Next generation cell therapies : from genome to receptor to vector engineering
Abstract/Contents
- Abstract
- The next generation of cell therapies will be leveraged to target solid tumors, clear viral infections, repair wounds, overcome autoimmunity, reverse aging, and beyond. To achieve this goal, diverse immune cell types need to respond to clinician- or disease-derived inputs and generate novel therapeutic responses. However, multiple challenges exist that inhibit the development of these next generation cell therapies including 1) primary immune cells silencing delivered transgenes, 2) engineered receptors lacking response to soluble inputs or activation of therapeutic pathways, and 3) clinically approved viral vectors that are incapable of engineering diverse immune cell types. To overcome these challenges, we expanded the cell therapy toolbox by developing a suite of technologies for genome, receptor, and vector engineering. Leveraging genome engineering, we develop a CRISPR-based virus-like particle (VLP) method to knockin very large genetic payloads into essential genomic loci. This methodology stabilizes expression of large and difficult to express transgenes in primary human T cells over a long period. With receptor engineering, we generate a chimeric transmembrane protein that oligomerizes in response to a small molecule drug or protein antigen to activate Toll-like Receptor (TLR) signaling. The receptor controllably increases the cytotoxicity of natural killer (NK) cell to enhance their anti-cancer capacity. With vector engineering, we reprogram lentiviruses to target specific cell types quickly and easily. This is leveraged to engineer cells that normally cannot be engineered by lentiviruses like NK cells or selectively engineer cell subtypes in a mixture. Together, these technologies create a new foundation for generating cell therapies that move beyond T cells targeting blood cancers and maximize the therapeutic benefit of this new drug class.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Chavez, Michael Gregory |
|---|---|
| Degree supervisor | Qi, Lei, (Professor of Bioengineering) |
| Thesis advisor | Qi, Lei, (Professor of Bioengineering) |
| Thesis advisor | Covert, Markus |
| Thesis advisor | Weinacht, Katja |
| Degree committee member | Covert, Markus |
| Degree committee member | Weinacht, Katja |
| Associated with | Stanford University, Department of Bioengineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Michael Chavez. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/tj404mr6597 |
Access conditions
- Copyright
- © 2022 by Michael Gregory Chavez
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
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