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Title: Temporospatial Dynamics of the Epithelial-Mesenchymal Transition in Cancer Metastasis
Authors: Liu, Daniel
Advisors: Kang, Yibin
Department: Molecular Biology
Certificate Program: Applications of Computing Program
Global Health and Health Policy Program
Quantitative and Computational Biology Program
Class Year: 2018
Abstract: The epithelial to mesenchymal transition (EMT) is a cellular transdifferentiating process that endows epithelial cells with migratory and invasive capabilities. EMT is essential for development and homeostasis, but is also co-opted by cancer cells to facilitate cancer progression and metastasis. Extensive previous work has uncovered the major signals and transcription factors (TFs) inducing EMT; however, little is known about its intrinsic temporospatial dynamics. Here, we derive and experimentally validate a mathematical model of TGF-β signaling, which induces EMT by repressing the epithelial hallmark E-cadherin. The model reveals that TGF-β-induced EMT undergoes a non-linear response known as hysteresis, owing to the double-negative feedback loop between Zeb/miR-200s. Using CRISPR/Cas9-mediated genome editing, we were able to disrupt the Zeb/miR-200s feedback loop and eliminate hysteresis. Using these hysteretic and non-hysteretic cell lines, we show that hysteresis (1) facilitates a quick response in response to TGF-β, (2) endows cells with molecular memory, allowing for complete EMT response even after very short pulses of TGF-β, (3) sustains the EMT state long after withdrawal of TGF-β, and (4) spreads the EMT signal to neighboring cells via paracrine signaling. Most remarkably, cells following hysteretic EMT gained enhanced lung metastatic colonization, while those following non-hysteretic EMT did not. Accordingly, only cells undergoing hysteretic EMT differentially expressed subsets of stem cell and extracellular matrix genes with clinical prognosis value. Overall, these findings illustrate that the dynamics of EMT convey distinct biological impacts.
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Molecular Biology, 1954-2023
Global Health and Health Policy Program, 2017-2023

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