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A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database

BACKGROUND: Soft-tissue sarcomas are a group of heterogeneous and rare mesenchymal tumors with aggressive behavior. We aimed to identify the molecular signatures of N(6)-methyladenosine (m(6)A) methylation regulators associated with patient prognosis using The Cancer Genome Atlas (TCGA) database. MA...

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Autores principales: Hou, Mingming, Guo, Xiaohui, Chen, Yu, Cong, Lidan, Pan, Changwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780893/
https://www.ncbi.nlm.nih.gov/pubmed/33370249
http://dx.doi.org/10.12659/MSM.928400
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author Hou, Mingming
Guo, Xiaohui
Chen, Yu
Cong, Lidan
Pan, Changwu
author_facet Hou, Mingming
Guo, Xiaohui
Chen, Yu
Cong, Lidan
Pan, Changwu
author_sort Hou, Mingming
collection PubMed
description BACKGROUND: Soft-tissue sarcomas are a group of heterogeneous and rare mesenchymal tumors with aggressive behavior. We aimed to identify the molecular signatures of N(6)-methyladenosine (m(6)A) methylation regulators associated with patient prognosis using The Cancer Genome Atlas (TCGA) database. MATERIAL/METHODS: To evaluate the role of m(6)A in soft-tissue sarcomas, genomic and clinical data were downloaded from TCGA. The copy number variations (CNVs) and mutations of m(6)A regulators were analyzed. RESULTS: Alterations of m(6)A regulators were common, and ALKBH5 showed the highest frequency of copy number gain, while ZC3H13 had the highest frequency of loss. CNVs and mutations were closely correlated with histology (P<0.001) and tumor size (P=0.040), and CNVs were correlated with mRNA expression. Furthermore, patients with gains of METTL16, RMB15, RMB15B, YTHDC, and YTHDF3 displayed poorer overall survival (OS), and patients with gains of RBM15 and YTHDC2 and loss of IGF2BP1 had poorer disease-free survival (DFS). Further analysis indicated that CNVs and mutations of KIAA1429, YTHDF3, and IGF2BP1 were independent risk factors predicting OS and DFS. Gain of “writers” with loss of “erasers” led to worse OS than gain of “writers”. Genes involved in JAK2 oncogenic signature were enriched in cases of higher expressions of METTL16, YTHDC2, and YTHDF3. Similarly, the core serum response signature was enriched in patients with higher expressions of IGF2BP1, METTL16, RBM15, and YTHDC2. CONCLUSIONS: Our study provides a useful molecular tool to predict the outcome of soft-tissue sarcomas and deepens our understanding of the molecular mechanisms of the development of the disease.
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spelling pubmed-77808932021-01-07 A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database Hou, Mingming Guo, Xiaohui Chen, Yu Cong, Lidan Pan, Changwu Med Sci Monit Database Analysis BACKGROUND: Soft-tissue sarcomas are a group of heterogeneous and rare mesenchymal tumors with aggressive behavior. We aimed to identify the molecular signatures of N(6)-methyladenosine (m(6)A) methylation regulators associated with patient prognosis using The Cancer Genome Atlas (TCGA) database. MATERIAL/METHODS: To evaluate the role of m(6)A in soft-tissue sarcomas, genomic and clinical data were downloaded from TCGA. The copy number variations (CNVs) and mutations of m(6)A regulators were analyzed. RESULTS: Alterations of m(6)A regulators were common, and ALKBH5 showed the highest frequency of copy number gain, while ZC3H13 had the highest frequency of loss. CNVs and mutations were closely correlated with histology (P<0.001) and tumor size (P=0.040), and CNVs were correlated with mRNA expression. Furthermore, patients with gains of METTL16, RMB15, RMB15B, YTHDC, and YTHDF3 displayed poorer overall survival (OS), and patients with gains of RBM15 and YTHDC2 and loss of IGF2BP1 had poorer disease-free survival (DFS). Further analysis indicated that CNVs and mutations of KIAA1429, YTHDF3, and IGF2BP1 were independent risk factors predicting OS and DFS. Gain of “writers” with loss of “erasers” led to worse OS than gain of “writers”. Genes involved in JAK2 oncogenic signature were enriched in cases of higher expressions of METTL16, YTHDC2, and YTHDF3. Similarly, the core serum response signature was enriched in patients with higher expressions of IGF2BP1, METTL16, RBM15, and YTHDC2. CONCLUSIONS: Our study provides a useful molecular tool to predict the outcome of soft-tissue sarcomas and deepens our understanding of the molecular mechanisms of the development of the disease. International Scientific Literature, Inc. 2020-12-28 /pmc/articles/PMC7780893/ /pubmed/33370249 http://dx.doi.org/10.12659/MSM.928400 Text en © Med Sci Monit, 2020 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Database Analysis
Hou, Mingming
Guo, Xiaohui
Chen, Yu
Cong, Lidan
Pan, Changwu
A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title_full A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title_fullStr A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title_full_unstemmed A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title_short A Prognostic Molecular Signature of N(6)-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas Database
title_sort prognostic molecular signature of n(6)-methyladenosine methylation regulators for soft-tissue sarcoma from the cancer genome atlas database
topic Database Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780893/
https://www.ncbi.nlm.nih.gov/pubmed/33370249
http://dx.doi.org/10.12659/MSM.928400
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