Project Summary T cells play a central role in the immune response, detecting antigenic peptides cradled within MHC molecules (pMHCs) displayed on the surface of diseased cells via specific interactions with cell-surface T cell receptors (TCRs). This recognition triggers downstream T cell activation and cytotoxic killing. In vivo, T cells are exquisitely sensitive and specific, able to be activated by a single antigenic peptide displayed by a diseased cell. Immunotherapies attempt to harness this sensitivity and specificity to eliminate cancerous cells by either transfusing patients with T cells engineered to display TCRs specific for tumor-associated antigens (neoantigens) or injecting peptide ‘vaccines’ to stimulate expansion of neoantigen-specific T cell clones. Predicting which neoantigen/TCR combinations will activate a potent T cell response in a patient remains a formidable challenge. There are a vast number of potential pMHC/TCR complexes: MHC molecules are encoded by 23,000 HLA alleles, each MHC displays a ~9 amino acid peptide (209 possibilities), and each patient can express >1020 possible TCRs. While many techniques leverage next-generation sequencing to screen millions of pMHC/TCR combinations for high-affinity binders, these screens can test only a small fraction of possible combinations. Moreover, the strength of pMHC/TCR binding does not predict activation: many high-affinity peptides do not activate T cells, and many potent agonists bind with only moderate affinities. T cells generate pN to nN forces on pMHC/TCR complexes as they crawl over antigen-presenting cells, and emerging evidence has established that these biomechanical forces are essential for sensitive and specific TCR-pMHC recognition: pMHC/TCR complexes that drive potent activation form ‘catch’ bonds that strengthen under force, while those that do not form ‘slip’ bonds more likely to break. Thus, developing improved immunotherapies requires new technologies capable of testing large numbers of candidate pMHC/TCR interactions for their ability to form catch bonds and activate T cells under physiological forces. My lab is uniquely qualified to address this critical need. In prior work, we developed a microfluidic platform that enables recombinant cell-free expression, purification, and quantitative in vitro characterization of >1,500 proteins in hours and at low cost. Here, we will apply this powerful technology to systematically investigate which pMHC/TCR combinations form ‘catch’ bonds that predict activation (Platform 1) and which neoantigens are efficiently displayed by 1000s of different MHC sequences encoded by variable HLA alleles (Platform 2). To further test candidate pMHC/TCR combinations in their cellular context, we will apply a novel droplet-based technology we invented to co-encapsulate 10s of millions of T cell/APC pairs and sort them based on activation (Platform 3).

Project Narrative T cells recognize diseased cells via molecular interactions between T cell receptors (TCRs) and peptides presented by MHC molecules (pMHCs), and an improved ability to predict which pMHC/TCR pairs drive strong T cell responses could improve our ability to engineer personalized anti-cancer therapies without dangerous side effects. T cell crawling during immunosurveillance applies biomechanical forces to pMHC/TCR complexes that are crucial for sensitive and specific recognition, with activating pMHC/TCR pairs forming ‘catch’ bonds that strengthen under force, but current screening methods test pMHC/TCR binding in the absence of force and thus fail to predict potent agonists in vivo. Here, I will develop new microfluidic technologies that make it possible to systematically interrogate 10000s of pMHC/TCR complexes for their ability to form catch bonds and drive potent T cell activation, generating critical new tools and quantitative training data in the fight against cancer.