Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNA), has been impeded by lack of time series single cell sampling of polyclonal populations and temporal statistical models 1 – 7 . Here, we generated 42,000 genomes from multi-year time series single cell whole genome sequencing (scWGS) of breast epithelium and primary triple negative breast cancer (TNBC) patient derived xenografts (PDX), revealing the nature of CNA defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model 8 , 9 to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TP53 mutant TNBC PDX models, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones emerging from low fitness phylogenetic lineages in the untreated setting. Conversely, high fitness clones from treatment naive controls were eradicated, signaling an inversion of the fitness landscape. Finally, upon release of drug selective pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Taken together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.