Fig. 2: Potential regulatory mechanisms underlying glycolysis in AML. | npj Digital Medicine

Fig. 2: Potential regulatory mechanisms underlying glycolysis in AML.

From: Machine learning-driven glycolytic subtyping and exosome-based PKM splicing modulation overcome drug resistance in hyper-glycolytic myeloid leukemia

Fig. 2: Potential regulatory mechanisms underlying glycolysis in AML.

A Intersection analysis of differentially expressed genes (DEGs) and glycolysis-related genes (GRGs) in AML malignant cells compared with normal cells. B Expression profiles of 16 differentially expressed GRGs in a single-cell dataset. C Chromosomal locations of the 16 differentially expressed GRGs. D Identification of 16 transcription factors that exhibit differential enrichment of GRG binding sites. The i-cisTarget motif platform was utilized to analyze normalized enrichment scores (NESs). E Comparison of HIF1A expression between malignant and normal cells in AML single-cell datasets. F Correlation analysis between HIF1A and the expression levels of the 16 GRGs. G Visualization of intercellular ligand‒receptor pairs in single-cell data, with color indicating the likelihood and magnitude representing the significance of cell communication. H–J Communication network depicting MIF signaling interactions among distinct cell groups. The color consistency between lines and squares indicates source‒target relationships, where squares represent source cells, while line ends indicate target cells. K Heatmap displaying the dominant senders, receivers, mediators, and influencers involved in MIF signaling inferred from network centrality scores within the tumor context. L Expression characteristics of molecules within the MIF pathway across different cell groups.

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