多发性骨髓瘤
基因型
业务
计算机科学
癌症研究
生物
遗传学
免疫学
基因
作者
Corynn Kasap,Adila Izgutdina,Bonell Patiño-Escobar,Amrik S. Kang,Nikhil Chilakapati,Naomi Akagi,Haley Johnson,Tasfia Rashid,Juwita Werner,Abhilash Barpanda,Huimin Geng,Yu-Hsiu T. Lin,Sham Rampersaud,Daniel Gil-Alós,Amin Sobh,Daphné Dupéré-Richer,Gianina Wicaksono,K.M. Kawehi Kelii,R. Dalal,Emilio Ramos
标识
DOI:10.1101/2024.02.24.581875
摘要
Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in urgent need of additional therapeutic options. Here, we identify CD70, widely recognized as a favorable immunotherapy target in other cancers, as a specifically upregulated cell surface antigen in high risk myeloma tumors. We use a structure-guided design to define a CD27-based anti-CD70 CAR-T design that outperforms all tested scFv-based CARs, leading to >80-fold improved CAR-T expansion in vivo. Epigenetic analysis via machine learning predicts key transcription factors and transcriptional networks driving CD70 upregulation in high risk myeloma. Dual-targeting CAR-Ts against either CD70 or BCMA demonstrate a potential strategy to avoid antigen escape-mediated resistance. Together, these findings support the promise of targeting CD70 with optimized CAR-Ts in myeloma as well as future clinical translation of this approach.
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