The hybrid epithelial/mesenchymal phenotype and its implications in cancer metastasis
| dc.contributor.advisor | Levine, Herbert | en_US |
| dc.creator | Jolly, Mohit Kumar | en_US |
| dc.date.accessioned | 2017-08-01T15:12:22Z | en_US |
| dc.date.available | 2017-08-01T15:12:22Z | en_US |
| dc.date.created | 2016-12 | en_US |
| dc.date.issued | 2016-11-17 | en_US |
| dc.date.submitted | December 2016 | en_US |
| dc.date.updated | 2017-08-01T15:12:22Z | en_US |
| dc.description.abstract | More than 90% of cancer-related deaths occur because cancer cells metastasize, i.e. invade the surrounding tissue, travel throughout the body, and form tumors at distant organs. Metastasis is often fueled by Epithelial-to-Mesenchymal Transition (EMT) that enables cells to migrate and invade, and its reverse Mesenchymal-to-Epithelial Transition (MET) that facilitates cells to shed migration and regain adhesion to colonize other organs. While undergoing EMT or MET, cells can adopt a hybrid epithelial/mesenchymal (E/M) phenotype through which they can both adhere and migrate, leading to collective migration as clusters of Circulating Tumor Cells (CTCs) that can be apoptosis-resistant and can initiate 50 times more tumors as compared to individually migrating CTCs. However, the hybrid E/M remains poorly characterized and has been tacitly assumed to be ‘metastable’ or transient. This study, through integrating mathematical modeling with wet-lab experiments, suggests that the hybrid E/M phenotype can be quite stable and its stability can aggravate tumor progression. First, we model the core regulatory network underlying EMT/MET – interconnected feedback loops among miR-34, miR-200, ZEB, SNAIL families – to predict that it can act as a ‘three-way’ switch enabling three phenotypes – epithelial (high miR-200, low ZEB), mesenchymal (low miR-200, high ZEB) and hybrid E/M (medium miR-200, medium ZEB). Second, GRHL2 and OVOL1/2 are predicted to stabilize a hybrid E/M phenotype and then confirmed experimentally in H1975 lung cancer cells that display a stable hybrid E/M phenotype. Third, modeling the interconnections of core EMT network with that regulating tumor-initiation potential (LIN28/let-7) predicts that a hybrid E/M, but not necessarily a fully mesenchymal, phenotype associates with higher tumor-initiation potential. Finally, integrating the core EMT network with intercellular Notch signaling, we predict that Notch-Jagged signaling can give rise to clusters of cells in a hybrid E/M phenotype. This prediction corroborates with our experimental observations that the drug-resistant tumor-initiating cells display elevated levels of Notch-Jagged signaling, reflecting the metastatic potential of hybrid E/M cells that can form clusters of CTCs. These results strongly argue that cancer cells in a hybrid E/M phenotype can be the key ‘bad actors’ of metastasis and identify novel targets – OVOL1/2, GRHL2 and JAG1 – to curb metastatic load. | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.citation | Jolly, Mohit Kumar. "The hybrid epithelial/mesenchymal phenotype and its implications in cancer metastasis." (2016) Diss., Rice University. <a href="https://hdl.handle.net/1911/95959">https://hdl.handle.net/1911/95959</a>. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/95959 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | en_US |
| dc.subject | Cancer metastasis | en_US |
| dc.subject | Epithelial-mesenchymal transition | en_US |
| dc.subject | Multistability | en_US |
| dc.subject | Systems Biology | en_US |
| dc.subject | Cell-fate decisons | en_US |
| dc.subject | Hybrid epithelial/mesenchymal phenotype | en_US |
| dc.title | The hybrid epithelial/mesenchymal phenotype and its implications in cancer metastasis | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Bioengineering | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy | en_US |
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