Testa Stefano, Pal Aastha, Subramanian Ajay, Varma Sushama, Tang Jack Pengfei, Graham Danielle, Arfan Sara, Pan Minggui, Bui Nam Q, Ganjoo Kristen N, Dry Sarah, Huang Paul, van de Rijn Matt, Jiang Wei, Kalbasi Anusha, Moding Everett J
Department of Medicine, Stanford University, Stanford, CA, USA.
Division of Hematology and Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Genome Med. 2025 Aug 14;17(1):89. doi: 10.1186/s13073-025-01514-9.
The FDA approval of T cell receptor-engineered T cells (TCR-T) for synovial sarcoma demonstrates the potential for adoptive T cell therapies (ACTs) in solid tumors. However, the paucity of tumor-associated targets without expression in normal tissues remains a major bottleneck, especially in rare cancer subtypes.
We developed a comprehensive computational pipeline called SCAN-ACT that leverages single-cell RNA sequencing and multi-omics data from tumor and normal tissues to nominate and prioritize putative targets for both chimeric antigen receptor (CAR)- and TCR-T cells. For surface membrane targets, SCAN-ACT proposes monospecific targets and potential target pairs for bispecific Boolean logic-gated CAR T cells. For peptide-MHC targets, SCAN-ACT proposes intracellular peptides bound to a diverse set of human leukocyte antigens. Selected targets were validated experimentally by protein expression and for peptide-MHC binding.
We applied the SCAN-ACT pipeline to soft tissue sarcoma (STS), analyzing 986,749 single cells to identify and prioritize 395 monospecific CAR-T targets, 14,192 bispecific CAR-T targets, and 5020 peptide-MHC targets for TCR-T cells. Proposed targets and target pairs reflected the mesenchymal, neuronal, and hematopoietic ontogeny of STS. We further validated SCAN-ACT in glioblastoma revealing its versatility.
This work provides a robust data repository along with a web-based and user-friendly set of analysis tools to accelerate ACT development for solid tumors ( https://scanact.stanford.edu/ ).
美国食品药品监督管理局(FDA)批准用于滑膜肉瘤的T细胞受体工程化T细胞(TCR-T)证明了过继性T细胞疗法(ACT)在实体瘤治疗中的潜力。然而,缺乏在正常组织中不表达的肿瘤相关靶点仍然是一个主要瓶颈,尤其是在罕见癌症亚型中。
我们开发了一种名为SCAN-ACT的综合计算流程,该流程利用来自肿瘤和正常组织的单细胞RNA测序和多组学数据,为嵌合抗原受体(CAR)-T细胞和TCR-T细胞筛选并优先确定潜在靶点。对于表面膜靶点,SCAN-ACT提出单特异性靶点以及双特异性布尔逻辑门控CAR T细胞的潜在靶点对。对于肽-MHC靶点,SCAN-ACT提出与多种人类白细胞抗原结合的细胞内肽段。通过蛋白质表达和肽-MHC结合实验对选定的靶点进行验证。
我们将SCAN-ACT流程应用于软组织肉瘤(STS),分析了986,749个单细胞,以识别并优先确定395个单特异性CAR-T靶点、14,192个双特异性CAR-T靶点和5020个TCR-T细胞的肽-MHC靶点。提出的靶点和靶点对反映了STS的间充质、神经元和造血发育过程。我们在胶质母细胞瘤中进一步验证了SCAN-ACT,揭示了其通用性。
这项工作提供了一个强大的数据存储库以及一套基于网络且用户友好的分析工具,以加速实体瘤ACT的开发(https://scanact.stanford.edu/)。