Extended Data Fig. 9: Clinical utility of pharmacoscopy for multiple myeloma.
a, Graphic representation of the non-immunotherapy subcohort (n = 19 patients), similar to Fig. 8c. Patients with their respective PhenoGroups are reported, followed by the sample IDs, and treatments given in the clinic. A heatmap reports individual PCY scores for the treatments given, with their respective integrated PCY (iPCY) scores on the right. Finally, each patient’s time to the next treatment is reported, with blue indicating PCY-sensitive and red PCY-resistant samples. Ongoing treatments are indicated. b, Kaplan-Meier curves showing the time to next treatments in days for all 34 patients (combining both the non-immunotherapy and immunotherapy subcohorts). Thick lines represent cohort stratification by PCY-sensitivity (determined as in Fig. 8b) of myeloma cells. In comparison, dashed lines represent equivalently-calculated cohort stratification by PCY-sensitivity of all plasma cells (as detected by the 4-class CNN classifier). Plasma cell drug responses do not stratify clinical responses. Relevant p-values from the log-rank (Mantel-Cox) test are indicated on the right, with a table reporting the number of patients at risk at different time points below the plot. c, Scatter plot showing similarity in subpopulation abundances identified across MM samples by PCY (x-axis) and flow cytometry (y-axis) (n = 5 patient samples across n = 4 subpopulations). Spearman’s rank and Pearson’s correlations and p-values are indicated. d, ROC curve on the false (x-axis) and true (y-axis) positive rate of inference of samples belonging to PG1 based on the clinical flow-based abundance of plasma cells in each sample. PG1 inference was performed by thresholding on the plasma cell abundances. Area under the characteristic curve is indicated. ROC curve includes data on 67 patient samples for which the clinical flow data was available.
