Extended Data Fig. 2: Global discovery of essential cysteines in cancer dependency proteins.
From: Assigning functionality to cysteines by base editing of cancer dependency genes
a, Scatter plot showing the dependencies included in the base-editing screens. b, Barplots summarizing the number of designed sgRNAs per cysteine. (Left) all or (right) ligandable cysteines in the dependency proteins. c, Plot comparing the essential cysteine hit rate using sgRNA targeting cysteines in dependency proteins or non-targeting sgRNA data randomly resampled from the library 10 times. The p value was calculated using two-sided Student’s t test. d, Scatter plot showing the correlation between cysteine dropouts observed with the ABE or the CBE library for Common Essential proteins in PC14 and KMS26. The Pearson correlation and two-sided p value is shown. e, f, Density scatter plots comparing the evolutionary conservation and significance of dropout of cysteines using the ABE (e) or CBE (f). Pearson correlations and two-sided p values are shown. g, Barplot showing the distribution of missense mutations for essential cysteines in orthologous proteins. h, i, Scatter plots comparing the day 16 vs day 1 LFC values of cysteines in Common Essential dependencies in KMS26 versus PC14 cells. The essential cysteines are highlighted for (h) ABE and (i) CBE libraries. j, k, Dot plots comparing the dropouts of cysteines from Strongly Selective dependencies using (j) PC14 or (k) KMS26 cells. Each pair of points compares the same cysteine. The cysteines were included based on the first essentiality filter (FDR < 10%, LFC < −0.6) only using data from one cell line without considering the dependency difference between the two cell lines. A second selectivity filter (greater dropout in the more dependent cell line, LFC difference > 0.3) was applied, and cysteines passing this filter are shown in red. Only Strongly Selective proteins with gene-level dependency scores that are sufficiently different (CERES difference > 0.8) between PC14 and KMS26 were included. The p values were calculated using two-sided paired Student’s t test based on all cysteines that pass the first filter. For c, d, e, f, h, i, j, k, the base-editing dropout screen data represent two independent experiments in PC14 and KMS26.
