Lactylation-Related Gene Biomarkers in Acute Myeloid Leukemia

Seven hub lactylation-related genes (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) were identified as prognostic biomarkers for acute myeloid leukemia (AML) through integrative profiling. The analysis leveraged RNA and single-cell sequencing data from public databases and validated findings using machine learning models and Mendelian randomization. GZMB and LSP1 were specifically validated as key clinical modeling indicators.

Use Cases

• Validate the prognostic power of the seven identified hub genes (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) in independent AML cohorts.
• Investigate the relationship between GZMB/LSP1 expression levels and immune cell infiltration patterns in the leukemic microenvironment.
• Screen for potential drug candidates targeting GZMB or LSP1 using molecular docking simulations based on the reported binding potentials.
• Assess pan-lactylation levels in AML cell lines under different metabolic conditions, such as exogenous lactate or sodium oxamate treatment.

Strengths

• Identifies seven specific lactylation-related genes (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) as hub biomarkers.
• Validation employs multiple machine learning algorithms (LASSO, SVM-RFE, Boruta) and Mendelian randomization.
• Findings are supported by experimental data from AML cell lines (e.g., Kasumi-1) and patient samples via qRT-PCR and immunohistochemistry.

Limitations

• The dataset is small at 23.5 KB, indicating limited primary data volume, likely containing summary results rather than raw sequencing data.
• Specific row and column counts for the underlying data tables are unknown, limiting assessment of analytical scope.
• The analysis is focused on specific genes from public databases, which may not capture the full lactylation landscape in AML.

Provenance

Source

Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases.

Collection Method

Integrative analysis of RNA and single-cell sequencing data using Seurat, WGCNA, enrichment analyses, and machine learning algorithms.

Freshness

Last updated March 23, 2026.