Alexander V Lavrov1,2, Ekaterina Yu Chelysheva3, Elmira P Adilgereeva4, Oleg A Shukhov3, Svetlana A Smirnikhina4, Konstantin S Kochergin-Nikitsky4, Valentina D Yakushina4, Grigory A Tsaur5,6,7, Sergey V Mordanov8, Anna G Turkina3, Sergey I Kutsev4,9. 1. Laboratory of Mutagenesis, Federal State Budgetary Institution, Research Centre for Medical Genetics, Moskvorechie str., 1, Moscow, Russian Federation, 115522. alexandervlavrov@gmail.com. 2. Department of Molecular and Cellular Genetics, State Budgetary Educational Institution of Higher Professional Education "Russian National Research Medical University named after N.I. Pirogov" of Ministry of Health of the Russian Federation, Ostrovityanova str., 1, Moscow, Russian Federation, 117997. alexandervlavrov@gmail.com. 3. Scientific and Advisory Department of Chemotherapy of Myeloproliferative disorders, Federal State-Funded Institution National Research Center for Hematology of the Ministry of Healthcare of the Russian Federation, Novy Zykovki proezd, 4, Moscow, Russian Federation, 125167. 4. Laboratory of Mutagenesis, Federal State Budgetary Institution, Research Centre for Medical Genetics, Moskvorechie str., 1, Moscow, Russian Federation, 115522. 5. Regional Children Hospital 1, S. Deryabinoy str., 32, Ekaterinburg, Russian Federation, 620149. 6. Research Institute of Medical Cell Technologies, Soboleva str., 25, Ekaterinburg, Russian Federation, 620905. 7. Federal State Budgetary Educational Institution of Higher Education, Urals State Medical University of the Ministry of Healthcare of the Russian Federation, Repina str., 3, Ekaterinburg, Russian Federation, 620028. 8. Laboratory of Medical Genetics, The Rostov State Medical University, Nahichevansky av., 29, Rostov-on-Don, Russian Federation, 344022. 9. Department of Molecular and Cellular Genetics, State Budgetary Educational Institution of Higher Professional Education "Russian National Research Medical University named after N.I. Pirogov" of Ministry of Health of the Russian Federation, Ostrovityanova str., 1, Moscow, Russian Federation, 117997.
Abstract
BACKGROUND: Approximately 5-20% of chronic myeloid leukemia (CML) patients demonstrate primary resistance or intolerance to imatinib. None of the existing predictive scores gives a good prognosis of TKI efficacy. Gene polymorphisms, expression and microRNAs are known to be involved in the pathogenesis of TKI resistance in CML. The aim of our study is to find new molecular markers of TKI therapy efficacy in CML patients. METHODS: Newly diagnosed patients with Ph+ CML in chronic phase were included in this study. Optimal and non-optimal responses to TKI were estimated according to ELN 2013 recommendation. We performed genotyping of selected polymorphisms in 62 blood samples of CML patients, expression profiling of 33 RNA samples extracted from blood and miRNA profiling of 800 miRNA in 12 blood samples of CML patients. RESULTS: The frequencies of genotypes at the studied loci did not differ between groups of patients with an optimal and non-optimal response to TKI therapy. Analysis of the expression of 34,681 genes revealed 26 differently expressed genes (p < 0.05) in groups of patients with different TKI responses, but differences were very small and were not confirmed by qPCR. Finally, we did not find difference in miRNA expression between the groups. CONCLUSIONS: Using modern high-throughput methods such as whole-exome sequencing, transcriptome and miRNA analysis, we could not find reliable molecular markers for early prediction of TKI efficiency in Ph+ CML patients.
BACKGROUND: Approximately 5-20% of chronic myeloid leukemia (CML) patients demonstrate primary resistance or intolerance to imatinib. None of the existing predictive scores gives a good prognosis of TKI efficacy. Gene polymorphisms, expression and microRNAs are known to be involved in the pathogenesis of TKI resistance in CML. The aim of our study is to find new molecular markers of TKI therapy efficacy in CMLpatients. METHODS: Newly diagnosed patients with Ph+ CML in chronic phase were included in this study. Optimal and non-optimal responses to TKI were estimated according to ELN 2013 recommendation. We performed genotyping of selected polymorphisms in 62 blood samples of CMLpatients, expression profiling of 33 RNA samples extracted from blood and miRNA profiling of 800 miRNA in 12 blood samples of CMLpatients. RESULTS: The frequencies of genotypes at the studied loci did not differ between groups of patients with an optimal and non-optimal response to TKI therapy. Analysis of the expression of 34,681 genes revealed 26 differently expressed genes (p < 0.05) in groups of patients with different TKI responses, but differences were very small and were not confirmed by qPCR. Finally, we did not find difference in miRNA expression between the groups. CONCLUSIONS: Using modern high-throughput methods such as whole-exome sequencing, transcriptome and miRNA analysis, we could not find reliable molecular markers for early prediction of TKI efficiency in Ph+ CMLpatients.
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