RNA 5-Methylcytosine Regulators Contribute to Metabolism Heterogeneity and Predict Prognosis in Ovarian Cancer

Abstract

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5-Methylcytosine (m5C) is an abundant and highly conserved modification in RNAs. The dysregulation of RNA m5C methylation has been reported in cancers, but the regulatory network in ovarian cancer of RNA m5C methylation-related genes and its implication in metabolic regulation remain largely unexplored. In this study, RNA-sequencing data and clinical information of 374 ovarian cancer patients were downloaded from The Cancer Genome Atlas database, and a total of 14 RNA m5C regulators were included. Through unsupervised consensus clustering, two clusters with different m5C modification patterns were identified with distinct survivals. According to enrichment analyses, glycosaminoglycan and collagen metabolism–related pathways were specifically activated in cluster 1, whereas fatty acid metabolism–related pathways were enriched in cluster 2, which had better overall survival (OS). Besides the metabolism heterogeneity, the higher sensitivity to platinum and paclitaxel in cluster 2 can further explain the improved OS. Ultimately, a least absolute shrinkage and selection operator prediction model formed by ALYREF, NOP2, and TET2 toward OS was constructed. In conclusion, distinct m5C modification pattern exhibited metabolism heterogeneity, different chemotherapy sensitivity, and consequently survival difference, providing evidence for risk stratification.

Keywords

• ovarian cancer
• 5-methylcytosine
• RNA modification
• metabolism heterogeneity
• LASSO cox regression