Recurrent Translocations in Topoisomerase Inhibitor-Related Leukemia Are Determined by the Features of DNA Breaks Rather Than by the Proximity of the Translocating Genes.
Nikolai A LomovVladimir S ViushkovSergey V UlianovAlexey A GavrilovDaniil A AlexeyevskyArtem V ArtemovSergey V RazinMikhail A RubtsovPublished in: International journal of molecular sciences (2022)
Topoisomerase inhibitors are widely used in cancer chemotherapy. However, one of the potential long-term adverse effects of such therapy is acute leukemia. A key feature of such therapy-induced acute myeloid leukemia (t-AML) is recurrent chromosomal translocations involving AML1 (RUNX1) or MLL (KMT2A) genes. The formation of chromosomal translocation depends on the spatial proximity of translocation partners and the mobility of the DNA ends. It is unclear which of these two factors might be decisive for recurrent t-AML translocations. Here, we used fluorescence in situ hybridization (FISH) and chromosome conformation capture followed by sequencing (4C-seq) to investigate double-strand DNA break formation and the mobility of broken ends upon etoposide treatment, as well as contacts between translocation partner genes. We detected the separation of the parts of the broken AML1 gene, as well as the increased mobility of these separated parts. 4C-seq analysis showed no evident contacts of AML1 and MLL with loci, implicated in recurrent t-AML translocations, either before or after etoposide treatment. We suggest that separation of the break ends and their increased non-targeted mobility-but not spatial predisposition of the rearrangement partners-plays a major role in the formation of these translocations.
Keyphrases
- acute myeloid leukemia
- genome wide
- copy number
- allogeneic hematopoietic stem cell transplantation
- single molecule
- dna methylation
- circulating tumor
- single cell
- hiv testing
- machine learning
- squamous cell carcinoma
- transcription factor
- bioinformatics analysis
- diabetic rats
- oxidative stress
- radiation therapy
- risk assessment
- bone marrow
- acute lymphoblastic leukemia
- hiv infected
- genome wide analysis
- drug delivery
- hepatitis c virus
- deep learning
- gene expression
- mesenchymal stem cells
- small molecule
- squamous cell
- human immunodeficiency virus
- molecular dynamics simulations
- genome wide association study
- quantum dots