Fig. 5: Construction of an MCL1 inhibitor efficacy model. | Nature Biomedical Engineering

Fig. 5: Construction of an MCL1 inhibitor efficacy model.

From: Profiling protein–protein interactions to predict the efficacy of B-cell-lymphoma-2-homology-3 mimetics for acute myeloid leukaemia

Fig. 5

a, The absolute Pearson correlations between ex vivo AUC of AZD-5991 and PPI profiles for primary AML samples (*P < 0.05, **P < 0.01, ***P < 0.001; P values are provided as Source Data) (n = 27). b–d, Correlations between ex vivo AUC and single PPI metrics. MCL1 total level (coefficient: 0.05, P = 1.5 × 10−4) (b), MCL1-BIMBH3 PBA (coefficient: 0.04, P = 0.005) (c), BCLxL-BIMBH3 PBA (coefficient: −0.13, P = 0.010) (one-sided F-test) (d). e, Comparison of BCLxL-BIMBH3 PBA counts for the AZD-5991 to responsive (ex vivo AUC ≥ 0.61, n = 12) and non-responsive (ex vivo AUC < 0.61, n = 15) AML samples (two-sided two-sample t-test, P = 0.03). For the boxplots, the centre line represents the median, the box limits are the upper and lower quartiles, and the whiskers represent 1.5× interquartile range. f, Correlation between ex vivo AUC and the combination of multiple PPI metrics (MCL1 total level, BCLxL-BIMBH3 PBA, BCLxL-BAK CPX) (one-sided F-test, P = 7.0 × 10−7). g, ROC curve between the estimated score and the ex vivo efficacy (two-sided t-test, P = 6.4 × 10−4).

Source data

Back to article page