Supplementary Figure 6: Tolerance to types of errors of tumor PDOs.
From: Ongoing chromosomal instability and karyotype evolution in human colorectal cancer organoids
(a) Quantification of single cell fate tracking per type of error and per tumor PDOs. Events were classified as cell division, cell death or survival without division. Graph shows the mean percentage of segregation errors observed in all cells per independent replicate. Graph is different representation of the data of Figure 5D. n = 2 or 3 independent experiments. (b) Quantification of single cell fate tracking. Daughter cells originating from the same mother cell were grouped. Mitotic events were classified as correct or erroneous mitoses and plots represent the respective frequencies of subsequent fate (cell division, cell death or survival without division). Graph shows the mean percentage of events observed in all cells per independent replicate. Different representation of data shown in Figure 5D. n = 2 or 3 independent experiments. (c) Multiple regression analysis of heterogeneity or aneuploidy versus the percentage of division after error (DAE, %) per tumor PDOs. Heterogeneity and aneuploidy scores obtained in 2Mb bins generated using a modified version of the Aneufinder algorithm from Figure 4. Mean CIN levels are derived from Figure 1C. Death and Growth values derived from Figure 5A. Different representation of data shown in Figure 5F. n = 1 (heterogeneity), 2 (DAE), 2 or 3 (CIN) or 3 (Growth and Death) independent experiments. Shapiro Wilk test to determine if sample is normal distributed. If p-value < α (0.05), H0: Y=b0 is rejected. Alternative hypothesis H1: Y=b0+b1X1+...+bpXp. We used right tail to check if the regression formula and parameters are statistically significant.
