Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 147-168). / Cell-cell communication between malignant, immune, and stromal cells influences many aspects of in vivo tumor biology, including tumorigenesis, tumor progression, and therapeutic resistance. As a result, targeting receptor-ligand interactions, for instance with immune check-point inhibitors, can provide significant benefit for patients. However, our knowledge of this complex network of cell-cell interactions in a tumor microenvironment is still incomplete, and there is a need for systematic approaches to study cell-cell communication. This thesis presents computational approaches for characterizing cell-cell communication networks in three different experimental studies. In the first study, we modeled metastatic triple negative breast cancer in the liver using a microphysiological system and identified inflammatory cytokines secreted by the microenvironment that result in the proliferation of dormant metastases. In the second study, we used single-cell RNA sequencing (scRNA-seq) to quantify receptor-ligand interactions in six syngeneic mouse tumor models. To identify specific receptor-ligand interactions that predict tumor growth rate and immune infiltration, we used receptor-ligand interactions as features in regression models. For the third study, we extended our scRNA-seq approach to include inferences of single-cell signaling pathway and transcription factor activity. We then identified protein-protein interaction networks that connect extra-cellular receptor-ligand interactions to intra-cellular signal transduction pathways. Using this approach, we compared inflammatory versus genetic models of colorectal cancer and identified cancer-associated-fibroblasts as drivers of a partial epithelial-to-mesenchymal transition in tumor cells via MAPK1 and MAPK14 signaling. Overall, the methods developed in this thesis provide a foundational computational framework for constructing "multi-scale" models of communication networks in multi-cellular tissues. / by Manu Prajapati Kumar. / Ph. D. / Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/123063 |
| Date | January 2019 |
| Creators | Kumar, Manu Prajapati. |
| Contributors | Douglas A. Lauffenburger., Massachusetts Institute of Technology. Department of Biological Engineering., Massachusetts Institute of Technology. Department of Biological Engineering |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 168 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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