Investigation of measurable residual disease in acute myeloid leukemia by DNA methylation patterns.

Assessment of measurable residual disease (MRD) upon treatment of acute myeloid leukemia (AML) remains challenging. It is usually addressed by highly sensitive PCR- or sequencing-based screening of specific mutations, or by multiparametric flow cytometry. However, not all patients have suitable mutations and heterogeneity of surface markers hampers standardization in clinical routine. In this study, we propose an alternative approach to estimate MRD based on AML-associated DNA methylation (DNAm) patterns. We identified four CG dinucleotides (CpGs) that commonly reveal aberrant DNAm in AML and their combination could reliably discern healthy and AML samples. Interestingly, bisulfite amplicon sequencing demonstrated that aberrant DNAm patterns were symmetric on both alleles, indicating that there is epigenetic crosstalk between homologous chromosomes. We trained shallow-learning and deep-learning algorithms to identify anomalous DNAm patterns. The method was then tested on follow-up samples with and without MRD. Notably, even samples that were classified as MRD negative often revealed higher anomaly ratios than healthy controls, which may reflect clonal hematopoiesis. Our results demonstrate that targeted DNAm analysis facilitates reliable discrimination of malignant and healthy samples. However, since healthy samples also comprise few abnormal-classified DNAm reads the approach does not yet reliably discriminate MRD positive and negative samples.

A human somatic cell culture system for modelling gene silencing by transcriptional interference.

Transcriptional interference and transcription through regulatory elements (transcriptional read-through) are implicated in gene silencing and the establishment of DNA methylation. Transcriptional read-through is needed to seed DNA methylation at imprinted genes in the germ line and can lead to aberrant gene silencing by DNA methylation in human disease. To enable the study of parameters and factors influencing transcriptional interference and transcriptional read-through at human promoters, we established a somatic cell culture system. At two promoters of imprinted genes (UBE3A and SNRPN) and two promoters shown to be silenced by aberrant transcriptional read-through in human disease (MSH2 and HBA2) we tested, if transcriptional read-through is sufficient for gene repression and the acquisition of DNA methylation. Induction of transcriptional read-through from the doxycycline-inducible CMV promoter resulted in consistent repression of all downstream promoters, independent of promoter type and orientation. Repression was dependent on ongoing transcription, since withdrawal of induction resulted in reactivation. DNA methylation was not acquired at any of the promoters. Overexpression of DNMT3A and DNMT3L, factors needed for DNA methylation establishment in oocytes, was still not sufficient for the induction of DNA methylation. This indicates that induction of DNA methylation has more complex requirements than transcriptional read-through and the presence of de novo DNA methyltransferases.

Chicken or Egg: Is Clonal Hematopoiesis Primarily Caused by Genetic or Epigenetic Aberrations?

Hematopoietic malignancies, including multiple myeloma, are associated with characteristic mutations and genetic instabilities that drive malignant transformation. On the other hand, tumor formation is also associated with drastic epigenetic aberrations, which can impact the genetic sequence. Therefore, the question arises if malignant transformation is primarily caused by genetic or epigenetic events. The tight connection of these processes becomes obvious by the fact that in several malignancies, as well as in age-related clonal hematopoiesis, mutations are particularly observed in epigenetic writers such as DNMT3A and TET2. On the other hand, specific epigenetic aberrations, so-called "epimutations," can mimic genomic mutations. In contrast to the genetic sequence, which remains relatively stable throughout life, the epigenome notoriously undergoes drastic changes in normal hematopoietic development and aging. It is conceivable that such epigenetic reorganization, e.g., in 3D chromatin conformation, paves the way for secondary chromosomal instabilities, which then result in tumor-specific genomic changes that further trigger disease progression. This scenario might explain the occurrence of tumor-specific mutations particularly in the elderly. Taken together, the causality dilemma is difficult to solve because genetic and epigenetic aberrations are interlinked during disease development. A better understanding of how the chromatin structure or 3D nuclear organization can evoke specific mutations might provide new perspectives for prevention, early diagnostics, and targeted therapy.

Variants of DNMT3A cause transcript-specific DNA methylation patterns and affect hematopoiesis.

De novo DNA methyltransferase 3A (DNMT3A) plays pivotal roles in hematopoietic differentiation. In this study, we followed the hypothesis that alternative splicing of DNMT3A has characteristic epigenetic and functional sequels. Specific DNMT3A transcripts were either down-regulated or overexpressed in human hematopoietic stem and progenitor cells, and this resulted in complementary and transcript-specific DNA methylation and gene expression changes. Functional analysis indicated that, particularly, transcript 2 (coding for DNMT3A2) activates proliferation and induces loss of a primitive immunophenotype, whereas transcript 4 interferes with colony formation of the erythroid lineage. Notably, in acute myeloid leukemia expression of transcript 2 correlates with its in vitro DNA methylation and gene expression signatures and is associated with overall survival, indicating that DNMT3A variants also affect malignancies. Our results demonstrate that specific DNMT3A variants have a distinct epigenetic and functional impact. Particularly, DNMT3A2 triggers hematopoietic differentiation and the corresponding signatures are reflected in acute myeloid leukemia.

Leukocyte Counts Based on DNA Methylation at Individual Cytosines.

BACKGROUND: White blood cell counts are routinely measured with automated hematology analyzers, by flow cytometry, or by manual counting. Here, we introduce an alternative approach based on DNA methylation (DNAm) at individual CG dinucleotides (CpGs). METHODS: We identified candidate CpGs that were nonmethylated in specific leukocyte subsets. DNAm levels (ranging from 0% to 100%) were analyzed by pyrosequencing and implemented into deconvolution algorithms to determine the relative composition of leukocytes. For absolute quantification of cell numbers, samples were supplemented with a nonmethylated reference DNA. RESULTS: Conventional blood counts correlated with DNAm at individual CpGs for granulocytes (r = -0.91), lymphocytes (r = -0.91), monocytes (r = -0.74), natural killer (NK) cells (r = -0.30), T cells (r = -0.73), CD4+ T cells (r = -0.41), CD8+ T cells (r = -0.88), and B cells (r = -0.66). Combination of these DNAm measurements into the "Epi-Blood-Count" provided similar precision as conventional methods in various independent validation sets. The method was also applicable to blood samples that were stored at 4 °C for 7 days or at -20 °C for 3 months. Furthermore, absolute cell numbers could be determined in frozen blood samples upon addition of a reference DNA, and the results correlated with measurements of automated analyzers in fresh aliquots (r = 0.84). CONCLUSIONS: White blood cell counts can be reliably determined by site-specific DNAm analysis. This approach is applicable to very small blood volumes and frozen samples, and it allows for more standardized and cost-effective analysis in clinical application.

DNA-methylation in C1R is a prognostic biomarker for acute myeloid leukemia.

BACKGROUND: Epigenetic aberrations play a central role in the pathophysiology of acute myeloid leukemia (AML). It has been shown that molecular signatures based on DNA-methylation (DNAm) patterns can be used for classification of the disease. In this study, we followed the hypothesis that DNAm at a single CpG site might support risk stratification in AML. FINDINGS: Using DNAm profiles of 194 patients from The Cancer Genome Atlas (TCGA), we identified a CpG site in complement component 1 subcomponent R (C1R) as best suited biomarker: patients with higher methylation at this CpG site (>27 % DNAm) reveal significantly longer overall survival (53 versus 11 months; P < 0.0001). This finding was validated in an independent set of 62 DNAm profiles of cytogenetically normal AML patients (P = 0.009) and with a region-specific pyrosequencing assay in 84 AML samples (P = 0.012). DNAm of C1R correlated with genomic DNAm and gene expression patterns, whereas there was only moderate association with gene expression levels of C1R. These results indicate that DNAm of C1R is a biomarker reflecting chromatin reorganization rather than being of pathophysiological relevance per se. Notably, DNAm of C1R was associated with occurrence of specific genomic mutations that are traditionally used for risk stratification in AML. Furthermore, DNAm of C1R correlates also with overall survival in several other types of cancer, but the prognostic relevance was less pronounced than in AML. CONCLUSIONS: Analysis of DNAm at C1R provides a simple, robust, and cost-effective biomarker to further complement risk assessment in AML.