Merkerova MD, Klema J, Kundrat D, Szikszai K, Krejcik Z, Hrustincova A, Trsova I, LE AV, Cermak J, Jonasova A, Belickova M. Noncoding RNAs and Their Response Predictive Value in Azacitidine-treated Patients With Myelodysplastic Syndrome and Acute Myeloid Leukemia With Myelodysplasia-related Changes.
Cancer Genomics Proteomics 2022;
19:205-228. [PMID:
35181589 DOI:
10.21873/cgp.20315]
[Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/07/2022] [Accepted: 01/14/2022] [Indexed: 11/10/2022] Open
Abstract
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.
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