Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma
High-grade neuroblastoma (HG-NB) exhibits a significantly diminished survival rate in comparison to low-grade neuroblastoma (LG-NB), primarily attributed to the mechanism of HG-NB is unclear and the lacking effective therapeutic targets and diagnostic model. Therefore, the current investigation aims...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1345734/full |
| _version_ | 1797366585660276736 |
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| author | Wancun Zhang Wancun Zhang Wancun Zhang Mengxin Zhang Meng Sun Minghui Hu Muchun Yu Jushan Sun Xianwei Zhang Bang Du Bang Du Bang Du |
| author_facet | Wancun Zhang Wancun Zhang Wancun Zhang Mengxin Zhang Meng Sun Minghui Hu Muchun Yu Jushan Sun Xianwei Zhang Bang Du Bang Du Bang Du |
| author_sort | Wancun Zhang |
| collection | DOAJ |
| description | High-grade neuroblastoma (HG-NB) exhibits a significantly diminished survival rate in comparison to low-grade neuroblastoma (LG-NB), primarily attributed to the mechanism of HG-NB is unclear and the lacking effective therapeutic targets and diagnostic model. Therefore, the current investigation aims to study the dysregulated network between HG-NB and LG-NB based on transcriptomics and metabolomics joint analysis. Meanwhile, a risk diagnostic model to distinguish HG-NB and LG-NB was also developed. Metabolomics analysis was conducted using plasma samples obtained from 48 HG-NB patients and 36 LG-NB patients. A total of 39 metabolites exhibited alterations, with 20 showing an increase and 19 displaying a decrease in HG-NB. Additionally, transcriptomics analysis was performed on NB tissue samples collected from 31 HG-NB patients and 20 LG-NB patients. Results showed that a significant alteration was observed in a total of 1,199 mRNAs in HG-NB, among which 893 were upregulated while the remaining 306 were downregulated. In particular, the joint analysis of both omics data revealed three aberrant pathways, namely the cAMP signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway, which were found to be associated with cell death. Notably, a diagnostic model for HG-NB risk classification was developed based on the genes MGST1, SERPINE1, and ERBB3 with an area under the receiver operating characteristic curve of 0.915. In the validation set, the sensitivity and specificity were determined to be 75.0% and 80.0%, respectively. |
| first_indexed | 2024-03-08T17:05:53Z |
| format | Article |
| id | doaj.art-5e9766265dc24069b9cb25dbd8219a42 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-03-08T17:05:53Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-5e9766265dc24069b9cb25dbd8219a422024-01-04T04:56:41ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-01-011410.3389/fimmu.2023.13457341345734Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastomaWancun Zhang0Wancun Zhang1Wancun Zhang2Mengxin Zhang3Meng Sun4Minghui Hu5Muchun Yu6Jushan Sun7Xianwei Zhang8Bang Du9Bang Du10Bang Du11Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan International Joint Laboratory for Prevention and Treatment of Pediatric Disease, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHenan Key Laboratory of Children’s Genetics and Metabolic Diseases, Children’s Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaHigh-grade neuroblastoma (HG-NB) exhibits a significantly diminished survival rate in comparison to low-grade neuroblastoma (LG-NB), primarily attributed to the mechanism of HG-NB is unclear and the lacking effective therapeutic targets and diagnostic model. Therefore, the current investigation aims to study the dysregulated network between HG-NB and LG-NB based on transcriptomics and metabolomics joint analysis. Meanwhile, a risk diagnostic model to distinguish HG-NB and LG-NB was also developed. Metabolomics analysis was conducted using plasma samples obtained from 48 HG-NB patients and 36 LG-NB patients. A total of 39 metabolites exhibited alterations, with 20 showing an increase and 19 displaying a decrease in HG-NB. Additionally, transcriptomics analysis was performed on NB tissue samples collected from 31 HG-NB patients and 20 LG-NB patients. Results showed that a significant alteration was observed in a total of 1,199 mRNAs in HG-NB, among which 893 were upregulated while the remaining 306 were downregulated. In particular, the joint analysis of both omics data revealed three aberrant pathways, namely the cAMP signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway, which were found to be associated with cell death. Notably, a diagnostic model for HG-NB risk classification was developed based on the genes MGST1, SERPINE1, and ERBB3 with an area under the receiver operating characteristic curve of 0.915. In the validation set, the sensitivity and specificity were determined to be 75.0% and 80.0%, respectively.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1345734/fullneuroblastomametabolomicstranscriptomics; therapeutic targetnetworkdiagnostic model |
| spellingShingle | Wancun Zhang Wancun Zhang Wancun Zhang Mengxin Zhang Meng Sun Minghui Hu Muchun Yu Jushan Sun Xianwei Zhang Bang Du Bang Du Bang Du Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma Frontiers in Immunology neuroblastoma metabolomics transcriptomics; therapeutic target network diagnostic model |
| title | Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma |
| title_full | Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma |
| title_fullStr | Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma |
| title_full_unstemmed | Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma |
| title_short | Metabolomics-transcriptomics joint analysis: unveiling the dysregulated cell death network and developing a diagnostic model for high-grade neuroblastoma |
| title_sort | metabolomics transcriptomics joint analysis unveiling the dysregulated cell death network and developing a diagnostic model for high grade neuroblastoma |
| topic | neuroblastoma metabolomics transcriptomics; therapeutic target network diagnostic model |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1345734/full |
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