An integrative systems biology and experimental approach identifies convergence of epithelial plasticity, metabolism, and autophagy to promote chemoresistance

Abstract

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

Hybrid E/M Phenotype(s) and Stemness: A Mechanistic Connection Embedded in Network Topology

“…Mechanism-based models of individual axes of plasticity are the building blocks required to answer this question from a dynamical systems perspective. There has been increasing interest in dynamical modeling of EMP [ 82 , 83 , 84 , 85 , 86 ]; similar efforts to model related aspects of EMP, such as metabolic reprogramming [ 87 ], autophagy [ 88 , 89 ], therapy resistance [ 90 , 91 ], and immune evasion [ 92 ], are being attempted too. Coupling these modules to decode the interconnections among different axes of plasticity can help unravel the survival strategies of metastasis-initiating cells and eventually contribute to designing new clinical strategies.…”

Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT

“…The dynamics of EMT has been studied much more in detail as compared to that of MET [51][52][53][54][55][56]; therefore, it is not surprising that irreversible EMT has been reported more frequently. The degree of reversibility of EMT has been proposed to be largely a function of the timescale of EMT induction and corresponding epigenetic changes.…”

A Comparative Oncology Drug Discovery Pipeline to Identify and Validate New Treatments for Osteosarcoma

“…All human (143B, MG63, SAOS, U2OS, 17-3X) and canine (Abrams, Moresco, D17, D418) osteosarcoma cell lines were cultured in DMEM + 10% FBS + 1% Penicillin/Streptomycin. The NIH Approved Oncology set (119 compounds) and Selleck Bioactives collection (2100 compounds) were screened in the Duke Functional Genomics Shared Resource as described previously [ 21 , 50 ]. Briefly, compounds were first stamped in triplicate into 384 well plates at a final concentration of 1 μM using an Echo Acoustic Dispenser (Labcyte, Indianapolis, IN, USA).…”