Our work first established a framework for evaluating CAR target safety and selectivity using patient tumor single-cell transcriptomics data. Through a pan-cancer analysis, we demonstrated the near-optimality of existing CAR targets in most cancers while identifying novel promising targets for head and neck squamous cell carcinoma. Building on this foundation, we developed LogiCAR, a novel genetic algorithm that identifies logical combinations of surface antigens using AND, OR, and NOT operators. When applied to breast cancer cohorts, LogiCAR successfully identified triplet antigen combinations that outperform clinically approved single-antigen targets in efficacy while maintaining high safety profiles.
Building on these results, we will adapt the LogiCAR framework to address the unique challenges of pediatric acute myeloid leukemia (AML), where the similarity between malignant and healthy blood cells demands particularly precise target selection. Additionally, we will explore larger combinations of 4-5 antigens to potentially achieve even greater specificity in target cell recognition. This work aims to advance the field of CAR-T cell therapy by providing computational tools for rational target selection and combination strategies in both solid and liquid tumors.
Sanna Madan is a PhD student in Computer Science at the University of Maryland, College Park, primarily conducting her research at the National Cancer Institute's Cancer Data Science Laboratory through the NCI-UMD Partnership for Integrative Cancer Research. Her research focuses on developing computational methods to advance CAR-T cell therapy, particularly through the analysis of single-cell RNA sequencing data. She has developed novel approaches for identifying both single and combinatorial CAR targets, including LogiCAR, a genetic algorithm framework that identifies optimal logical combinations of surface antigens for enhanced cancer cell targeting. Through innovative computational approaches, her work addresses fundamental challenges in cancer therapeutic design, aiming to improve both the efficacy and safety of immunotherapy treatments. She works under the supervision of Dr. Eytan Ruppin and Professor Aravind Srinivasan.