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Acute myeloid leukaemia (AML) is a highly heterogeneous disease, which lead to various findings in transcriptomic research. This study addresses these challenges by integrating 34 datasets, including 26 control groups, 6 prognostic datasets and 2 single-cell RNA sequencing (scRNA-seq) datasets to identify 10,000 AML-related genes (ARGs). We focused on genes with low variability and high consistency and successfully discovered 191 AML signatures (ASs). Leveraging machine learning techniques, specifically the XGBoost model and our custom framework, we classified AML subtypes with both scRNA-seq and bulk RNA-seq data, complementing the ELN2022 classification approach. Our research also identified promising treatments for AML through drug repurposing, with solasonine showing potential efficacy for high-risk AML patients, supported by molecular docking and transcriptomic analyses. To enhance reproducibility and customizability, we developed CSAMLdb, a user-friendly database platform. It facilitates the reuse and personalized analysis of nearly all results obtained in this research, including single-gene prognostics, multi-gene scoring, enrichment analysis, machine learning risk assessment, drug repositioning analysis and literature abstract named entity recognition. CSAMLdb is available at http://www.csamldb.com., (© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Objective: To characterize the effect of omeprazole on the spectrum of gene expression in the cultured human umbilical vein endothelial cell (HUVEC) line (EA.hy926), and explore the underlying molecular mechanism., Methods: Affymetrix U133 plus2.0 oligonucleotide microarray was used to detect the alteration in the gene expression profiles induced by 1×10(-5) mol/L omeprazole in HUVECs. Real-time PCR was employed to verify the results of selected differentially expressed genes, and Western blotting was performed to test the expression levels of the related proteins., Results: A total of 282 genes were found to show at least 1.5-fold changes in EA.hy926 cells after treatment with omeprazole for 48 h, including 236 up-regulated and 46 down-regulated ones. These genes were involved in the regulation of transcription, inflammatory response, immune response, cell adherence, anti-apoptosis, and signal transduction., Conclusion: Omeprazole modulates the function of endothelial cells by regulating the gene expression profiles of multiple pathways.