Plates were sealed with aluminium seals (Corning) and stored until imaged at 4C while protected from light. spectrum of phenotypes can identify novel mechanisms of action. It can also reveal unanticipated effects and could thereby reduce high attrition rates of small molecule development pipelines. Here, we used high\content screening and image analysis to measure effects of 1,280 pharmacologically active compounds on complex phenotypes in isogenic malignancy cell lines which harbor activating or inactivating mutations in important oncogenic signaling pathways. Using multiparametric chemicalCgenetic Grapiprant (CJ-023423) conversation analysis, we observed phenotypic geneCdrug interactions for more than 193 compounds, with many affecting phenotypes other than cell growth. We produced a resource termed the Pharmacogenetic Phenome Compendium (PGPC), which enables exploration of drug mode of action, detection of potential off\target effects, and the generation of hypotheses on drug combinations and synergism. For example, we demonstrate that MEK inhibitors amplify the viability effect of the clinically used anti\alcoholism drug disulfiram and show BSP-II that this EGFR inhibitor tyrphostin AG555 has off\target activity around the proteasome. Taken together, this study demonstrates how combining multiparametric phenotyping in different genetic backgrounds can Grapiprant (CJ-023423) be used to predict additional mechanisms of action and to reposition clinically used drugs. (\catenin), (PI3K) was deleted, leaving only the respective wild\type allele, as well as seven knockout cell lines for AKT1AKT1,and together (((and two parental HCT116 cell lines (P1 and P2). HCT116 cells were chosen as a model system since multiple well\characterized isogenic derivatives are available (Torrance mutant [mt], (HCT116 CTNNB1 wt +/mt +)), wild\type (wt) cells (HCT116 CTNNB1 wt +/mt ?) showed protrusions of the cell body, a morphology previously associated with a mesenchymal\like phenotype (Caie wt cells, and the phenoprints indicated largely comparable changes in shape. In contrast, the spindle toxin colchicine induced an apoptosis phenotype in parental HCT116 cells, whereas we observed increased sizes for the wt cells. Analogously, the histone methyltransferase inhibitor BIX01294 experienced a moderate impact on parental HCT116 cells, but led to decreased cell size and altered nuclear shape in wt cells (Fig?2A). Open in a separate window Physique EV2 Phenotypes of the twelve isogenic cell lines employedIsogenic KO cell lines show divergent phenotypes; actin, reddish; DNA, cyan. Phenoprints for the isogenic cell lines are depicted. Level bars?=?20?m. Open in Grapiprant (CJ-023423) a separate window Physique 2 Quantitative analysis of phenotypic chemicalCgenetic interactions Drugs induce either convergent or divergent phenotypic alterations depending on genetic backgrounds as revealed by visual inspection. Phenotypes for parental HCT116 cells (P1; mutant (mut); HCT116 CTNNB 1 wt +/mt +) and wild\type (wt) (HCT116 CTNNB 1 wt +/mt ?) cells, that is, HCT116 cells with a knockout of the mutant allele, differ under control conditions (DMSO). Treatment with etoposide induces an increase in nuclear and cell size in both genetic backgrounds. Colchicine induces apoptosis in parental HCT116 cells and an increase in nuclear and cell size in wt Grapiprant (CJ-023423) (HCT116 CTNNB 1 wt +/mt ?) cells. BIX01294 moderately affects phenotypic features in parental cells, but induces cell condensation in wt (HCT116 CTNNB 1 wt +/mt ?) cells. Colchicine and BIX01294 reduce cell number impartial of genotype. Colors: cyan, DNA; reddish, actin. Scale bars, 20?m. Quantitative analysis of chemicalCgenetic interactions across multiple phenotypic features. ChemicalCgenetic interactions were calculated for all those 20 phenotypic features as explained. Colchicine and BIX01294 display multiple Grapiprant (CJ-023423) interactions in wt (HCT116 CTNNB 1 wt +/mt ?) cells. Interactions are scaled to range of 0 to 1 1. *FDR? ?0.01, highlighted in red. Overlap of chemicalCgenetic interactions between phenotypic groups. Zero values have been omitted for better readability. Specificity and pleiotropy of geneCdrug interactions. The portion of genetic backgrounds is shown for which compounds reveal at least one significant conversation (FDR? ?0.01). Quantity of interactions per genetic backgrounds. Different genotypes reveal varying numbers of interactions across the 20 phenotypic features investigated (FDR? ?0.01). Next, we calculated conversation coefficients (Horn wt cells, whereas we did not observe significant interactions affecting cell number, that is, cell proliferation and viability (FDR ?0.01,.