Data supporting the publication: Transcriptomic analysis of glycolytic regulation by lncRNAs in acute myeloid leukemia

Acute myeloid leukemia (AML), a high-mortality malignancy, limits the efficacy of traditional therapies due to high heterogeneity. Glycolysis drives AML progression via the tumor microenvironment, but glycolysis-related long non-coding RNAs' (lncRNAs') pathological role in AML remains unclear. This study aimed to reveal key glycolysis-related lncRNAs in AML and their mechanisms of action.The AML dataset and glycolysis-related genes (GRGs) were obtained from public databases. Glycolysis-related lncRNAs were predicted based on GRGs. Differential analysis identified differentially expressed lncRNAs (DE-lncRNAs) between case and control groups in the training set, with overlapping lncRNAs between DE-lncRNAs and glycolysis-related lncRNAs as candidate lncRNAs. Feature lncRNAs were obtained via Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE) and Boruta. Key lncRNAs were identified through receiver operating characteristic (ROC) analysis. A nomogram was constructed to evaluate the predictive value of key lncRNAs for AML. Molecular regulatory network, drug prediction, and expression level validation were conducted on the key lncRNAs. Expression of key lncRNAs was verified via reverse transcription-quantitative PCR (RT-qPCR).