Fig 2: MEF2D-IRF8 regulatory loop in AML(A) Similarity matrix (left) of 66 leukemia-enriched TF dependencies in their (minus) CERES effects (row) versus mRNA expressions (column) hierarchically clustered by pair-wise Pearson correlation in 49 leukemia cell lines. Heatmap (right) implicates average expression level of TFs in different subtypes of leukemia.(B) RNA-seq rank plot of gene expression changes in MOLM-13 (up, (Cao et al., 2021)) or MV4; 11 cells 4–5 days after transduction of two independent sgNeg or sgMEF2D. Dark dots indicate IRF8-regulated genes in Figure S3A.(C) Scatterplot of MEF2D CERES versus IRF8 CERES in leukemia cell lines.(D and E) Scatterplot that shows a linear correlation between IRF8’s mRNA expression and MEF2D’s CERES dependency scores (D) or MEF2D’s mRNA expression and IRF8’s CERES dependency scores (E). Each dot represents one cell line; the shaded regions indicate 95% confidence interval for the linear regression model.(F) Pearson correlation analysis of MEF2D mRNA expression with other genes in 173 AML patients. Data retrieved from TCGA dataset.(G) Scatterplot of MEF2D and IRF8 expression in 173 AML patients.(H) Meta-profile (top) and density plot (bottom) of MEF2D CUT&RUN and H3K27ac ChIP-seq peaks in MOLM-13 cells. Peaks are ranked by MEF2D CUT&RUN tag counts.(I) Gene tracks of H3K27ac and MEF2D enrichment at IRF8 locus in MOLM-13 cells. Shadowed in gray is the AML-specific IRF8 enhancer (IE). (J) CUT&RUN-qPCR against MEF2D on IRF8 locus (n = 3).

Fig 3: IRF8 supports PU.1’s chromatin occupancy and transcriptional output(A) Scatterplot of IRF8 CERES versus PU.1 CERES in leukemia cell lines.(B) GSEA analysis of IRF8-KO (left) and MEF2D-KO (right) RNA-seq data in MOLM-13 cells. PU.1 signature scatterplot of MEF2D CERES versus IRF8 CERES in leukemia cell lines, where the PU.1 signature is defined as the top 500 downregulated genes on PU.1 depletion. Normalized enrichment score (NES) and false discovery rate (FDR) q value are shown.(C and D) Density plot (C) and meta-profiles (D) of PU.1, H3K27ac and H3K4me1 ChIP-seq signals at IRF8 binding sites in MOLM13-dIRF8 cells (Cao et al., 2021) on 4 h treatment of DMSO or dTAG that rapidly eliminates IRF8 protein. Peaks are ranked by IRF8 ChIP-seq tag counts (n = 3).(E) Immunoblotting of IRF8, PU.1 and GAPDH in whole-cell lysates of MOLM13-dIRF8 cells treated with 500nM dTAG-47 for 4h.(F and G) Gene tracks of ChIP-seq signal from Figures 4C and 4D at MEF2D (E) or CD180 (F) locus.

Fig 4: MEF2D is an AML-biased dependency(A) Violin plots of MEF2D CERES effects.(B) Competition-based proliferation assays in MOLM-13 (AML, upper left), MV4; 11 (AML, upper right), THP1 (AML, bottom left) and K562 (an acute (erythro)blastic transformation of prior CML, bottom right) cell lines stably expressing Cas9. Plotted are relative GFP/sgRNA + population normalized based on day 3 (n = 3–5, mean ± SEM). sgNeg, negative control. sgPCNA, positive control.(C) Scatterplot that shows a linear correlation between MEF2D’s CERE dependency scores and mRNA expression in leukemia (red) or other cancer cell lines (light gray) in the DepMap dataset. Each dot represents one cell line; the shaded regions indicate 95% confidence interval for the linear regression model.(D) Immunoblotting of MEF2D in indicated whole-cell lysates. MEF2Dhi cell lines are labeled in purple. HCC, Hepatocellular carcinoma.

Fig 5: A working model illuminating MEF2D-IRF8 circuit in AMLOncogenic events (such as KMT2A-r and FLT3ITD + NPM1c) (Yun et al., 2021) can lead to activation and addiction to the MEF2D-IRF8 transcriptional circuit in AML. IRF8-PU.1 complex and MEF2D cooperatively maintain PU.1/MEIS1 co-regulated gene expression (Zhou et al., 2014) and AML state.