Browsing by Author "Somarelli, Jason A."

Now showing 1 - 4 of 4
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    EMT and MET: necessary or permissive for metastasis?
    (Wiley, 2017) Jolly, Mohit Kumar; Ware, Kathryn E.; Gilja, Shivee; Somarelli, Jason A.; Levine, Herbert; Bioengineering; Center for Theoretical Biological Physics
    Epithelial-to-mesenchymal transition (EMT) and its reverse mesenchymal-to-epithelial transition (MET) have been suggested to play crucial roles in metastatic dissemination of carcinomas. These phenotypic transitions between states are not binary. Instead, carcinoma cells often exhibit a spectrum of epithelial/mesenchymal phenotype(s). While epithelial/mesenchymal plasticity has been observed preclinically and clinically, whether any of these phenotypic transitions are indispensable for metastatic outgrowth remains an unanswered question. Here, we focus on epithelial/mesenchymal plasticity in metastatic dissemination and propose alternative mechanisms for successful dissemination and metastases beyond the traditional EMT/MET view. We highlight multiple hypotheses that can help reconcile conflicting observations, and outline the next set of key questions that can offer valuable insights into mechanisms of metastasis in multiple tumor models.
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    Epithelial/mesenchymal plasticity: how have quantitative mathematical models helped improve our understanding?
    (Wiley, 2017) Jolly, Mohit Kumar; Tripathi, Satyendra C.; Somarelli, Jason A.; Hanash, Samir M.; Levine, Herbert; Bioengineering; Center for Theoretical Biological Physics
    Phenotypic plasticity, the ability of cells to reversibly alter their phenotypes in response to signals, presents a significant clinical challenge to treating solid tumors. Tumor cells utilize phenotypic plasticity to evade therapies, metastasize, and colonize distant organs. As a result, phenotypic plasticity can accelerate tumor progression. A well-studied example of phenotypic plasticity is the bidirectional conversions among epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) phenotype(s). These conversions can alter a repertoire of cellular traits associated with multiple hallmarks of cancer, such as metabolism, immune evasion, invasion, and metastasis. To tackle the complexity and heterogeneity of these transitions, mathematical models have been developed that seek to capture the experimentally verified molecular mechanisms and act as ‘hypothesis-generating machines’. Here, we discuss how these quantitative mathematical models have helped us explain existing experimental data, guided further experiments, and provided an improved conceptual framework for understanding how multiple intracellular and extracellular signals can drive E/M plasticity at both the single-cell and population levels. We also discuss the implications of this plasticity in driving multiple aggressive facets of tumor progression.
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    Induction of Mesenchymal-Epithelial Transitions in Sarcoma Cells
    (JoVE, 2017) Ware, Kathryn E.; Gilja, Shivee; Xu, Shenghan; Shetler, Samantha; Jolly, Mohit K.; Wang, Xueyang; Dewitt, Suzanne Bartholf; Hish, Alexander J.; Jordan, Sarah; Eward, William; Levine, Herbert; Armstrong, Andrew J.; Somarelli, Jason A.; Bioengineering
    We present here a cell culture method for inducing mesenchymal-epithelial transitions (MET) in sarcoma cells based on combined ectopic expression of microRNA-200 family members and grainyhead-like 2 (GRHL2). This method is suitable for better understanding the biological impact of phenotypic plasticity on cancer aggressiveness and treatments.
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    Survival outcomes in cancer patients predicted by a partial EMT gene expression scoring metric
    (American Association for Cancer Research, 2017) George, Jason T.; Jolly, Mohit Kumar; Xu, Shengnan; Somarelli, Jason A.; Levine, Herbert; Bioengineering; Physics and Astronomy
    with a posterior probability from 0.80 to 1.00 contained more than 50% neoplasia 99% (84/85) of the time. This study demonstrates a proof-of-concept of how noninvasive optical imaging can be used as a tool to study expression levels of multiple biomarkers and their heterogeneity across a large mucosal surface and how biomarker characteristics