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dc.contributor.advisorScott Manalis.en_US
dc.contributor.authorHamza, Bashar,Ph. D.(Bashar M.)Massachusetts Institute of Technology.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2020-11-06T21:08:00Z
dc.date.available2020-11-06T21:08:00Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/128399
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2020en_US
dc.descriptionCataloged from student-submitted PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 109-119).en_US
dc.description.abstractMetastasis is a complex, multi-step process that is responsible for over 90% of cancer-related deaths. Circulating tumor cells (CTCs) that are shed from primary tumors represent the disseminating "seeds" that give rise to distant malignant growths. Despite their importance to metastasis, understanding of their role has been hindered by the extreme difficulty of characterizing CTC populations over time and linking them to metastases that occur during natural tumor progression. The use of in vivo mouse models of cancer for studying metastasis has been crucial for discovering effective new cancer biomarkers and therapies. This thesis outlines the development of a new platform that enables longitudinal and dynamic CTC studies in mouse models of cancer. The platform is designed to help better understand how changes in CTCs may reflect the evolution of their tumors of origin over time.en_US
dc.description.abstractIt is composed of a microfluidic, cell-sorting chip connected serially to an un-anesthetized mouse via an implanted arteriovenous shunt. Pneumatically-controlled microfluidic valves capture CTCs as they flow through the chip, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of this platform, we profiled CTCs isolated longitudinally from animals over several days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq). We showed that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. Furthermore, the direct access to a mouse's circulatory system in real time allowed us to devise a new method for measuring the circulatory dynamics and physical properties of CTCs in mice.en_US
dc.description.abstractDirect measurements of the main parameters that govern CTC levels in blood - mainly the intravasation rate and the half-life time in the circulation - were demonstrated. Observing how such parameters change during tumor development or in response to therapy may help shed light on the dynamics of the most tumorigenic CTCs. Finally, in collaboration with several laboratories at MIT and elsewhere, further validation of this platform is demonstrated by carrying out longitudinal studies of single CTCs and rare, circulating, tumor-experienced immune cells collected from different mouse models of cancer. Information gained from these studies will help dissect the potential mechanisms of resistance to therapy (e.g. immunotherapy) and identify new "druggable" candidate cells.en_US
dc.description.statementofresponsibilityby Bashar Hamza.en_US
dc.format.extent131 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleAn optofluidic platform for longitudinal circulating tumor cell studies in mouse models of canceren_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1203059636en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2020-11-06T21:07:59Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentEECSen_US


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