26The evolution of therapeutic resistance is a major cause of death for patients with solid 27 tumors. The development of therapy resistance is shaped by the ecological dynamics 28 within the tumor microenvironment and the selective pressure induced by the host 29 immune system. These ecological and selective forces often lead to evolutionary 30 convergence on one or more pathways or hallmarks that drive progression. These 31 hallmarks are, in turn, intimately linked to each other through gene expression 32 networks. Thus, a deeper understanding of the evolutionary convergences that occur at 33 the gene expression level could reveal vulnerabilities that could be targeted to treat 34 therapy-resistant cancer. To this end, we used a combination of phylogenetic clustering, 35 systems biology analyses, and wet-bench molecular experimentation to identify 36 convergences in gene expression data onto common signaling pathways. We applied 37 these methods to derive new insights about the networks at play during TGF-β-38 mediated epithelial-mesenchymal transition in a lung cancer model system. 39Phylogenetics analyses of gene expression data from TGF-β treated cells revealed 40 evolutionary convergence of cells toward amine-metabolic pathways and autophagy 41 during TGF-β treatment. Using high-throughput drug screens, we found that 42 knockdown of the autophagy regulatory, ATG16L1, re-sensitized lung cancer cells to 43 cancer therapies following TGF-β-induced resistance, implicating autophagy as a TGF-β-44 mediated chemoresistance mechanism. Analysis of publicly-available clinical data sets 45 validated the adverse prognostic importance of ATG16L expression in multiple cancer 46 types including kidney, lung, and colon cancer patients. These analyses reveal the 47 usefulness of combining evolutionary and systems biology methods with experimental 48 validation to illuminate new therapeutic vulnerabilities. 49 50