Year: 2024
Type: article
Abstract: Lysosome-targeting chimeras (LYTACs) are a promising therapeutic modality to drive the degradation of extracellular proteins. However, early versions of LYTAC contain synthetic glycopeptides that cannot be genetically encoded. Here we present our designs for a fully genetically encodable LYTAC (GELYTAC), making our tool compatible with integration into therapeutic cells for targeted delivery at diseased sites. To achieve this, we replaced the glycopeptide portion of LYTACs with the protein insulin like growth factor 2 (IGF2). After showing initial efficacy with wild type IGF2, we increased the potency of GELYTAC using directed evolution. Subsequently, we demonstrated that our engineered GELYTAC construct not only secretes from HEK293T cells but also from human primary T-cells to drive the uptake of various targets into receiver cells. Immune cells engineered to secrete GELYTAC thus represent a promising avenue for spatially-selective targeted protein degradation. Significance Statement Better therapeutic windows can be achieved by targeting therapeutics to their desired sites of action. For protein therapeutics, this might be achieved by engineering cell therapies that home to a tissue of interest and secrete the biologic drug locally. Here, we demonstrate that human primary T cells can be engineered to produce genetically encoded lysosome targeting chimeras (GELYTACs). These GELYTACs mediate the degradation of extracellular proteins associated with cancer progression. Thus, cells engineered to produce GELYTACs represent a potential new class of cancer therapeutics.
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Funders: Foundation for the National Institutes of Health, Virginia and D.K. Ludwig Fund for Cancer Research, Parker Institute for Cancer Immunotherapy, Chan Zuckerberg Initiative, Emerson Collective, Cancer Research UK, National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences
OpenAlex ID: W4393032910
