Rouzanna Istvanffy | Search PubMed

PubMed2026

Pancreatic ductal adenocarcinoma: The Vision of Heracles.

Pancreatic ductal adenocarcinoma (PDAC) remains among the deadliest malignancies, as tumors evolve faster than therapies. Resistance is ecological, not merely KRAS driven, involving overlooked players like high-grade pancreatic intraepithelial neoplasias (PanINs), peripancreatic fat, stromal mechanics, myeloid-neural circuits, metabolic rewiring, and systemic host responses. We propose precision interception targeting PanIN/intraductal papillary mucinous neoplasm (IPMN) biology, spatial-functional-proteogenomic classification beyond transcriptomics, the Heracles Protocol (measure, prime, strike, and adapt), and integrated technologies from AI pathology to exosomal delivery and CRISPR-based synergy mapping, together making PDAC more tractable.

Humans↗

PubMed2026

Creating bottom-up RNA transfer vehicles from synthetic protein assemblies.

Evolution guides biological systems to populate ecological niches, with viruses among the most successful examples of this principle. Viruses evolved over billions of years to efficiently transfer genetic information. Although viruses are highly diverse, most have converged towards remarkable similarity in the size and shape of their capsids1,2. By contrast, generative models for protein design enable the creation of protein architectures that are absent from nature3-5. Here we investigate whether protein assemblies designed by artificial intelligence can be functionalized to construct nucleic acid transport vehicles that are independent of evolutionary trajectories. By combining natural protein domains with synthetic protein assemblies, we create more than 100 bottom-up RNA transfer vehicles with unique sizes and shapes. These vehicles surpass the RNA transfer efficiency of widely used delivery vehicles by several orders of magnitude. In addition, we demonstrate that their tropism can be programmed by incorporation of computationally designed peptide binders and use them to deliver therapeutically relevant cargo RNAs into a wide range of cellular models. We show the in vivo biodistribution of one of these vehicles in a mouse at near-single-cell resolution, confirm its safety, and use it to perform a gene-editing treatment strategy for Duchenne muscular dystrophy in patient-derived cells and a pig. Our work demonstrates how proteins created by generative artificial intelligence can be harnessed for the rational engineering of RNA transport systems with the desired properties by overcoming the limitations of natural protein diversity.

Journal Article↗