Abstract
Ph+ chronic myeloid leukemia (CML) is a stem cell malignancy characterized by the BCR-ABL1 oncoprotein and leukemic expansion of myeloid progenitor cells. In the chronic phase (CP) of CML, clonal cells undergo myeloid differentiation and respond well to BCR-ABL1 inhibitors. In the accelerated phase (AP) and blast phase (BP) of CML, however, neoplastic cells are immature and often resistant against most BCR-ABL1-targeting drugs which is a challenge in clinical hematology. So far, little is known about molecular mechanisms underlying disease progression in CML. Methylation of CG sites around the transcriptional start site of various cancer-related genes including diverse tumor suppressor genes (referred to as methylation) is a frequently occurring epigenetic feature in neoplastic cells resulting in silencing of these genes. Although methylation is considered a critical factor in the pathogenesis of various malignant diseases including myeloid neoplasms, no comprehensive studies on the impact of methylation in the pathogenesis of CML have been conducted so far. We hypothesized that methylation may be an important mechanism regulating the transcriptional gene activity in CML cells during disease progression. Therefore, we investigated the methylome and the transcriptome of neoplastic cells in patients with CML in various phases of the disease (CP, n=15; AP, n=5; BP, n=7). Genome-wide methylation and gene expression patterns were analysed by next generation sequencing approaches using bone marrow (BM) or peripheral blood (PB) mononuclear cells (MNC) obtained from patients with CML and BM or PB MNC from control individuals. Methylation was analysed by reduced representation bisulfite sequencing (RRBS), and mRNA expression was determined by RNA-sequencing (RNA-seq). By comparing the methylome of patients who were initially diagnosed with CP-CML and who relapsed several months later (AP-CML, n=1; BC-CML, n=3), we identified a large number of genes which were methylated around their transcriptional start site in leukemic cells in patients at the time of progression compared to the time of CP-CML (range in the 4 patients: 423-1209 genes, adjusted p<0.05). These methylated genes were found to be less methylated or not methylated in BM or PB MNC of control individuals. When the methylome of all patients in all cohorts was examined and compared, more genes were found to be methylated in AP-CML and BC-CML compared to CP-CML (CP-CML, n=200; AP-CML, n=311; BC-CML, n=570). In addition, we identified several genes that were less methylated or not methylated in AP-CML and BC-CML cells compared to cells in CP-CML samples (range: 16-541 genes). Moreover, we analysed and compared the transcriptome of CP-CML, AP-CML and BC-CML samples and identified a large number of genes whose expression is downregulated in AP-CML and BC-CML samples compared to CP-CML (range: 187-382 genes). By correlating RRBS results and RNA-seq data, we found that expression of >100 of the methylated genes is downregulated in AP-CML/BC-CML compared to CP-CML suggesting that these genes may be regulated by methylation. Expression of the majority of these genes was detected in BM or PB MNC of control individuals. In silico pathway analyses and gene network analyses revealed that some methylated genes are involved in the regulation of apoptosis (e.g. CYP1B1, ZBTB16), negative regulation of cell proliferation (e.g. BTG3, VSX2) or regulation of Wnt signalling (e.g. SFRP1). Currently, a large number of CML patients are analysed gene-specifically for methylation by methylation-sensitive high resolution melting PCR and for expression of selected genes by RT-PCR in order to define prognostic patterns in CML. In summary, our results demonstrate that methylation changes are frequent events accompanying disease progression in patients with CML. These results may contribute to the identification of clinically relevant methylation patterns in CML and thus may improve prognostication. In addition, our data may reveal new epigenetic targets of therapy and may help to develop new treatment strategies for high risk or relapsing patients with CML.
Disclosures
Valent: Novartis: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; BMS: Honoraria.
Megakaryocytes differentially sort mRNAs for matrix metalloproteinases and their inhibitors into platelets: a mechanism for regulating synthetic events
