韩国科学技术院Jung Kyoon Choi、Jung Kyoon Choi等合作近期取得重要工作进展。他们报道了使用逻辑门的CAR开关组合靶抗原的单细胞映射。相关论文2023年2月16日在线发表于《自然—生物技术》杂志上。

据介绍，鉴定区分癌症细胞和正常周围组织细胞的最佳靶抗原仍是嵌合抗原受体（CAR）细胞治疗肿瘤内异质性肿瘤的关键挑战。

研究人员通过构建单细胞表达图谱，将组织复杂性分解到单个细胞的水平，该图谱整合了来自412个肿瘤和12个正常器官的约140万肿瘤、肿瘤浸润正常细胞和参考正常细胞。他们使用随机森林和卷积神经网络的两步筛选方法来选择最有助于区分单个恶性细胞和正常细胞的基因对。基于单个细胞中配对基因的组合表达模式，评估and、OR和NOT逻辑门的肿瘤覆盖率和特异性。

总之，单细胞转录组偶联表位分析验证了卵巢癌症和结直肠癌中确定的AND、OR和NOT开关靶点。

附：英文原文

Title: Single-cell mapping of combinatorial target antigens for CAR switches using logic gates

Author: Kwon, Joonha, Kang, Junho, Jo, Areum, Seo, Kayoung, An, Dohyeon, Baykan, Mert Yakup, Lee, Jun Hyeong, Kim, Nayoung, Eum, Hye Hyeon, Hwang, Sohyun, Lee, Ji Min, Park, Woong-Yang, An, Hee Jung, Lee, Hae-Ock, Park, Jong-Eun, Choi, Jung Kyoon

Issue&Volume: 2023-02-16

Abstract: Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

DOI: 10.1038/s41587-023-01686-y

Source: https://www.nature.com/articles/s41587-023-01686-y