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Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
Published on: June 16, 2017
DNA methylation-based subtypes of acute myeloid leukemia with distinct prognosis and clinical features
Jimo Jian1,2, Chenglu Yuan1, Chunyan Ji2
1Department of Hematology, Qilu Hospital of Shandong University, Qingdao, 266035, Shandong, People's Republic of China.
Abstract:
Acute myeloid leukemia (AML) is a malignancy of the stem cell precursors of the myeloid lineage. DNA methylation is an important DNA modification that regulates gene expression. Investigating AML heterogeneity based on DNA methylation could be clinically informative for improving clinical diagnosis and prognosis. The AML subtypes based on DNA methylation were identified by unsupervised consensus clustering. The association of these subtypes with gene mutation, copy number variations, immune infiltration and clinical features were further explored. Finally, univariate, LASSO and multivariate cox regression analyses were used to identify prognosis-associated genes and construct risk model for AML patients. In addition, we validated this model by using other datasets and explored the involved biological functions and pathways of its related genes. Three CpG island methylator phenotypes (CIMP-H, CIMP-M and CIMP-L) were identified using the 91 differential CpG sites. Overall survival, morphology, macrophages M0 and monocytes were distinct from each other. The most frequently mutated gene in CIMP-L was DNMT3A while which in CIMP-M that was RUNX1. In addition, the TIDE scores, used to predict the response to immune checkpoint inhibitors, were significantly different among CIMPs. The CIMP-associated prognosis risk model (CPM) using 32 key genes had convinced accuracy of prediction to forecast 0.5-year, 1-year, 3-year and 5-year survival rates. Moreover, the risk score-related genes were significantly enriched in pattern specification process, regionalization, embryonic organ morphogenesis and other critical cancer-related biological functions. We systematically and comprehensively analyzed the DNA methylation in AML. The risk model we constructed is an independent predictor of overall survival in AML and could be used as prognostic factor for AML treatment.
Insights
This study identifies distinct DNA methylation subtypes in acute myeloid leukemia (AML), revealing differences in mutations and immune infiltration. A novel risk model based on methylation predicts patient survival, offering a new prognostic tool for AML treatment.
Area of Science:
- Oncology
- Epigenetics
- Genomics
Background:
- Acute myeloid leukemia (AML) is a myeloid stem cell malignancy.
- DNA methylation is a key regulator of gene expression with implications for AML heterogeneity.
- Understanding AML subtypes based on DNA methylation can improve clinical diagnosis and prognosis.
Purpose of the Study:
- To identify AML subtypes using DNA methylation patterns.
- To explore associations between methylation subtypes and genetic mutations, copy number variations, immune infiltration, and clinical features.
- To develop and validate a DNA methylation-based risk model for predicting AML patient survival.
Main Methods:
- Unsupervised consensus clustering to define AML subtypes based on DNA methylation.
- Analysis of gene mutations, copy number variations, immune infiltration (TIDE scores), and clinical features across subtypes.
- Cox regression analyses (univariate, LASSO, multivariate) to identify prognostic genes and construct a risk model.
- External dataset validation of the constructed risk model.
Main Results:
- Three distinct CpG island methylator phenotypes (CIMP-H, CIMP-M, CIMP-L) were identified.
- Significant differences in overall survival, morphology, and immune cell infiltration (macrophages M0, monocytes) were observed among CIMPs.
- Specific gene mutations (DNMT3A in CIMP-L, RUNX1 in CIMP-M) and differential immune checkpoint inhibitor response (TIDE scores) were linked to CIMPs.
- A 32-gene CIMP-associated prognosis risk model (CPM) demonstrated accurate prediction of 0.5, 1, 3, and 5-year survival rates.
- Risk score-related genes were enriched in developmental and cancer-related biological functions.
Conclusions:
- DNA methylation analysis provides a comprehensive understanding of AML heterogeneity.
- The developed CPM serves as an independent predictor of overall survival in AML patients.
- The CPM can be utilized as a valuable prognostic factor for guiding AML treatment strategies.
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