肿瘤细胞治疗研究
英文原题：AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.
AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.
嵌合抗原受体（CAR）T 细胞已在血液系统恶性肿瘤中显示出治愈潜力，并在实体瘤和非恶性疾病中展现出日益提高的疗效。
嵌合抗原受体（CAR）T细胞已在血液系统肿瘤中显示出治愈潜力，并在实体瘤和非恶性疾病中展现出不断提高的疗效。然而，靶点鉴定仍是主要瓶颈。我们开发了一种由人工智能（AI）驱动的CAR T细胞靶点发现方法，整合人类皮肤癌及健康组织的单细胞RNA测序数据。我们利用公共数据集进一步筛选候选靶点，以优化其肿瘤表达比例、组织特异性和临床可行性。随后应用大型语言模型，优先排序并提名具有治疗潜力的靶点。非转移性糖蛋白黑色素瘤蛋白B（GPNMB）是最常被提名的靶点。我们验证了其在血液系统肿瘤和实体瘤中的表达，并构建了靶向人GPNMB的CAR T细胞。该细胞在单核母细胞白血病、黑色素瘤和结直肠腺癌小鼠模型中表现出强效抗肿瘤活性。这些发现建立了可扩展的CAR T细胞靶点发现流程，并支持推进靶向GPNMB的CAR T细胞作为多癌种治疗方案。
Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-malignant diseases. However, target identification remains a major bottleneck. We developed an artificial intelligence (AI)-driven approach for CAR T cell target discovery by integrating single-cell RNA sequencing datasets from human skin cancer and healthy tissue. Candidates were refined using public datasets to optimize for tumor composition, tissue specificity, and clinical feasibility. Large language models were applied to prioritize and nominate targets with therapeutic promise. Glycoprotein non-metastatic melanoma protein B (GPNMB) was the most frequently nominated target. We validated its expression across hematologic and solid tumors. We engineered a human GPNMB-directed CAR T cell, which showed potent anti-tumor activity in mouse models of monoblastic leukemia, melanoma, and colorectal adenocarcinoma. These findings establish a scalable pipeline for CAR T cell target discovery and support the translation of GPNMB-directed CAR T cells as a multi-cancer therapeutic.
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