Title |
Early transduction produces highly functional chimeric antigen receptor-modified virus-specific T-cells with central memory markers: a Production Assistant for Cell Therapy (PACT) translational application
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Published in |
Journal for Immunotherapy of Cancer, February 2015
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DOI | 10.1186/s40425-015-0049-1 |
Pubmed ID | |
Authors |
Jiali Sun, Leslie E Huye, Natalia Lapteva, Maksim Mamonkin, Manasa Hiregange, Brandon Ballard, Olga Dakhova, Darshana Raghavan, April G Durett, Serena K Perna, Bilal Omer, Lisa A Rollins, Ann M Leen, Juan F Vera, Gianpietro Dotti, Adrian P Gee, Malcolm K Brenner, Douglas G Myers, Cliona M Rooney |
Abstract |
Virus-specific T-cells (VSTs) proliferate exponentially after adoptive transfer into hematopoietic stem cell transplant (HSCT) recipients, eliminate virus infections, then persist and provide long-term protection from viral disease. If VSTs behaved similarly when modified with tumor-specific chimeric antigen receptors (CARs), they should have potent anti-tumor activity. This theory was evaluated by Cruz et al. in a previous clinical trial with CD19.CAR-modified VSTs, but there was little apparent expansion of these cells in patients. In that study, VSTs were gene-modified on day 19 of culture and we hypothesized that by this time, sufficient T-cell differentiation may have occurred to limit the subsequent proliferative capacity of the transduced T-cells. To facilitate the clinical testing of this hypothesis in a project supported by the NHLBI-PACT mechanism, we developed and optimized a good manufacturing practices (GMP) compliant method for the early transduction of VSTs directed to Epstein-Barr virus (EBV), Adenovirus (AdV) and cytomegalovirus (CMV) using a CAR directed to the tumor-associated antigen disialoganglioside (GD2). |
X Demographics
Geographical breakdown
Country | Count | As % |
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Russia | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Unknown | 91 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 19 | 21% |
Student > Ph. D. Student | 13 | 14% |
Student > Bachelor | 9 | 10% |
Student > Master | 8 | 9% |
Student > Doctoral Student | 5 | 5% |
Other | 18 | 20% |
Unknown | 20 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 25 | 27% |
Agricultural and Biological Sciences | 20 | 22% |
Immunology and Microbiology | 11 | 12% |
Biochemistry, Genetics and Molecular Biology | 7 | 8% |
Engineering | 3 | 3% |
Other | 4 | 4% |
Unknown | 22 | 24% |