DNA methylation analysis improves the prognostication of acute myeloid leukemia

Abstract Acute myeloid leukemia is classified by the presence or absence of recurrent cytogenetic aberrations. In order to improve diagnosis and therapy, more recently new studies have been performed to supplement the current classification with refined molecular information based on gene expression profiling. However, it has been established that expression levels of genes are often largely controlled by the state of cytosine methylation in the adjacent promoter region. Thus we were interested to evaluate the quantitative methylation levels for a previously identified predictive set of genes (Bullinger et al. 2004) using a novel technology based on a unique combination of base specific cleavage of single stranded nucleic acids with MALDI TOF detection. We have employed this new quantitative high throughput DNA methylation analysis technology to analyze 147 promoter regions in a total of 192 individuals. The resulting quantitative methylation data was analyzed using a semi-supervised approach to evaluate the quantitative methylation data as a predictor for patient survival. We used a first set of 96 individuals to train a statistical learning algorithm and a second set of 96 samples to validate the trained algorithm. The analysis revealed quantitative methylation patterns as a reliable predictor for survival (p < 0.001). Subsequently, we combined the methylation based predictive model with the results from the expression based predictor. The combination of both models yielded a superior predictive model for patient survival, which outperformed all clinical and cytogenetic risk stratification in the given sample set. The results of this work revealed a potential significance of DNA methylation in the pathophysiology of AML and suggest that DNA-methylation patterns might be useful molecular markers for patient survival prediction based on the fact that large-scale DNA methylation studies can now be performed with reasonable efforts in a limited amount of time. Therefore, these results lay the groundwork for future research which might ultimately enable individualized therapy based on improved molecular characterization of AML.

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Faculty Opinions recommendation of DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1528964.1017064 ◽

2010 ◽

Author(s):

Lee Grimes

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Acute Myeloid

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Identification and validation of obesity-related gene LEP methylation as a prognostic indicator in patients with acute myeloid leukemia

Clinical Epigenetics ◽

10.1186/s13148-021-01013-9 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Ting-juan Zhang ◽

Zi-jun Xu ◽

Yu Gu ◽

Ji-chun Ma ◽

Xiang-mei Wen ◽

...

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Prognostic Indicator ◽

The Cancer Genome Atlas ◽

Related Gene ◽

Targeted Bisulfite Sequencing ◽

Specific Pcr ◽

Frequent Event ◽

Acute Myeloid

Abstract Background Obesity confers enhanced risk for multiple diseases including cancer. The DNA methylation alterations in obesity-related genes have been implicated in several human solid tumors. However, the underlying role and clinical implication of DNA methylation of obesity-related genes in acute myeloid leukemia (AML) has yet to be elucidated. Results In the discovery stage, we identified that DNA methylation-associated LEP expression was correlated with prognosis among obesity-related genes from the databases of The Cancer Genome Atlas. In the validation stage, we verified that LEP hypermethylation was a frequent event in AML by both targeted bisulfite sequencing and real-time quantitative methylation-specific PCR. Moreover, LEP hypermethylation, correlated with reduced LEP expression, was found to be associated with higher bone marrow blasts, lower platelets, and lower complete remission (CR) rate in AML. Importantly, survival analysis showed that LEP hypermethylation was significantly associated with shorter overall survival (OS) in AML. Moreover, multivariate analysis disclosed that LEP hypermethylation was an independent risk factor affecting CR and OS among non-M3 AML. By clinical and bioinformatics analysis, LEP may be also regulated by miR-517a/b expression in AML. Conclusions Our findings indicated that the obesity-related gene LEP methylation is associated with LEP inactivation, and acts as an independent prognostic predictor in AML.

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Decitabine induces very early in vivo DNA methylation changes in blasts from patients with acute myeloid leukemia

Leukemia Research ◽

10.1016/j.leukres.2012.10.015 ◽

2013 ◽

Vol 37 (2) ◽

pp. 190-196 ◽

Cited By ~ 20

Author(s):

Rainer Claus ◽

Dietmar Pfeifer ◽

Maika Almstedt ◽

Manuela Zucknick ◽

Björn Hackanson ◽

...

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Acute Myeloid

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

Leukemia ◽

10.1038/s41375-021-01316-z ◽

2021 ◽

Author(s):

Tanja Božić ◽

Chao-Chung Kuo ◽

Jan Hapala ◽

Julia Franzen ◽

Monika Eipel ◽

...

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Residual Disease ◽

Amplicon Sequencing ◽

Multiparametric Flow Cytometry ◽

Methylation Patterns ◽

Cg Dinucleotides ◽

Measurable Residual Disease ◽

Acute Myeloid

AbstractAssessment 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.

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Tritsomy 8 Acute Myeloid Leukemia Analysis Reveals New Insights of DNA Methylome with Identification of HHEX as Potential Diagnostic Marker

Biomarkers in Cancer ◽

10.4137/bic.s19614 ◽

2015 ◽

Vol 7 ◽

pp. BIC.S19614 ◽

Cited By ~ 4

Author(s):

Marwa H. Saied ◽

Jacek Marzec ◽

Sabah Khalid ◽

Paul Smith ◽

Gael Molloy ◽

...

Keyword(s):

Dna Methylation ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Diagnostic Marker ◽

Cpg Island ◽

Global Analysis ◽

Extra Chromosome ◽

Chromosome 8 ◽

Trisomy 8 ◽

Acute Myeloid

Trisomy 8 acute myeloid leukemia (AML) is the commonest numerical aberration in AML. Here we present a global analysis of trisomy 8 AML using methylated DNA immunoprecipitation-sequencing (MeDIP-seq). The study is based on three diagnostic trisomy 8 AML and their parallel relapse status in addition to nine non-trisomic AML and four normal bone marrows (NBMs). In contrast to non-trisomic DNA samples, trisomy 8 AML showed a characteristic DNA methylation distribution pattern because an increase in the frequency of the hypermethylation signals in chromosome 8 was associated with an increase in the hypomethylation signals in the rest of the chromosomes. Chromosome 8 hypermethylation signals were found mainly in the CpG island (CGI) shores and interspersed repeats. Validating the most significant differentially methylated CGI ( P = 7.88 · 10–11identified in trisomy 8 AML demonstrated a specific core region within the gene body of HHEX, which was significantly correlated with HHEX expression in both diagnostic and relapse trisomy 8 AMLs. Overall, the existence of extra chromosome 8 was associated with a global impact on the DNA methylation distribution with identification of HHEX gene methylation as a potential diagnostic marker for trisomy 8 AML.

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