Aberrant DNA Methylation Is Associated with Disease Progression, Resistance to Imatinib and Shortened Survival in Chronic Myelogenous Leukemia

The epigenetic impact of DNA methylation in chronic myelogenous leukemia (CML) is not completely understood. To elucidate its role we analyzed 120 patients with CML for methylation of promoter-associated CpG islands of 10 genes. Five genes were identified by DNA methylation screening in the K562 cell line and 3 genes in patients with myeloproliferative neoplasms. The CDKN2B gene was selected for its frequent methylation in myeloid malignancies and ABL1 as the target of BCR-ABL translocation. Thirty patients were imatinib-naïve (mostly treated by interferon-alpha before the imatinib era), 30 were imatinib-responsive, 50 were imatinib-resistant, and 10 were imatinib-intolerant. We quantified DNA methylation by bisulfite pyrosequencing. The average number of methylated genes was 4.5 per patient in the chronic phase, increasing significantly to 6.2 in the accelerated and 6.4 in the blastic phase. Higher numbers of methylated genes were also observed in patients resistant or intolerant to imatinib. These patients also showed almost exclusive methylation of a putative transporter OSCP1. Abnormal methylation of a Src suppressor gene PDLIM4 was associated with shortened survival independently of CML stage and imatinib responsiveness. We conclude that aberrant DNA methylation is associated with CML progression and that DNA methylation could be a marker associated with imatinib resistance. Finally, DNA methylation of PDLIM4 may help identify a subset of CML patients that would benefit from treatment with Src/Abl inhibitors

Quantum Machine Learning: Current State and Challenges

In recent years, machine learning has penetrated a large part of our daily lives, which creates special challenges and impressive progress in this area. Nevertheless, as the amount of daily data is grown, learning time is increased. Quantum machine learning (QML) may speed up the processing of information and provide great promise in machine learning. However, it is not used in practice yet, because quantum software and hardware challenges are still unsurmountable. This paper provides current research of quantum computing and quantum machine learning algorithms. Also, the quantum vendors, their frameworks, and their platforms are presented. A few fully implemented versions of quantum machine learning are presented, which are easier to be evaluated. Finally, QML's challenges, and problems are discussed. © 2021 ACM

Methylation status of RASSF1A in patients with chronic myeloid leukemia

RASSF1A, a key cell cycle related gene, is expressed in all hematopoietic cells, it is implicated in ras signaling pathway and its promoter hypermethylation is observed in a wide variety of solid tumors. Till now, RASSF1A methylation status has not been investigated in patients with chronic myeloid leukemia (CML). In this study, we analyzed 41 patients carrying the BCR-ABL rearrangement, in different stages of the disease. No patient displayed RASSF1A promoter methylation, although the K562 erythroleukemia cell line, bearing the BCR-ABL rearrangement, was found methylated. Thus, our findings indicate that RASSF1A methylation does not appear to represent a critical step in the pathogenesis and/or the progression of CML. (C) 2009 Elsevier Ltd. All rights reserved