Abstract C042: Systematic discovery of logic-gated cell surface targets for enhanced solid tumor CAR therapy through single-cell transcriptomics

Abstract Background: Current CAR-T therapies for solid tumors are limited by suboptimal target selection, with single antigens failing to address tumor heterogeneity and causing on-target, off-tumor toxicities. Systematic identification of multi-target combinations using logic gates (AND, OR, NOT) represents an untapped approach for discovering safer, more effective CAR immunotherapy targets. Methods: We developed LogiCAR designer, a genetic algorithm-based framework that systematically screens 2,758 cell surface proteins to identify optimal 1-5 gene logic-gated target combinations (i.e., ‘circuits’) from single-cell transcriptomics data. Applied to the largest breast cancer single-cell dataset (∼2 million cells, >620k tumor cells from 342 patients across 17 cohorts), we optimized tumor-targeting efficacy while maintaining safety across 689,601 normal cells from 31 Human Protein Atlas tissues. Comprehensive target validation included RNA and protein expression profiling across major human tissues and tumor microenvironment specificity analysis. Results: Our systematic approach identified novel cell surface targets with superior profiles compared to current clinical candidates. The top 3-gene circuit ('GABRP | PRLR | VTCN1') achieved 60% tumor-targeting efficacy—234% higher than the best clinical trial targets. Newly discovered single targets (ELAPOR1, PRLR, BAMBI, LDLRAD3) demonstrated consistent tumor-specific expression (>2-fold tumor vs. non-tumor cells, p<0.05) across all datasets, unlike current clinical targets. Safety profiling revealed that many existing targets (BSG, EPCAM, TACSTD2) showed concerning expression in critical normal tissues, while our identified circuits maintained superior safety profiles. Finally, shared circuits were still ineffective for some patients, prompting development of personalized approaches. Individualized target combinations addressed intratumor heterogeneity: in our new 82-patient multi-ethnicity cohort, personalized circuits reached 98% mean efficacy with 76% of patients achieving complete response-equivalent targeting. Conclusions: This work establishes the first systematic molecular target discovery pipeline for multi-antigen therapeutic design, identifying previously unrecognized targets with superior efficacy-safety profiles. Our approach transforms target selection from empirical to data-driven, providing a foundation for next-generation precision therapeutics across cancer types. Citation Format: Sanna Madan, Tian-Gen Chang, Andrew Martinez, Alexandra R. Harris, Huaitian Liu, Saugato R. Dhruba, Binbin Wang, Padma S. Rajagopal, Sanju Sinha, Aravind Srinivasan, Simon R. V. Knott, Shahin Sayed, Francis Makokha, Chi-Ping Day, Gretchen L. Gierach, Stefan Ambs, Alejandro A. Schäffer, Eytan Ruppin. Systematic discovery of logic-gated cell surface targets for enhanced solid tumor CAR therapy through single-cell transcriptomics [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C042.