Lactylation-Related Gene Biomarkers in Acute Myeloid Leukemia

Acute myeloid leukemia research identifies seven hub lactylation-related genes (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) through integrative analysis of GEO and TCGA data. The study employs machine learning algorithms including LASSO-logistic, SVM-RFE, and Boruta to validate prognostic biomarkers. GZMB and LSP1 were confirmed via Mendelian randomization as clinical modeling indicators.

Use Cases

• Validate the prognostic power of the seven hub LRGs (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) using the GLM model identified in the study.
• Analyze the relationship between key LRGs like GZMB and LSP1 and immune cell infiltration patterns using CIBERSORT methodology.
• Screen for potential drug candidates targeting GZMB or LSP1 by replicating the molecular docking approach for compounds like (-)-gallocatechin gallate and indomethacin.
• Assess pan-lactylation levels in AML cell lines under exogenous lactate or sodium oxamate treatment conditions as described in the experimental results.

Strengths

• Identifies seven specific hub lactylation-related genes (LSP1, MPO, GZMB, SPINK2, HLA-DRB1, HLA-DRA, POU2F2) with analytical validation.
• Employs multiple machine learning algorithms (LASSO-logistic, SVM-RFE, Boruta) and Mendelian randomization for robust biomarker identification.
• Integrates data from authoritative public repositories, specifically the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA).

Limitations

• The dataset is very small at 19.6 KB, indicating limited raw data or summary-level results rather than a large primary dataset.
• Unknown row and column structure prevents direct analysis of individual patient or sample-level records.
• Findings are specific to acute myeloid leukemia and the seven identified genes, limiting generalizability to other cancers or biological processes.

Provenance

Source

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

Collection Method

Computational analysis using Seurat, limma, WGCNA, and machine learning algorithms on RNA and single-cell sequencing data, supplemented by experimental validation (Western blot, qRT–PCR, immunohistochemistry).

Freshness

Last updated March 23, 2026.