AI-powered engineering and analysis of cyanobacterium vesicles targeting gastrointestinal cancer abstract gastrointestinal (GI) malignancies, such as gastric, colon, liver and pancreatic cancers,…

AI-powered engineering and analysis of cyanobacterium vesicles targeting gastrointestinal cancer abstract gastrointestinal (GI) malignancies, such as gastric, colon, liver and pancreatic cancers, represent some of the most common and deadly cancers worldwide. There are over 5000 clinical trials testing therapeutic candidates for GI cancers. Unfortunately, 75-80% of drug candidates fail due to efficacy and/or safety issues associated with ineffective in vivo delivery. This is particularly the case for biologicals such as RNA and protein therapeutics. There is thus an urgent need for developing a) precision drug delivery vehicles to increase the success rates of RNA and protein drugs and B) scalable biomanufacturing platforms that can provide sustainable treatment solutions. Here we propose such a platform based on reprogramming membrane vesicles from the cyanobacterium spirulina (arthrospira platensis). The platform combines advantages of I) state-of- the-art AI protein design algorithms, II) sensitive and rapid vesicle analysis and III) a well-tolerated, edible microbial production system, to improve targeted and oral delivery of RNA therapeutics for gastrointestinal cancer. In aim 1, we will apply AI pipeline to design new vesicle scaffold proteins and test for membrane anchoring and target binding. Subsequently in aim 2, we will engineer spirulina vesicles and assess cellular uptake in human cancer cell lines. The phase I proposal will focus on engineering vesicles to enable targeted RNA delivery to CLDN18.2-positive cancer cells of the GI origin. We envision this programmable spirulina vesicle platform as a transformative technology to help I) accelerate the development of RNA-based therapeutics for GI cancers (e.g. rnas for tumor suppressor P53, protac targeting oncogenic kras), and II) improve oral delivery and precision treatments to better patient outcomes.