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Investigation of Measurable Residual Disease in Acute Myeloid Leukemia by DNA Methylation Patterns

ABSTRACT: Assessment of measurable residual disease (MRD) upon treatment of acute myeloid leukemia (AML) remains a challenge. It is usually addressed by highly sensitive PCR-based screening of disease-specific mutations or multiparametric flow cytometry. However, not all patients have suitable mutations to track the disease and heterogeneity of applied 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, many of these aberrations are shown to affect both alleles. Using bisulfite amplicon sequencing (BA-seq), we captured local DNAm patterns flanking these AML associated CpGs, and trained shallow-learning and deep-learning algorithms to identify anomalous, non healthy DNAm patterns within the amplicons. The method was then tested on follow-up samples with and without MRD status. Notably, many MRD negative samples revealed higher anomaly ratios than healthy controls. Our results demonstrate that targeted DNAm analysis facilitates reliable discrimination of malignant and healthy samples. However, even after successful treatment aberrant DNAm patterns persist in some samples that were classified as MRD negative.

ORGANISM(S): Homo sapiens

PROVIDER: GSE166264 | GEO | 2021/06/16

REPOSITORIES: GEO

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