BACKGROUND/AIM: Prediction of response to azacitidine (AZA) treatment is an important challenge in hematooncology. In addition to protein coding genes (PCGs), AZA efficiency is influenced by various noncoding RNAs (ncRNAs), including long ncRNAs (lncRNAs), circular RNAs (circRNAs), and transposable elements (TEs). MATERIALS AND METHODS: RNA sequencing was performed in patients with myelodysplastic syndromes or acute myeloid leukemia before AZA treatment to assess contribution of ncRNAs to AZA mechanisms and propose novel disease prediction biomarkers. RESULTS: Our analyses showed that lncRNAs had the strongest predictive potential. The combined set of the best predictors included 14 lncRNAs, and only four PCGs, one circRNA, and no TEs. Epigenetic regulation and recombinational repair were suggested as crucial for AZA response, and network modeling defined three deregulated lncRNAs (CTC-482H14.5, RP11-419K12.2, and RP11-736I24.4) associated with these processes. CONCLUSION: The expression of various ncRNAs can influence the effect of AZA and new ncRNA-based predictive biomarkers can be defined.
- Keywords
- Noncoding RNAs, acute myeloid leukemia, azacytidine, circular RNAs, myelodysplastic syndrome, transposable elements,
- MeSH
- Leukemia, Myeloid, Acute * drug therapy genetics MeSH
- Azacitidine pharmacology therapeutic use MeSH
- Epigenesis, Genetic MeSH
- Humans MeSH
- Myelodysplastic Syndromes * drug therapy genetics MeSH
- RNA, Long Noncoding * genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Azacitidine MeSH
- RNA, Long Noncoding * MeSH
