28 December 2020 : Database Analysis
A Prognostic Molecular Signature of N⁶-Methyladenosine Methylation Regulators for Soft-Tissue Sarcoma from The Cancer Genome Atlas DatabaseMingming Hou1AE*, Xiaohui Guo2BE, Yu Chen1CEF, Lidan Cong3DE, Changwu Pan1CE
Med Sci Monit 2020; 26:e928400
BACKGROUND: Soft-tissue sarcomas are a group of heterogeneous and rare mesenchymal tumors with aggressive behavior. We aimed to identify the molecular signatures of N⁶-methyladenosine (m6A) methylation regulators associated with patient prognosis using The Cancer Genome Atlas (TCGA) database.
MATERIAL AND METHODS: To evaluate the role of m⁶A in soft-tissue sarcomas, genomic and clinical data were downloaded from TCGA. The copy number variations (CNVs) and mutations of m6A regulators were analyzed.
RESULTS: Alterations of m⁶A 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.
Keywords: DNA Copy Number Variations, Methylation, Mutation, Prognosis, Sarcoma, Adenosine, DNA Methylation, Databases, Genetic, Disease-Free Survival, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genome, Human, Middle Aged, Multivariate Analysis, Proportional Hazards Models, RNA, Messenger
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