肿瘤细胞治疗研究
英文原题：CAR T targets: AI takes the wheel.
识别安全有效的靶点仍是 CAR T 细胞疗法的主要瓶颈。
寻找安全且有效的靶点仍是CAR-T细胞疗法发展的主要瓶颈。本期《Cell》中，Baker及其同事开发了一种大型语言模型辅助评分框架，以简化靶点筛选流程，并据此鉴定和验证糖蛋白非转移性黑色素瘤蛋白B（GPNMB）是可用于黑色素瘤、白血病及结直肠癌的候选嵌合抗原受体（CAR）T细胞靶点。
Identifying safe and effective targets remains a major bottleneck for CAR T cell therapies. In this issue of Cell, Baker and colleagues developed a large language model (LLM)-assisted scoring framework to streamline this process and as a result identified and validated glycoprotein non-metastatic melanoma protein B (GPNMB) as a candidate chimeric antigen receptor (CAR) T target across melanoma, leukemia, and colorectal cancer.
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