Angus J. Lennaárd

The clinical use of chemotherapeutics is limited by several factors, including low cellular uptake, short circulation time, and severe adverse effects. Extracellular vesicles (EVs) have been suggested as a drug delivery platform with the potential to overcome these limitations. EVs are cell-derived, lipid bilayer nanoparticles, important for intercellular communication. They can transport bioactive cargo throughout the body, surmount biological barriers, and target a variety of tissues. Several small molecule drugs have been successfully incorporated into the lumen of EVs, permitting efficient transport to tumour tissue, increasing therapeutic potency, and reducing adverse effects. However, the cargo loading is often inadequate and refined methods are a prerequisite for successful utilisation of the platform. By systematically evaluating the effect of altered loading parameters for electroporation, such as total number of EVs, drug to EV ratio, buffers, pulse capacitance, and field strength, we were able to distinguish tendencies and correlations. This allowed us to design an optimised electroporation protocol for loading EVs with the chemotherapeutic drug doxorubicin. The loading technique demonstrated improved cargo loading and EV recovery, as well as drug potency, with a 190-fold increased response compared to naked doxorubicin.

Extracellular vesicles (EVs) function as natural delivery vectors and mediators of biological signals across tissues. Here, by leveraging these functionalities, we show that EVs decorated with an antibody-binding moiety specific for the fragment crystallizable (Fc) domain can be used as a modular delivery system for targeted cancer therapy. The Fc-EVs can be decorated with different types of immunoglobulin G antibody and thus be targeted to virtually any tissue of interest. Following optimization of the engineered EVs by screening Fc-binding and EV-sorting moieties, we show the targeting of EVs to cancer cells displaying the human epidermal receptor 2 or the programmed-death ligand 1, as well as lower tumour burden and extended survival of mice with subcutaneous melanoma tumours when systemically injected with EVs displaying an antibody for the programmed-death ligand 1 and loaded with the chemotherapeutic doxorubicin. EVs with Fc-binding domains may be adapted to display other Fc-fused proteins, bispecific antibodies and antibody-drug conjugates.

Abstract Upstream open reading frames (uORFs) are short translated regions that occur in the 5□ untranslated regions (5□ UTRs) of mRNA transcripts where they primarily serve to repress expression translation of the downstream primary open reading frame (pORF). Their widespread presence across mammalian transcriptomes suggests an important role in shaping the proteome, although the mechanistic basis of their regulatory effects remain incompletely understood. Here we present an integrated experimental and computational investigation into the features that govern uORF-mediated translation control. Using high-resolution proteomics data from 29 healthy human tissues and machine learning-based simulations, we have systematically dissected how features including uORF length, amino acid composition, start codon position, stop codon position, and Kozak context influence repressive activity, and performed experimental validation using reporter gene constructs. We also investigated how multiple uORFs within a single 5□ UTR can interact in synergistic or antagonistic ways, with the potential to produce counterintuitive effects on pORF translation. From these studies, we present a model of uORF function, suggesting a hierarchy of uORF feature importance, and proposing that a combination of uORF translation initiation probability, ribosome recycling rate, intercistronic ternary complex recharging requirements, and ribosome stalling mechanisms underlie uORF repressive activity. Together, these studies provide a comprehensive view of the molecular logic underlying uORF activity, offering new insights into their endogenous and highlighting their potential as targets for drug development.