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020 ▼a 9781085651547
035 ▼a (MiAaPQ)AAI13896178
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 614
1001 ▼a Williams, Jasper Zee.
24510 ▼a Engineering T Cells with Diverse Mechanisms for Improved Tumor Recognition Precision.
260 ▼a [S.l.]: ▼b University of California, San Francisco., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 198 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 ▼a Advisor: Szoka, Francis C.
5021 ▼a Thesis (Ph.D.)--University of California, San Francisco, 2019.
506 ▼a This item must not be sold to any third party vendors.
506 ▼a This item must not be added to any third party search indexes.
520 ▼a Engineered T cells are proven cancer therapeutics capable of executing potent antigen-dependent cell killing, and have gained FDA-approval after unprecedented results against certain blood cancers. However, successful treatment of solid tumors has been limited in large part by the lack of targetable antigens that are not also expressed in healthy tissues, as exhibited by ON-target OFF-tumor cross-reactive fatal toxicities seen in various human trials. An advantage of cell-based therapies is that cells can "compute" and execute more sophisticated programs than traditional drugs. Combinatorial antigen recognition has recently been introduced to overcome ON-target OFF-tumor toxicity limitations associated with traditional single antigen-targeted T cell therapies. This dissertation focuses on developing T cell engineering and biomaterials toolkits to expand the capabilities of combinatorial antigen-sensing T cell therapies. First presented is a set of approaches that use synNotch receptors and other synthetic receptors to program T cells with a diverse array of novel combinatorial antigen sensing circuits. It is shown that these Boolean logic-gated synNotch T cells can be engineered to sense both extracellular and intracellular antigens, target up to 3 antigens, integrate positive and negative regulation, and incorporate bispecific receptors. These abilities could enable engineering therapeutic T cells with the ability to target truly tumor-specific antigen combination signatures identified via bioinformatic analysis of antigen expression in cancer versus healthy cells. Also presented is a system to engineer T cells to recognize an orthogonal cue on biocompatible particles and incorporate this detection into combinatorial antigen-sensing circuits to specifically kill antigen positive tumor cells only in the presence of the particles. Using particles to control therapeutic cell activity in the body has the potential to enhance safety by enabling dynamic, local user-control of engineered cells during treatment. Together, the technologies presented here facilitate the development of engineered T cells to safely target a broader range of cancers. The toolkits developed here can be used to engineer T cell therapies to target cancer cells with significantly improved precision by taking advantage of our modern capabilities in cancer informatics, cell engineering, and biomaterials.
590 ▼a School code: 0034.
650 4 ▼a Pharmaceutical sciences.
650 4 ▼a Physiology.
650 4 ▼a Medicine.
650 4 ▼a Histology.
650 4 ▼a Epidemiology.
650 4 ▼a Immunology.
650 4 ▼a Public health.
650 4 ▼a Oncology.
650 4 ▼a Pathology.
650 4 ▼a Health sciences.
690 ▼a 0572
690 ▼a 0573
690 ▼a 0571
690 ▼a 0566
690 ▼a 0992
690 ▼a 0564
690 ▼a 0982
690 ▼a 0414
690 ▼a 0766
690 ▼a 0719
71020 ▼a University of California, San Francisco. ▼b Pharmaceutical Sciences and Pharmacogenomics.
7730 ▼t Dissertations Abstracts International ▼g 81-04B.
773 ▼t Dissertation Abstract International
790 ▼a 0034
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15491677 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK