LPMD Algorithm: Methylation Disorder Data for DNMT3A-Mutated AML and Azacitidine Response

Research data from a study developing the Local Promoter Methylation Disorder (LPMD) algorithm to analyze epigenetic instability in acute myeloid leukemia. The dataset includes results from multiple patient cohorts (GSE62298, TCGA-LAML, GSE152710) totaling over 300 samples, used to identify differentially methylated disorder regions and build a 5-DMDR predictive panel. The data was authored by Xin Liu and last updated on March 18, 2026.

Use Cases

• Predicting azacitidine treatment response based on the 5-DMDR panel identified in the study.
• Analyzing methylation disorder patterns associated with DNMT3A mutations.
• Investigating bidirectional epigenetic disruption (aberrant stabilization vs. maintenance failure) in promoter regions.
• Validating the LPMD algorithm's performance for quantifying local methylation heterogeneity.

Strengths

• Algorithm validated across multiple independent cohorts (GSE62298, TCGA-LAML, GSE152710) with over 300 total samples.
• Predictive panel achieved an AUC of 0.777 with 81% sensitivity and 73% specificity for azacitidine response.
• Longitudinal analysis includes 153 samples for tracking treatment dynamics.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect temporal or source bias inherent to the specific research cohorts used.

Provenance

Source

figshare, authored by Xin Liu.

Collection Method

Data derived from applying the LPMD algorithm to public and research cohorts (GSE62298, TCGA-LAML, GSE152710).

Freshness

Last updated 2026-03-18 05:21:24