A multi-agent workflow converts CAR-T patient evidence into experimentally testable hypotheses
Journal:
bioRxiv
Published Date:
Jul 16, 2026
Abstract
The rapid expansion of chimeric antigen receptor (CAR) T cell studies has produced a fragmented evidence landscape linking publications, repository accessions, patient metadata and mechanistic observations. Here we present BioPathfinder, a multi-agent discovery engine for CAR-T research evidence construction, hypothesis generation and validation planning. Unlike existing LLM-based and agentic approaches centered on predefined CAR-T development tasks, BioPathfinder constructs a provenance-tracked resource linking scRNA-seq datasets from treated patients to their publications and uses it to generate diverse, falsifiable and dataset-aware mechanistic hypotheses prioritized for computational and experimental validation by role-specialized LLM reviewer subagents. Applied to the curated CAR-T-treated patient paper-dataset corpus, BioPathfinder nominated candidate mechanisms of CAR-T persistence, dysfunction and therapeutic resistance, including the hypothesis that genes associated with an NK-like transition program could be targeted to reduce CAR-T exhaustion and promote persistence. Patient scRNA-seq analysis showed that this NK-like transition-associated program was enriched in exhausted post-infusion CAR-T cell states. Virtual perturbation further prioritized transition-associated KLR-family receptor genes, including KLRC1, KLRD1 and KLRG1. Expert review selected KLRC1, encoding NKG2A, for experimental testing. In vitro and in vivo chronic-stimulation models showed that NKG2A marked CD8 CAR-T cells with activated and exhaustion-associated phenotypes. NKG2A blockade improved antitumour function and persistence-associated readouts in vivo. These results show that structured clinical single-cell evidence can be transformed by domain-specialized multi-agent systems into experimentally actionable CAR-T engineering hypotheses.
