Michaela Dostalova Merkerova1, Jiri Klema2, David Kundrat3, Katarina Szikszai3, Zdenek Krejcik3, Andrea Hrustincova3, Iva Trsova3, Anh Vu LE2, Jaroslav Cermak4, Anna Jonasova5, Monika Belickova3. 1. Department of Genomics, Institute of Hematology and Blood Transfusion, Prague, Czech Republic; michaela.merkerova@uhkt.cz. 2. Department of Computer Sciences, Czech Technical University, Prague, Czech Republic. 3. Department of Genomics, Institute of Hematology and Blood Transfusion, Prague, Czech Republic. 4. Laboratory of Anemias, Institute of Hematology and Blood Transfusion, Prague, Czech Republic. 5. First Department of Medicine, General University Hospital, Prague, Czech Republic.
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.
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.
Authors: Sofie Singbrant; Meaghan Wall; Jennifer Moody; Göran Karlsson; Alistair M Chalk; Brian Liddicoat; Megan R Russell; Carl R Walkley; Stefan Karlsson Journal: Haematologica Date: 2014-01-10 Impact factor: 9.941
Authors: Lewis R Silverman; Erin P Demakos; Bercedis L Peterson; Alice B Kornblith; Jimmie C Holland; Rosalie Odchimar-Reissig; Richard M Stone; Douglas Nelson; Bayard L Powell; Carlos M DeCastro; John Ellerton; Richard A Larson; Charles A Schiffer; James F Holland Journal: J Clin Oncol Date: 2002-05-15 Impact factor: 44.544
Authors: Guillaume Bourque; Kathleen H Burns; Mary Gehring; Vera Gorbunova; Andrei Seluanov; Molly Hammell; Michaël Imbeault; Zsuzsanna Izsvák; Henry L Levin; Todd S Macfarlan; Dixie L Mager; Cédric Feschotte Journal: Genome Biol Date: 2018-11-19 Impact factor: 13.583