Table 1_Local Promoter Methylation Disorder algorithm reveals bidirectional epigenetic dis

68 AML patients from the GSE62298 dataset were used to develop the Local Promoter Methylation Disorder algorithm, which quantifies epigenetic instability. The algorithm was validated in a 20-sample WGBS cohort and a 194-sample TCGA-LAML cohort, with clinical predictive value assessed in 63 high-risk MDS/secondary AML patients. The data, authored by Xin Liu and last updated in March 2026, includes a 5-DMDR panel for predicting azacitidine treatment response.

Use Cases

• Predicting azacitidine treatment response in high-risk MDS/secondary AML patients based on the 5-DMDR panel.
• Analyzing bidirectional epigenetic disruption patterns associated with DNMT3A mutations.
• Monitoring treatment dynamics by tracking changes in Local Promoter Methylation Disorder scores over time.
• Identifying differentially methylated disorder regions (DMDRs) enriched in promoter regions.

Strengths

• Algorithm validated across multiple independent cohorts (GSE62298, a 20-sample WGBS cohort, and the 194-sample TCGA-LAML cohort).
• Clinical predictive panel (5-DMDRs) achieved an AUC of 0.777 with 81% sensitivity and 73% specificity.
• Includes longitudinal data from 153 samples for treatment dynamics analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 11.7 KB, indicating limited scope, likely containing summary results rather than raw data.

Provenance

Source

figshare, authored by Xin Liu.

Collection Method

Algorithm development and validation using multiple public genomic datasets (GSE62298, WGBS cohort, TCGA-LAML, GSE152710).

Freshness

Last updated 2026-03-18 05:21:22; freshness should be verified.