Author : Vibhuti Agrawal
Publisher :
ISBN 13 :
Total Pages : 181 pages
Book Rating : 4.:/5 (11 download)
Book Synopsis Dissecting the Molecular Mechanisms of Therapeutic Resistance in Cancer by : Vibhuti Agrawal
Download or read book Dissecting the Molecular Mechanisms of Therapeutic Resistance in Cancer written by Vibhuti Agrawal and published by . This book was released on 2017 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Therapeutic resistance continues to be a persistent challenge in medical oncology. In clinical settings, resistance can occur at the beginning of treatment, or may be acquired after an initial clinical response to the therapy. Several mechanisms of drug resistance have been described in cancer, including alterations in the drug transport and metabolism process, mutations in drug-target, activation of bypass signaling pathways, inhibition of cell-death pathways, and induction of an epithelial to mesenchymal transition (EMT) in response to cytotoxic or targeted therapies. In this study, I have investigated the molecular mechanisms underlying ZEB 1-induced EMT and established a new computational framework that uses inter-animal heterogeneity to identify drivers responsible for variable phenotypic responses across different animals. EMT describes a cell-state switching process wherein epithelial cells lose their tight cell-cell junction contacts, and acquire the ability to migrate and invade the surrounding stroma to enter into blood circulation. Given the widespread role of EMT in drug resistance, it is imperative to identify therapeutic strategies to inhibit this transition. To identify druggable targets to block EMT progression, and therefore overcome EMT-mediated therapeutic resistance, I studied the effects of ZEB 1 expression on cellular signaling networks. By quantifying changes in tyrosine phosphorylation at different time points during ZEB 1-induced EMT, I found that Src family kinases (SFKs) were activated within 24 hours of ZEB 1 expression. Inhibition of SFKs blocked not only ZEB 1-induced EMT, but also EMT initiated by TGFp- and EGF signaling pathways in both breast and NSCLC cell-lines. SFK inhibition also prevented EGFR inhibitor-induced EMT and drug resistance in NSCLC cells both in vitro and in vivo. Mechanistically, SFK activation stabilized ZEBI by promoting ERK1/2-mediated phosphorylation on three serine residues, S583, S646, and S679. Consequently, MEK inhibition phenocopied the effects of blocking SFK activity with regards to decreasing stability of ZEB 1 and inhibiting ZEB 1-induced EMT. These results provide a new therapeutic application of SFK inhibitors as a potential anti-EMT therapy, to enhance the susceptibility of cancer cells to chemo- or targeted therapies. In the second part of this thesis, I have described a computational framework that leverages inter-animal heterogeneity to identify molecular mechanisms underlying variable phenotypic responses across different animals. Substantial inter-animal variability in phenotypes within the same treatment group, limits our ability to draw conclusions or gain meaningful insights about a biological process by simply averaging the data. To identify molecular drivers for heterogeneous phenotypic responses, I have established a method where each animal is considered as an individual entity whose phenotypic response is dependent on the state of its underlying signaling networks. As a proof of concept, I have used this method to successfully predict the resistance mechanisms of CDK4/6 inhibitor, palbocilib in two GBM PDX and one MPNST PDX models. The GBM6 model activated EGFR signaling upon treatment with palbociclib whereas the GBM22 and MPNST3 models activated SFKs and PDGFRa signaling in resistant tumors. Across all three PDX tumor models, treatment with combination therapies, consisting of palbociclib and an inhibitor targeting the activated bypass signaling pathway, substantially prolonged survival of mice. Thus, these results suggest that inter-animal variability can be used as a tool to predict drivers for a specific phenotypic response across different treatment conditions.
