Three-dimensional nuclear telomere architecture and differential expression of aurora kinase genes in chronic myeloid leukemia to measure cell transformation

Abstract

BackgroundTelomere dysfunction results in aneuploidy, and ongoing chromosomal abnormalities. The three-dimensional (3D) nuclear organization of telomeres allows for a distinction between normal and tumor cells. On the other hand, aurora kinase genes (AURKA and AURKB) play an important role regulating the cell cycle. A correlation between overexpression of aurora kinase genes and clinical aggressiveness has been demonstrated in different types of neoplasias. To better understand cellular and molecular mechanisms of CML evolution, it was examined telomere dysfunction (alterations in the 3D nuclear telomere architecture), and the expression levels of AURKA and AURKB genes in two clinical distinct subgroups of CML samples, from the same patient.MethodsEighteen CML patients, in total, 36 bone marrow samples (18 patients, chronic vs. accelerated/blast phase) were eligible for 3D telomeric investigations. Quantitative 3D imaging, cytologic diagnosis and cytogenetic determination of additional chromosomal abnormalities were assessed according to standard protocols.ResultsUsing TeloView software, two CML subgroups were defined based on their 3D telomeric profiles, reflecting the different stages of the disease (chronic vs. accelerated/blast phase). Statistical analyses showed significant differences between the CML subgroups (p < 0.001). We also found that AURKA and AURKB mRNA were expressed at significantly higher levels in both CML subgroups, when compared with healthy donors. Our findings suggest that the evolution of CML progresses from a low to a high level of telomere dysfunction, that is, from an early stage to a more aggressive stage, followed by disease transformation, as demonstrated by telomere, additional chromosomal abnormalities, and gene expression profile dynamics.ConclusionsThus, we demonstrated that 3D telomere organization, in accordance with the genomic instability observed in CML samples were able to distinguish subgroup CML patients. Classifying CML patients based on these characteristics might represent an important strategy to define better therapeutic strategies.