Abstract

BackgroundChronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm whose pathogenesis is linked to the Philadelphia chromosome presence that generates the BCR–ABL1 fusion oncogene. Tyrosine kinase inhibitors (TKI) such as imatinib mesylate (IM) dramatically improved the treatment efficiency and survival of CML patients by targeting BCR–ABL tyrosine kinase. The disease shows three distinct clinical-laboratory stages: chronic phase, accelerated phase and blast crisis. Although patients in the chronic phase respond well to treatment, patients in the accelerated phase or blast crisis usually show therapy resistance and CML relapse. It is crucial, therefore, to identify biomarkers to predict CML genetic evolution and resistance to TKI therapy, considering not only the effects of genetic aberrations but also the role of epigenetic alterations during the disease. Although dysregulations in epigenetic modulators such as histone methyltrasnferases have already been described for some hematologic malignancies, to date very limited data is available for CML, especially when considering the lysine methyltransferase MLL2/KMT2D and MLL3/KMT2C.MethodsHere we investigated the expression profile of both genes in CML patients in different stages of the disease, in patients showing different responses to therapy with IM and in non-neoplastic control samples. Imatinib sensitive and resistant CML cell lines were also used to investigate whether treatment with other tyrosine kinase inhibitors interfered in their expression.ResultsIn patients, both methyltransferases were either upregulated or with basal expression level during the chronic phase compared to controls. Interestingly, MLL3/KMT2C and specially MLL2/KMT2D levels decreased during disease progression correlating with distinct clinical stages. Furthermore, MLL2/KMT2D was decreased in patients resistant to IM treatment. A rescue in the expression of both MLL genes was observed in KCL22S, a CML cell line sensitive to IM, after treatment with dasatinib or nilotinib which was associated with a higher rate of apoptosis, an enhanced expression of p21 (CDKN1A) and a concomitant decrease in the expression of CDK2, CDK4 and Cyclin B1 (CCNB1) in comparison to untreated KCL22S control or IM resistant KCL22R cell line, which suggests involvement of p53 regulated pathway.ConclusionOur results established a new association between MLL2/KMT2D and MLL3/KMT2C genes with CML and suggest that MLL2/KMT2D is associated with disease evolution and may be a potential marker to predict the development of therapy resistance.

Highlights

  • Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm whose pathogenesis is linked to the Philadelphia chromosome presence that generates the BCR–ABL1 fusion oncogene

  • Our results established a new association between MLL2/KMT2D and MLL3/KMT2C genes with CML and suggest that MLL2/KMT2D is associated with disease evolution and may be a potential marker to predict the develop‐ ment of therapy resistance

  • This difference was evident in at least 2 microarray probes used in the Microarray Innovations in Leukemia (MILE) study, in our cohort of 46 patients and 20 healthy donors, we found no significant difference in MLL2/KMT2D expression between the groups

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Summary

Introduction

Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm whose pathogenesis is linked to the Philadelphia chromosome presence that generates the BCR–ABL1 fusion oncogene. Patients in the chronic phase respond well to treatment, patients in the accelerated phase or blast crisis usually show therapy resistance and CML relapse. It is crucial, to identify biomarkers to predict CML genetic evolution and resistance to TKI therapy, considering the effects of genetic aberrations and the role of epigenetic alterations during the disease. Despite all the advances in our understand of CML, with identification of a few mutations associated with disease progression [1] and with different TKIs available for treatment, there is a lack of early and robust markers that can predict genetic evolution and development of therapy resistance

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