Dynamical systems biology approach to identify mediators of the epithelial-hybrid-mesenchymal spectrum
Material type:
- 616.994 SUB
Item type | Current library | Call number | URL | Status | Date due | Barcode | |
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JRD Tata Memorial Library | 616.994 SUB (Browse shelf(Opens below)) | Link to resource | Not For Loan | ET00224 |
includes bibliographical references and index
PhD; 2023; Centre for BioSystems Science and Engineering
Cancer metastasis – the spread of cancer cells from one organ to another – remains the major
cause of cancer-related deaths. A hallmark of metastasizing cells is their ability to adapt
quickly and reversibly to their dynamic microenvironment. This ability to switch among different
cell-states is called as phenotypic plasticity. A well-studied example of phenotypic plasticity in
carcinomas (cancers originating in epithelial tissues) is Epithelial-Mesenchymal Transition
(EMT) and its reverse Mesenchymal-Epithelial Transition (MET). EMT is characterized by
cancer cells losing their cell-cell adhesion and gaining migration and invasion traits, enabling
cancer cell dissemination. During MET, the disseminating cells, upon reaching distant organs,
regain the epithelial traits, facilitating metastatic colonization. Initially, EMT and MET were
considered as binary processes, but recent studies have discovered that cancer cells can
acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes that can be highly
aggressive and are associated with worse patient outcomes. While the molecular drivers of
EMT have been extensively investigated, the molecular factors that can stabilize hybrid E/M
phenotypes or drive MET are ill understood.
In my work, I have used dynamical systems approach to identify two transcription factors that
can stabilize hybrid E/M phenotype(s) – NFATc and SLUG – and two transcription factors that
can drive MET – ELF3 and KLF4. Our computational model predictions are validated by
extensive transcriptomic data analysis at both bulk and single-cell analysis levels. Further,
modeling results collected over an ensemble of kinetic parameters – using a tool called
RACIPE (RAndom CIrcuit PErturbation) – suggest that the role of these players in stabilizing
hybrid E/M phenotype or driving MET emerges from underlying network topology rather than
specific parameter values.
First, I incorporated experimentally reported interactions of NFATc with key molecules
influencing EMT dynamics, such as E-cadherin, SNAIL and ZEB, in a mechanism-based
model. Bifurcation analysis reveals that NFATc can prevent the progression towards a full
EMT and expand the parameter region for the existence of hybrid E/M phenotype. Further,
RACIPE analysis demonstrated the role of NFATc in augmenting the co-existence of epithelial,
hybrid E/M and mesenchymal phenotypes. Knockdown of NFATc in H1975 cells (lung cancer
cells exhibiting a stable hybrid E/M state) drove them towards a complete EMT, thus validating
the role of NFATc as a stabilizer of hybrid E/M state. Next, via dynamical modeling and
transcriptomic data analysis, I examined the role of EMT-inducing transcription factor SLUG
in mediating EMT/MET. I found that SLUG, unlike its family member SNAIL, drove a weak EMT and stabilized cells in hybrid E/M state. Overexpression of SLUG led to an enrichment
of hybrid E/M state, highlighting its role in maintaining this phenotype.
Second, I investigated the role of KLF4 and ELF3 through expanding abovementioned
regulatory networks governing EMT/MET. Mechanism-based modeling suggested that both
KLF4 and ELF3 can delay the onset of EMT, and their overexpression can drive MET, with
ELF3 being a relatively more potent inducer. In both cell lines and primary tumors, KLF4 and
ELF3 correlate negatively with EMT-inducing factors, and their expression is inhibited during
EMT. Thus, both ELF3 and KLF4 are associated with an epithelial phenotype and are putative
drivers of MET.
Finally, I observed that while high levels of NFATc, SLUG, KLF4 and ELF3 associated with
worse patient survival in some solid tumors, the trends were tissue specific. These
observations reveal the complex association of EMT/MET with patient survival.
Overall, my research showcases how a dynamical systems biology approach can help identify
potent regulators implicated in phenotypic plasticity, thus suggesting putative therapeutic
targets to be considered for curtailing metastasis.
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