AI Article Synopsis

  • Glioma is a prevalent brain tumor with a poor outlook, and recent research highlights the significance of 5-methylcytosine (m5C) RNA modification in its development.
  • The study utilized data from TCGA and CGGA to categorize glioma patients based on survival and clinicopathological characteristics, employing various analytical methods to investigate the link between m5C and the immune environment.
  • Key m5C RNA methylation regulators showed differing expression levels, with certain genes identified as significant prognostic factors for glioma, leading to the development of a predictive m5C-related signature validated in multiple datasets.

Article Abstract

Glioma is a common intracranial tumor and is generally associated with poor prognosis. Recently, numerous studies illustrated the importance of 5-methylcytosine (m5C) RNA modification to tumorigenesis. However, the prognostic value and immune correlation of m5C in glioma remain unclear. We obtained RNA expression and clinical information from The Cancer Genome Atlas (TCGA) and The Chinese Glioma Genome Atlas (CGGA) datasets to analyze. Nonnegative matrix factorization (NMF) was used to classify patients into two subgroups and compare these patients in survival and clinicopathological characteristics. CIBERSORT and single-sample gene-set algorithm (ssGSEA) methods were used to investigate the relationship between m5C and the immune environment. The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to construct a m5C-related signature. Most of m5C RNA methylation regulators presented differential expression and prognostic values. There were obvious relationships between immune infiltration cells and m5C regulators, especially NSUN7. In the m5C-related module from WGCNA, we found SEPT3, CHI3L1, PLBD1, PHYHIPL, SAMD8, RAP1B, B3GNT5, RER1, PTPN7, SLC39A1, and MXI1 were prognostic factors for glioma, and they were used to construct the signature. The great significance of m5C-related signature in predicting the survival of patients with glioma was confirmed in the validation sets and CGGA cohort.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10683591PMC
http://dx.doi.org/10.18632/aging.205179DOI Listing

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