Cell morphology and gene expression: tracking changes and complementarity across time and cell lines

Effective drug discovery relies on combining target knowledge with functional assays and multi-omics data to understand chemicals molecular actions. However, the relationship between cell morphology and gene expression over time and across cell lines remains unclear. To explore this, we analyzed Cell Painting and L1000 data for 106 compounds across three cell lines from osteoblast, lung, and breast tumors (U2OS, A549, and MCF7) at three time points (6h, 24h, 48h) using a 10{micro}M concentration. We found significant time and cell line effects in Cell Painting data, with less pronounced effects in transcriptomics. Using Weighted Gene Co-expression Network Analysis (WGCNA) and enrichment analysis, we identified connections between cell morphology and gene deregulation for chemicals with similar biological effects (e.g., HDAC and CDK inhibitors). These findings suggest that while Cell Painting shows distinct patterns, both technologies offer complementary insights into compound-induced cellular changes, enhancing drug discovery and chemical risk assessment.