Fig. 11

Use of the yeast phenomic model to predict doxorubicin-gene interaction in cancer cells. a BiomaRt was used to assign yeast-human gene homology for the GDSC and gCSI datasets. b PharmacoGx was used to retrieve differential gene expression for doxorubicin sensitive cell lines from the gCSI and GDSC databases, searching data from individual tissues or across data aggregated from all tissues. Human genes that are underexpressed in doxorubicin sensitive cell lines (UES) with yeast homologs that are deletion enhancers are predicted to be causal in their phenotypic association. Similarly, human genes that are overexpressed in doxorubicin sensitive cancer cell lines (OES) would be predicted to be causal if the yeast homolog was a deletion suppressor in the phenomic dataset. c, d Boxes inside of Venn diagrams indicate the genes for which gene interaction profiles are shown in the heatmaps below. Gene names are to the right of heatmaps, with blue labels indicating genes identified in both the GDSC and gCSI databases and black labels indicating genes found only in the gCSI dataset. The category of homology (see panel a) is indicated in the left column of each heatmap. c Deletion enhancement by yeast genes predicts human functions that buffer doxorubicin cytotoxicity, and thus, reduced expression of homologs in cancer cell lines is predicted to increase doxorubicin sensitivity. d Deletion suppression by yeast genes predicts functions that mediate cytotoxicity and is shown for human homologs having significant association of overexpression in cancer cell lines with increased doxorubicin sensitivity. e, f Genes representing enhancing or suppressing modules from REMc or GTA that are e UES or f OES in at least one of the two databases. Red labels indicate genes found only in the GDSC database. Additional file 11 reports all results from the analysis described above, including assessment of individual tissues