian2HE Xueyu3TIAN Xiaomao4Department of Urology, Key Laboratory of Child Development and Disorders of Ministry of Education, National Clinical Research Center for Child Health and Disorders, Chirdren's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Urology, Key Laboratory of Child Development and Disorders of Ministry of Education, National Clinical Research Center for Child Health and Disorders, Chirdren's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Urology, Key Laboratory of Child Development and Disorders of Ministry of Education, National Clinical Research Center for Child Health and Disorders, Chirdren's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Urology, Key Laboratory of Child Development and Disorders of Ministry of Education, National Clinical Research Center for Child Health and Disorders, Chirdren's Hospital of Chongqing Medical University, Chongqing, 400014, ChinaDepartment of Urology, Key Laboratory of Child Development and Disorders of Ministry of Education, National Clinical Research Center for Child Health and Disorders, Chirdren's Hospital of Chongqing Medical University, Chongqing, 400014, China Objective To construct a prognostic model for neuroblastoma (NB) based on cuproptosis-related genes (CRGs) and improve individualized management of neuroblastoma patients. Methods CRGs expression data with complete clinical information were collected from publicly available databases. A total of 3 independent datasets were obtained, including the GSE49711 cohort from Gene Expression Omnibus (GEO) database, the TARGET-NB cohort from Therapeutically Applicable Research to Generate Effective Treatments(TARGET) database, and the E-MTAB-8248 cohort from ArrayExpress database. 968 patients were finally included for follow-up data analysis after excluding patients with incomplete follow-up information. The GSE49711 cohort was selected as the training set to construct the prognositic model, and the other two data sets were used as the validation set to verify the accuracy. Log-rank tests were used to screen prognostically significant variables, and the best multi-gene prognostic model was contructed using LASSO-Cox regression. ROC curves, column plots, calibration curves, and DCA curves were used to assess the accuracy of the prognostic models. RT-qPCR was used to validate the expression levels of risk genes in NB cell lines, and the key risk gene PDHA1 was selected for functional analysis. Results A prognostic model was first constructed in the training cohort with a risk score formula of (1.573)×PDHA1+(-0.561)×GLS+(0.320)×LIAS+(0.088)×MTF1+(0.301)×PDHB. According to the risk scores calculated based on the formula, patients were classified into the high- and low-risk subgroups based on the median values. Survival analysis showed that NB patients in the high-risk subgroup had a significantly lower survival rate than that in the low-risk subgroup (P < 0.001). The time-dependent ROC curve predicted the area under curve (AUC) of 3-year, 5-year and 7-year survival rate was 0.80, 0.80, and 0.81, respectively. Survival analysis showed that in the TARGET-NB and E-MTAB-8248 cohorts, the high-risk subgroup was associated with a worse prognosis compared with the low-risk subgroup(P=0.011, P=0.008 7). The calibration curve and DCA curve (C-index: 0.736) of nomagram showed the good clinical value of nomagram. The expression levels of genes in the risk model and the function of the key gene PDHA1 were verified by RT-qPCR and loss-of-function experiments. Conclusion A prognostic model to predict the survival rate of patients with neuroblastoma is constructed based on cuproptosis-related genes and validated in two external datasets. http://aammt.tmmu.edu.cn/Upload/rhtml/202207150.htmneuroblastomacuproptosisprognostic modelnomogram |
| spellingShingle | XIANG Bin CHEN Meiling CAO Lijian HE Xueyu TIAN Xiaomao Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases 陆军军医大学学报 neuroblastoma cuproptosis prognostic model nomogram |
| title | Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases |
| title_full | Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases |
| title_fullStr | Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases |
| title_full_unstemmed | Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases |
| title_short | Construction and validation of acuproptosis-related prognostic model in neuroblastoma based on TARGET, ArrayExpress and GEO databases |
| title_sort | construction and validation of acuproptosis related prognostic model in neuroblastoma based on target arrayexpress and geo databases |
| topic | neuroblastoma cuproptosis prognostic model nomogram |
| url | http://aammt.tmmu.edu.cn/Upload/rhtml/202207150.htm |
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