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Noncoding RNAs and Their Response Predictive Value in Azacitidine-treated Patients With Myelodysplastic Syndrome and Acute Myeloid Leukemia With Myelodysplasia-related Changes

MD. Merkerova, J. Klema, D. Kundrat, K. Szikszai, Z. Krejcik, A. Hrustincova, I. Trsova, AV. LE, J. Cermak, A. Jonasova, M. Belickova

. 2022 ; 19 (2) : 205-228. [pub] -

Language English Country Greece

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc22010823

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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$a Klema, Jiri $u Department of Computer Sciences, Czech Technical University, Prague, Czech Republic
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$a Kundrat, David $u Department of Genomics, Institute of Hematology and Blood Transfusion, Prague, Czech Republic
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$a LE, Anh Vu $u Department of Computer Sciences, Czech Technical University, Prague, Czech Republic
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$a Jonasova, Anna $u First Department of Medicine, General University Hospital, Prague, Czech Republic
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