Summary
We developed PHENO-DEX, an experimental and machine-learning framework designed to characterize cancer cell response spectrums using dynamic molecular phenotypes. PHENO-DEX is specifically applied to dexamethasone (Dex) treatment, a widely used glucocorticoid receptor (GR) agonist that influences gene transcription. While Dex is commonly used in breast cancer treatment, patient responses vary, underscoring the need for predictive models. PHENO-DEX employs two core algorithms: (1) DSFMix (Anchang et al. 2022) which is a tree-based model that identifies key regulators and maps responsive and non
