| Title |
An optimized bicistronic chimeric antigen receptor against GPC2 or CD276 overcomes heterogeneous expression in neuroblastoma
|
|---|---|
| Published in |
Journal of Clinical Investigation, August 2022
|
| DOI | 10.1172/jci155621 |
| Pubmed ID | |
| Authors |
MEIJIE TIAN, Adam T. Cheuk, Jun S. Wei, Abdalla Abdelmaksoud, Hsien-Chao Chou, David Milewski, Michael C. Kelly, Young K. Song, Christopher M. Dower, Nan Li, Haiying Qin, Yong Yean Kim, Jerry T. Wu, Xinyu Wen, Mehdi Benzaoui, Katherine E. Masih, Xiaolin Wu, Zhongmei Zhang, Sherif Badr, Naomi Taylor, Brad St. Croix, Mitchell Ho, Javed Khan |
| Abstract |
Chimeric antigen receptor (CAR) T-cell therapies targeting single antigens perform poorly in clinical trials for solid tumors due to heterogenous expression of tumor-associated antigens (TAAs), limited T-cell persistence and exhaustion. Here we aimed to identify optimal CARs against Glypican-2 (GPC2) or CD276 (B7-H3), which were highly but heterogeneously expressed in neuroblastoma (NB), a lethal extracranial solid tumor of childhood. First, we examined CAR T-cell expansion in the presence of target by digital droplet PCR. Next, using Pooled Competitive Optimization of CAR by CITE-seq (P-COCC), we simultaneously analyzed protein and transcriptome expression of CAR T-cells to identify high activity CARs. Finally, we performed cytotoxicity assays to identify the most effective CAR against each target and combined them into a bicistronic "OR" CAR (BiCisCAR). BiCisCAR T-cells effectively eliminated tumor cells expressing GPC2 or CD276. Furthermore, the BiCisCAR demonstrated prolonged persistence and resistance to exhaustion comparing with single antigen targeting CARs. This study illustrated that targeting multiple TAAs with BiCisCARs may overcome heterogenous expression of target antigen in solid tumors, and identified a potent clinically relevant CAR against NB. Moreover, our multimodal approach integrating competitive expansion, P-COCC, and cytotoxicity assays is an effective strategy to identify potent CARs from a pool of candidates. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 29% |
| Japan | 1 | 6% |
| Italy | 1 | 6% |
| Russia | 1 | 6% |
| China | 1 | 6% |
| Unknown | 8 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 88% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
| Scientists | 1 | 6% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 13% |
| Student > Bachelor | 5 | 9% |
| Student > Ph. D. Student | 4 | 7% |
| Other | 3 | 5% |
| Student > Master | 3 | 5% |
| Other | 6 | 11% |
| Unknown | 27 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 22% |
| Medicine and Dentistry | 5 | 9% |
| Immunology and Microbiology | 4 | 7% |
| Agricultural and Biological Sciences | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 30 | 55% |